is artificial intelligence a threat essay

May 25, 2023

Here’s Why AI May Be Extremely Dangerous—Whether It’s Conscious or Not

Artificial intelligence algorithms will soon reach a point of rapid self-improvement that threatens our ability to control them and poses great potential risk to humanity

By Tamlyn Hunt

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“The idea that this stuff could actually get smarter than people.... I thought it was way off…. Obviously, I no longer think that,” Geoffrey Hinton, one of Google's top artificial intelligence scientists, also known as “ the godfather of AI ,” said after he quit his job in April so that he can warn about the dangers of this technology .

He’s not the only one worried. A 2023 survey of AI experts found that 36 percent fear that AI development may result in a “nuclear-level catastrophe.” Almost 28,000 people have signed on to an open letter written by the Future of Life Institute, including Steve Wozniak, Elon Musk, the CEOs of several AI companies and many other prominent technologists, asking for a six-month pause or a moratorium on new advanced AI development.

As a researcher in consciousness, I share these strong concerns about the rapid development of AI, and I am a co-signer of the Future of Life open letter.

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Why are we all so concerned? In short: AI development is going way too fast.

The key issue is the profoundly rapid improvement in conversing among the new crop of advanced "chatbots," or what are technically called “large language models” (LLMs). With this coming “AI explosion,” we will probably have just one chance to get this right.

If we get it wrong, we may not live to tell the tale. This is not hyperbole.

This rapid acceleration promises to soon result in “artificial general intelligence” (AGI), and when that happens, AI will be able to improve itself with no human intervention. It will do this in the same way that, for example, Google’s AlphaZero AI learned how to play chess better than even the very best human or other AI chess players in just nine hours from when it was first turned on. It achieved this feat by playing itself millions of times over.

A team of Microsoft researchers analyzing OpenAI’s GPT-4 , which I think is the best of the new advanced chatbots currently available, said it had, "sparks of advanced general intelligence" in a new preprint paper .

In testing GPT-4, it performed better than 90 percent of human test takers on the Uniform Bar Exam, a standardized test used to certify lawyers for practice in many states. That figure was up from just 10 percent in the previous GPT-3.5 version, which was trained on a smaller data set. They found similar improvements in dozens of other standardized tests.

Most of these tests are tests of reasoning. This is the main reason why Bubeck and his team concluded that GPT-4 “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.”

This pace of change is why Hinton told the New York Times : "Look at how it was five years ago and how it is now. Take the difference and propagate it forwards. That’s scary.” In a mid-May Senate hearing on the potential of AI, Sam Altman, the head of OpenAI called regulation “crucial.”

Once AI can improve itself, which may be not more than a few years away, and could in fact already be here now, we have no way of knowing what the AI will do or how we can control it. This is because superintelligent AI (which by definition can surpass humans in a broad range of activities) will—and this is what I worry about the most—be able to run circles around programmers and any other human by manipulating humans to do its will; it will also have the capacity to act in the virtual world through its electronic connections, and to act in the physical world through robot bodies.

This is known as the “control problem” or the “alignment problem” (see philosopher Nick Bostrom’s book Superintelligence for a good overview ) and has been studied and argued about by philosophers and scientists, such as Bostrom, Seth Baum and Eliezer Yudkowsky , for decades now.

I think of it this way: Why would we expect a newborn baby to beat a grandmaster in chess? We wouldn’t. Similarly, why would we expect to be able to control superintelligent AI systems? (No, we won’t be able to simply hit the off switch, because superintelligent AI will have thought of every possible way that we might do that and taken actions to prevent being shut off.)

Here’s another way of looking at it: a superintelligent AI will be able to do in about one second what it would take a team of 100 human software engineers a year or more to complete. Or pick any task, like designing a new advanced airplane or weapon system, and superintelligent AI could do this in about a second.

Once AI systems are built into robots, they will be able to act in the real world, rather than only the virtual (electronic) world, with the same degree of superintelligence, and will of course be able to replicate and improve themselves at a superhuman pace.

Any defenses or protections we attempt to build into these AI “gods,” on their way toward godhood, will be anticipated and neutralized with ease by the AI once it reaches superintelligence status. This is what it means to be superintelligent.

We won’t be able to control them because anything we think of, they will have already thought of, a million times faster than us. Any defenses we’ve built in will be undone, like Gulliver throwing off the tiny strands the Lilliputians used to try and restrain him.

Some argue that these LLMs are just automation machines with zero consciousness , the implication being that if they’re not conscious they have less chance of breaking free from their programming. Even if these language models, now or in the future, aren’t at all conscious, this doesn’t matter. For the record, I agree that it’s unlikely that they have any actual consciousness at this juncture—though I remain open to new facts as they come in.

Regardless, a nuclear bomb can kill millions without any consciousness whatsoever. In the same way, AI could kill millions with zero consciousness, in a myriad ways, including potentially use of nuclear bombs either directly (much less likely) or through manipulated human intermediaries (more likely).

So, the debates about consciousness and AI really don’t figure very much into the debates about AI safety.

Yes, language models based on GPT-4 and many other models are already circulating widely . But the moratorium being called for is to stop development of any new models more powerful than 4.0—and this can be enforced, with force if required. Training these more powerful models requires massive server farms and energy. They can be shut down.

My ethical compass tells me that it is very unwise to create these systems when we know already we won’t be able to control them, even in the relatively near future. Discernment is knowing when to pull back from the edge. Now is that time.

We should not open Pandora’s box any more than it already has been opened.

This is an opinion and analysis article, and the views expressed by the author or authors are not necessarily those of  Scientific American.

SQ10. What are the most pressing dangers of AI?

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As AI systems prove to be increasingly beneficial in real-world applications, they have broadened their reach, causing risks of misuse, overuse, and explicit abuse to proliferate. As AI systems increase in capability and as they are integrated more fully into societal infrastructure, the implications of losing meaningful control over them become more concerning. 1 New research efforts are aimed at re-conceptualizing the foundations of the field to make AI systems less reliant on explicit, and easily misspecified, objectives. 2 A particularly visible danger is that AI can make it easier to build machines that can spy and even kill at scale . But there are many other important and subtler dangers at present.

In this section

Techno-solutionism, dangers of adopting a statistical perspective on justice, disinformation and threat to democracy, discrimination and risk in the medical setting.

One of the most pressing dangers of AI is techno-solutionism, the view that AI can be seen as a panacea when it is merely a tool. 3 As we see more AI advances, the temptation to apply AI decision-making to all societal problems increases. But technology often creates larger problems in the process of solving smaller ones. For example, systems that streamline and automate the application of social services can quickly become rigid and deny access to migrants or others who fall between the cracks. 4

When given the choice between algorithms and humans, some believe algorithms will always be the less-biased choice. Yet, in 2018, Amazon found it necessary to discard a proprietary recruiting tool because the historical data it was trained on resulted in a system that was systematically biased against women. 5 Automated decision-making can often serve to replicate, exacerbate, and even magnify the same bias we wish it would remedy.

Indeed, far from being a cure-all, technology can actually create feedback loops that worsen discrimination. Recommendation algorithms, like Google’s page rank, are trained to identify and prioritize the most “relevant” items based on how other users engage with them. As biased users feed the algorithm biased information, it responds with more bias, which informs users’ understandings and deepens their bias, and so on. 6 Because all technology is the product of a biased system, 7 techno-solutionism’s flaws run deep: 8 a creation is limited by the limitations of its creator.

Automated decision-making may produce skewed results that replicate and amplify existing biases. A potential danger, then, is when the public accepts AI-derived conclusions as certainties. This determinist approach to AI decision-making can have dire implications in both criminal and healthcare settings. AI-driven approaches like PredPol, software originally developed by the Los Angeles Police Department and UCLA that purports to help protect one in 33 US citizens, 9 predict when, where, and how crime will occur. A 2016 case study of a US city noted that the approach disproportionately projected crimes in areas with higher populations of non-white and low-income residents. 10 When datasets disproportionately represents the lower power members of society, flagrant discrimination is a likely result.

Sentencing decisions are increasingly decided by proprietary algorithms that attempt to assess whether a defendant will commit future crimes, leading to concerns that justice is being outsourced to software. 11 As AI becomes increasingly capable of analyzing more and more factors that may correlate with a defendant's perceived risk, courts and society at large may mistake an algorithmic probability for fact. This dangerous reality means that an algorithmic estimate of an individual’s risk to society may be interpreted by others as a near certainty—a misleading outcome even the original tool designers warned against. Even though a statistically driven AI system could be built to report a degree of credence along with every prediction, 12 there’s no guarantee that the people using these predictions will make intelligent use of them. Taking probability for certainty means that the past will always dictate the future.

There is an aura of neutrality and impartiality associated with AI decision-making in some corners of the public consciousness, resulting in systems being accepted as objective even though they may be the result of biased historical decisions or even blatant discrimination. All data insights rely on some measure of interpretation. As a concrete example, an audit of a resume-screening tool found that the two main factors it associated most strongly with positive future job performance were whether the applicant was named Jared, and whether he played high school lacrosse. 13 Undesirable biases can be hidden behind both the opaque nature of the technology used and the use of proxies, nominally innocent attributes that enable a decision that is fundamentally biased. An algorithm fueled by data in which gender, racial, class, and ableist biases are pervasive can effectively reinforce these biases without ever explicitly identifying them in the code. 

Without transparency concerning either the data or the AI algorithms that interpret it, the public may be left in the dark as to how decisions that materially impact their lives are being made. Lacking adequate information to bring a legal claim, people can lose access to both due process and redress when they feel they have been improperly or erroneously judged by AI systems. Large gaps in case law make applying Title VII—the primary existing legal framework in the US for employment discrimination—to cases of algorithmic discrimination incredibly difficult. These concerns are exacerbated by algorithms that go beyond traditional considerations such as a person’s credit score to instead consider any and all variables correlated to the likelihood that they are a safe investment. A statistically significant correlation has been shown among Europeans between loan risk and whether a person uses a Mac or PC and whether they include their name in their email address—which turn out to be proxies for affluence. 14 Companies that use such attributes, even if they do indeed provide improvements in model accuracy, may be breaking the law when these attributes also clearly correlate with a protected class like race. Loss of autonomy can also result from AI-created “information bubbles” that narrowly constrict each individual’s online experience to the point that they are unaware that valid alternative perspectives even exist.

AI systems are being used in the service of disinformation on the internet, giving them the potential to become a threat to democracy and a tool for fascism. From deepfake videos to online bots manipulating public discourse by feigning consensus and spreading fake news, 15 there is the danger of AI systems undermining social trust. The technology can be co-opted by criminals, rogue states, ideological extremists, or simply special interest groups, to manipulate people for economic gain or political advantage. Disinformation poses serious threats to society, as it effectively changes and manipulates evidence to create social feedback loops that undermine any sense of objective truth. The debates about what is real quickly evolve into debates about who gets to decide what is real, resulting in renegotiations of power structures that often serve entrenched interests. 16

While personalized medicine is a good potential application of AI, there are dangers. Current business models for AI-based health applications tend to focus on building a single system—for example, a deterioration predictor—that can be sold to many buyers. However, these systems often do not generalize beyond their training data. Even differences in how clinical tests are ordered can throw off predictors, and, over time, a system’s accuracy will often degrade as practices change. Clinicians and administrators are not well-equipped to monitor and manage these issues, and insufficient thought given to the human factors of AI integration has led to oscillation between mistrust of the system (ignoring it) and over-reliance on the system (trusting it even when it is wrong), a central concern of the 2016 AI100 report.

These concerns are troubling in general in the high-risk setting that is healthcare, and even more so because marginalized populations—those that already face discrimination from the health system from both structural factors (like lack of access) and scientific factors (like guidelines that were developed from trials on other populations)—may lose even more. Today and in the near future, AI systems built on machine learning are used to determine post-operative personalized pain management plans for some patients and in others to predict the likelihood that an individual will develop breast cancer. AI algorithms are playing a role in decisions concerning distributing organs, vaccines, and other elements of healthcare. Biases in these approaches can have literal life-and-death stakes.

In 2019, the story broke that Optum, a health-services algorithm used to determine which patients may benefit from extra medical care, exhibited fundamental racial biases. The system designers ensured that race was precluded from consideration, but they also asked the algorithm to consider the future cost of a patient to the healthcare system. 17 While intended to capture a sense of medical severity, this feature in fact served as a proxy for race: controlling for medical needs, care for Black patients averages $1,800 less per year.

New technologies are being developed every day to treat serious medical issues. A new algorithm trained to identify melanomas was shown to be more accurate than doctors in a recent study, but the potential for the algorithm to be biased against Black patients is significant as the algorithm was trained using majority light-skinned groups. 18 The stakes are especially high for melanoma diagnoses, where the five-year survival rate is 17 percentage points less for Black Americans than white. While technology has the potential to generate quicker diagnoses and thus close this survival gap, a machine-learning algorithm is only as good as its data set. An improperly trained algorithm could do more harm than good for patients at risk, missing cancers altogether or generating false positives. As new algorithms saturate the market with promises of medical miracles, losing sight of the biases ingrained in their outcomes could contribute to a loss of human biodiversity, as individuals who are left out of initial data sets are denied adequate care. While the exact long-term effects of algorithms in healthcare are unknown, their potential for bias replication means any advancement they produce for the population in aggregate—from diagnosis to resource distribution—may come at the expense of the most vulnerable.

[1]  Brian Christian, The Alignment Problem: Machine Learning and Human Values, W. W. Norton & Company, 2020

[2]   https://humancompatible.ai/app/uploads/2020/11/CHAI-2020-Progress-Report-public-9-30.pdf  

[3]   https://knightfoundation.org/philanthropys-techno-solutionism-problem/  

[4]   https://www.theguardian.com/world/2021/jan/12/french-woman-spends-three-years-trying-to-prove-she-is-not-dead ; https://virginia-eubanks.com/ (“Automating inequality”)

[5]   https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G

[6]  Safiya Umoja Noble, Algorithms of Oppression: How Search Engines Reinforce Racism , NYU Press, 2018 

[7]  Ruha Benjamin, Race After Technology: Abolitionist Tools for the New Jim Code , Polity, 2019

[8]   https://www.publicbooks.org/the-folly-of-technological-solutionism-an-interview-with-evgeny-morozov/

[9]   https://predpol.com/about  

[10]  Kristian Lum and William Isaac, “To predict and serve?” Significance , October 2016, https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1740-9713.2016.00960.x

[11]  Jessica M. Eaglin, “Technologically Distorted Conceptions of Punishment,” https://www.repository.law.indiana.edu/cgi/viewcontent.cgi?article=3862&context=facpub  

[12]  Riccardo Fogliato, Maria De-Arteaga, and Alexandra Chouldechova, “Lessons from the Deployment of an Algorithmic Tool in Child Welfare,” https://fair-ai.owlstown.net/publications/1422  

[13]   https://qz.com/1427621/companies-are-on-the-hook-if-their-hiring-algorithms-are-biased/  

[14]   https://www.fdic.gov/analysis/cfr/2018/wp2018/cfr-wp2018-04.pdf  

[15]  Ben Buchanan, Andrew Lohn, Micah Musser, and Katerina Sedova, “Truth, Lies, and Automation,” https://cset.georgetown.edu/publication/truth-lies-and-automation/  

[16]  Britt Paris and Joan Donovan, “Deepfakes and Cheap Fakes: The Manipulation of Audio and Visual Evidence,” https://datasociety.net/library/deepfakes-and-cheap-fakes/  

[17]   https://www.washingtonpost.com/health/2019/10/24/racial-bias-medical-algorithm-favors-white-patients-over-sicker-black-patients/ .

[18]   https://www.theatlantic.com/health/archive/2018/08/machine-learning-dermatology-skin-color/567619/

Cite This Report

Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven Sloman, Shannon Vallor, and Toby Walsh. "Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report." Stanford University, Stanford, CA, September 2021. Doc:  http://ai100.stanford.edu/2021-report. Accessed: September 16, 2021.

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© 2021 by Stanford University. Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report is made available under a Creative Commons Attribution-NoDerivatives 4.0 License (International):  https://creativecommons.org/licenses/by-nd/4.0/ .

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• Artificial Intelligence and the Future of Humans

Experts say the rise of artificial intelligence will make most people better off over the next decade, but many have concerns about how advances in AI will affect what it means to be human, to be productive and to exercise free will

Table of contents.

• 1. Concerns about human agency, evolution and survival
• 2. Solutions to address AI’s anticipated negative impacts
• 3. Improvements ahead: How humans and AI might evolve together in the next decade
• About this canvassing of experts
• Acknowledgments

Digital life is augmenting human capacities and disrupting eons-old human activities. Code-driven systems have spread to more than half of the world’s inhabitants in ambient information and connectivity, offering previously unimagined opportunities and unprecedented threats. As emerging algorithm-driven artificial intelligence (AI) continues to spread, will people be better off than they are today?

Some 979 technology pioneers, innovators, developers, business and policy leaders, researchers and activists answered this question in a canvassing of experts conducted in the summer of 2018.

The experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities. They spoke of the wide-ranging possibilities; that computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation. They said “smart” systems in communities, in vehicles, in buildings and utilities, on farms and in business processes will save time, money and lives and offer opportunities for individuals to enjoy a more-customized future.

Many focused their optimistic remarks on health care and the many possible applications of AI in diagnosing and treating patients or helping senior citizens live fuller and healthier lives. They were also enthusiastic about AI’s role in contributing to broad public-health programs built around massive amounts of data that may be captured in the coming years about everything from personal genomes to nutrition. Additionally, a number of these experts predicted that AI would abet long-anticipated changes in formal and informal education systems.

Yet, most experts, regardless of whether they are optimistic or not, expressed concerns about the long-term impact of these new tools on the essential elements of being human. All respondents in this non-scientific canvassing were asked to elaborate on why they felt AI would leave people better off or not. Many shared deep worries, and many also suggested pathways toward solutions. The main themes they sounded about threats and remedies are outlined in the accompanying table.

[chart id=”21972″]

Specifically, participants were asked to consider the following:

“Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties.

Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today?”

Overall, and despite the downsides they fear, 63% of respondents in this canvassing said they are hopeful that most individuals will be mostly better off in 2030, and 37% said people will not be better off.

A number of the thought leaders who participated in this canvassing said humans’ expanding reliance on technological systems will only go well if close attention is paid to how these tools, platforms and networks are engineered, distributed and updated. Some of the powerful, overarching answers included those from:

Sonia Katyal , co-director of the Berkeley Center for Law and Technology and a member of the inaugural U.S. Commerce Department Digital Economy Board of Advisors, predicted, “In 2030, the greatest set of questions will involve how perceptions of AI and their application will influence the trajectory of civil rights in the future. Questions about privacy, speech, the right of assembly and technological construction of personhood will all re-emerge in this new AI context, throwing into question our deepest-held beliefs about equality and opportunity for all. Who will benefit and who will be disadvantaged in this new world depends on how broadly we analyze these questions today, for the future.”

We need to work aggressively to make sure technology matches our values. Erik Brynjolfsson

[machine learning]

Bryan Johnson , founder and CEO of Kernel, a leading developer of advanced neural interfaces, and OS Fund, a venture capital firm, said, “I strongly believe the answer depends on whether we can shift our economic systems toward prioritizing radical human improvement and staunching the trend toward human irrelevance in the face of AI. I don’t mean just jobs; I mean true, existential irrelevance, which is the end result of not prioritizing human well-being and cognition.”

Andrew McLaughlin , executive director of the Center for Innovative Thinking at Yale University, previously deputy chief technology officer of the United States for President Barack Obama and global public policy lead for Google, wrote, “2030 is not far in the future. My sense is that innovations like the internet and networked AI have massive short-term benefits, along with long-term negatives that can take decades to be recognizable. AI will drive a vast range of efficiency optimizations but also enable hidden discrimination and arbitrary penalization of individuals in areas like insurance, job seeking and performance assessment.”

Michael M. Roberts , first president and CEO of the Internet Corporation for Assigned Names and Numbers (ICANN) and Internet Hall of Fame member, wrote, “The range of opportunities for intelligent agents to augment human intelligence is still virtually unlimited. The major issue is that the more convenient an agent is, the more it needs to know about you – preferences, timing, capacities, etc. – which creates a tradeoff of more help requires more intrusion. This is not a black-and-white issue – the shades of gray and associated remedies will be argued endlessly. The record to date is that convenience overwhelms privacy. I suspect that will continue.”

danah boyd , a principal researcher for Microsoft and founder and president of the Data & Society Research Institute, said, “AI is a tool that will be used by humans for all sorts of purposes, including in the pursuit of power. There will be abuses of power that involve AI, just as there will be advances in science and humanitarian efforts that also involve AI. Unfortunately, there are certain trend lines that are likely to create massive instability. Take, for example, climate change and climate migration. This will further destabilize Europe and the U.S., and I expect that, in panic, we will see AI be used in harmful ways in light of other geopolitical crises.”

Amy Webb , founder of the Future Today Institute and professor of strategic foresight at New York University, commented, “The social safety net structures currently in place in the U.S. and in many other countries around the world weren’t designed for our transition to AI. The transition through AI will last the next 50 years or more. As we move farther into this third era of computing, and as every single industry becomes more deeply entrenched with AI systems, we will need new hybrid-skilled knowledge workers who can operate in jobs that have never needed to exist before. We’ll need farmers who know how to work with big data sets. Oncologists trained as robotocists. Biologists trained as electrical engineers. We won’t need to prepare our workforce just once, with a few changes to the curriculum. As AI matures, we will need a responsive workforce, capable of adapting to new processes, systems and tools every few years. The need for these fields will arise faster than our labor departments, schools and universities are acknowledging. It’s easy to look back on history through the lens of present – and to overlook the social unrest caused by widespread technological unemployment. We need to address a difficult truth that few are willing to utter aloud: AI will eventually cause a large number of people to be permanently out of work. Just as generations before witnessed sweeping changes during and in the aftermath of the Industrial Revolution, the rapid pace of technology will likely mean that Baby Boomers and the oldest members of Gen X – especially those whose jobs can be replicated by robots – won’t be able to retrain for other kinds of work without a significant investment of time and effort.”

Barry Chudakov , founder and principal of Sertain Research, commented, “By 2030 the human-machine/AI collaboration will be a necessary tool to manage and counter the effects of multiple simultaneous accelerations: broad technology advancement, globalization, climate change and attendant global migrations. In the past, human societies managed change through gut and intuition, but as Eric Teller, CEO of Google X, has said, ‘Our societal structures are failing to keep pace with the rate of change.’ To keep pace with that change and to manage a growing list of ‘wicked problems’ by 2030, AI – or using Joi Ito’s phrase, extended intelligence – will value and revalue virtually every area of human behavior and interaction. AI and advancing technologies will change our response framework and time frames (which in turn, changes our sense of time). Where once social interaction happened in places – work, school, church, family environments – social interactions will increasingly happen in continuous, simultaneous time. If we are fortunate, we will follow the 23 Asilomar AI Principles outlined by the Future of Life Institute and will work toward ‘not undirected intelligence but beneficial intelligence.’ Akin to nuclear deterrence stemming from mutually assured destruction, AI and related technology systems constitute a force for a moral renaissance. We must embrace that moral renaissance, or we will face moral conundrums that could bring about human demise. … My greatest hope for human-machine/AI collaboration constitutes a moral and ethical renaissance – we adopt a moonshot mentality and lock arms to prepare for the accelerations coming at us. My greatest fear is that we adopt the logic of our emerging technologies – instant response, isolation behind screens, endless comparison of self-worth, fake self-presentation – without thinking or responding smartly.”

John C. Havens , executive director of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems and the Council on Extended Intelligence, wrote, “Now, in 2018, a majority of people around the world can’t access their data, so any ‘human-AI augmentation’ discussions ignore the critical context of who actually controls people’s information and identity. Soon it will be extremely difficult to identify any autonomous or intelligent systems whose algorithms don’t interact with human data in one form or another.”

At stake is nothing less than what sort of society we want to live in and how we experience our humanity. Batya Friedman

Batya Friedman , a human-computer interaction professor at the University of Washington’s Information School, wrote, “Our scientific and technological capacities have and will continue to far surpass our moral ones – that is our ability to use wisely and humanely the knowledge and tools that we develop. … Automated warfare – when autonomous weapons kill human beings without human engagement – can lead to a lack of responsibility for taking the enemy’s life or even knowledge that an enemy’s life has been taken. At stake is nothing less than what sort of society we want to live in and how we experience our humanity.”

Greg Shannon , chief scientist for the CERT Division at Carnegie Mellon University, said, “Better/worse will appear 4:1 with the long-term ratio 2:1. AI will do well for repetitive work where ‘close’ will be good enough and humans dislike the work. … Life will definitely be better as AI extends lifetimes, from health apps that intelligently ‘nudge’ us to health, to warnings about impending heart/stroke events, to automated health care for the underserved (remote) and those who need extended care (elder care). As to liberty, there are clear risks. AI affects agency by creating entities with meaningful intellectual capabilities for monitoring, enforcing and even punishing individuals. Those who know how to use it will have immense potential power over those who don’t/can’t. Future happiness is really unclear. Some will cede their agency to AI in games, work and community, much like the opioid crisis steals agency today. On the other hand, many will be freed from mundane, unengaging tasks/jobs. If elements of community happiness are part of AI objective functions, then AI could catalyze an explosion of happiness.”

Kostas Alexandridis , author of “Exploring Complex Dynamics in Multi-agent-based Intelligent Systems,” predicted, “Many of our day-to-day decisions will be automated with minimal intervention by the end-user. Autonomy and/or independence will be sacrificed and replaced by convenience. Newer generations of citizens will become more and more dependent on networked AI structures and processes. There are challenges that need to be addressed in terms of critical thinking and heterogeneity. Networked interdependence will, more likely than not, increase our vulnerability to cyberattacks. There is also a real likelihood that there will exist sharper divisions between digital ‘haves’ and ‘have-nots,’ as well as among technologically dependent digital infrastructures. Finally, there is the question of the new ‘commanding heights’ of the digital network infrastructure’s ownership and control.”

Oscar Gandy , emeritus professor of communication at the University of Pennsylvania, responded, “We already face an ungranted assumption when we are asked to imagine human-machine ‘collaboration.’ Interaction is a bit different, but still tainted by the grant of a form of identity – maybe even personhood – to machines that we will use to make our way through all sorts of opportunities and challenges. The problems we will face in the future are quite similar to the problems we currently face when we rely upon ‘others’ (including technological systems, devices and networks) to acquire things we value and avoid those other things (that we might, or might not be aware of).”

James Scofield O’Rourke , a professor of management at the University of Notre Dame, said, “Technology has, throughout recorded history, been a largely neutral concept. The question of its value has always been dependent on its application. For what purpose will AI and other technological advances be used? Everything from gunpowder to internal combustion engines to nuclear fission has been applied in both helpful and destructive ways. Assuming we can contain or control AI (and not the other way around), the answer to whether we’ll be better off depends entirely on us (or our progeny). ‘The fault, dear Brutus, is not in our stars, but in ourselves, that we are underlings.’”

Simon Biggs , a professor of interdisciplinary arts at the University of Edinburgh, said, “AI will function to augment human capabilities. The problem is not with AI but with humans. As a species we are aggressive, competitive and lazy. We are also empathic, community minded and (sometimes) self-sacrificing. We have many other attributes. These will all be amplified. Given historical precedent, one would have to assume it will be our worst qualities that are augmented. My expectation is that in 2030 AI will be in routine use to fight wars and kill people, far more effectively than we can currently kill. As societies we will be less affected by this as we currently are, as we will not be doing the fighting and killing ourselves. Our capacity to modify our behaviour, subject to empathy and an associated ethical framework, will be reduced by the disassociation between our agency and the act of killing. We cannot expect our AI systems to be ethical on our behalf – they won’t be, as they will be designed to kill efficiently, not thoughtfully. My other primary concern is to do with surveillance and control. The advent of China’s Social Credit System (SCS) is an indicator of what it likely to come. We will exist within an SCS as AI constructs hybrid instances of ourselves that may or may not resemble who we are. But our rights and affordances as individuals will be determined by the SCS. This is the Orwellian nightmare realised.”

Mark Surman , executive director of the Mozilla Foundation, responded, “AI will continue to concentrate power and wealth in the hands of a few big monopolies based on the U.S. and China. Most people – and parts of the world – will be worse off.”

William Uricchio , media scholar and professor of comparative media studies at MIT, commented, “AI and its related applications face three problems: development at the speed of Moore’s Law, development in the hands of a technological and economic elite, and development without benefit of an informed or engaged public. The public is reduced to a collective of consumers awaiting the next technology. Whose notion of ‘progress’ will prevail? We have ample evidence of AI being used to drive profits, regardless of implications for long-held values; to enhance governmental control and even score citizens’ ‘social credit’ without input from citizens themselves. Like technologies before it, AI is agnostic. Its deployment rests in the hands of society. But absent an AI-literate public, the decision of how best to deploy AI will fall to special interests. Will this mean equitable deployment, the amelioration of social injustice and AI in the public service? Because the answer to this question is social rather than technological, I’m pessimistic. The fix? We need to develop an AI-literate public, which means focused attention in the educational sector and in public-facing media. We need to assure diversity in the development of AI technologies. And until the public, its elected representatives and their legal and regulatory regimes can get up to speed with these fast-moving developments we need to exercise caution and oversight in AI’s development.”

The remainder of this report is divided into three sections that draw from hundreds of additional respondents’ hopeful and critical observations: 1) concerns about human-AI evolution, 2) suggested solutions to address AI’s impact, and 3) expectations of what life will be like in 2030, including respondents’ positive outlooks on the quality of life and the future of work, health care and education. Some responses are lightly edited for style.

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Why We Should Think About the Threat of Artificial Intelligence

By Gary Marcus

If the New York Times ’ s latest article is to be believed, artificial intelligence is moving so fast it sometimes seems almost “ magical .” Self-driving cars have arrived; Siri can listen to your voice and find the nearest movie theatre; and I.B.M. just set the “Jeopardy”-conquering Watson to work on medicine, initially training medical students, perhaps eventually helping in diagnosis. Scarcely a month goes by without the announcement of a new A.I. product or technique. Yet, some of the enthusiasm may be premature: as I’ve noted previously, we still haven’t produced machines with common sense , vision , natural language processing, or the ability to create other machines. Our efforts at directly simulating human brains remain primitive.

Still, at some level, the only real difference between enthusiasts and skeptics is a time frame. The futurist and inventor Ray Kurzweil thinks true, human-level A.I. will be here in less than two decades. My estimate is at least double that, especially given how little progress has been made in computing common sense; the challenges in building A.I., especially at the software level, are much harder than Kurzweil lets on.

But a century from now, nobody will much care about how long it took, only what happened next. It’s likely that machines will be smarter than us before the end of the century—not just at chess or trivia questions but at just about everything, from mathematics and engineering to science and medicine. There might be a few jobs left for entertainers, writers, and other creative types, but computers will eventually be able to program themselves, absorb vast quantities of new information, and reason in ways that we carbon-based units can only dimly imagine. And they will be able to do it every second of every day, without sleep or coffee breaks.

For some people, that future is a wonderful thing. Kurzweil has written about a rapturous singularity in which we merge with machines and upload our souls for immortality; Peter Diamandis has argued that advances in A.I. will be one key to ushering in a new era of “ abundance ,” with enough food, water, and consumer gadgets for all. Skeptics like Eric Brynjolfsson and I have worried about the consequences of A.I. and robotics for employment . But even if you put aside the sort of worries about what super-advanced A.I. might do to the labor market, there’s another concern, too: that powerful A.I. might threaten us more directly, by battling us for resources.

Most people see that sort of fear as silly science-fiction drivel—the stuff of “The Terminator” and “The Matrix.” To the extent that we plan for our medium-term future, we worry about asteroids, the decline of fossil fuels, and global warming, not robots. But a dark new book by James Barrat, “ Our Final Invention: Artificial Intelligence and the End of the Human Era ,” lays out a strong case for why we should be at least a little worried.

Barrat’s core argument, which he borrows from the A.I. researcher Steve Omohundro , is that the drive for self-preservation and resource acquisition may be inherent in all goal-driven systems of a certain degree of intelligence. In Omohundro’s words, “if it is smart enough, a robot that is designed to play chess might also want to be build a spaceship,” in order to obtain more resources for whatever goals it might have. A purely rational artificial intelligence, Barrat writes, might expand “its idea of self-preservation … to include proactive attacks on future threats,” including, presumably, people who might be loathe to surrender their resources to the machine. Barrat worries that “without meticulous, countervailing instructions, a self-aware, self-improving, goal-seeking system will go to lengths we’d deem ridiculous to fulfill its goals,” even, perhaps, commandeering all the world’s energy in order to maximize whatever calculation it happened to be interested in.

Of course, one could try to ban super-intelligent computers altogether. But “the competitive advantage—economic, military, even artistic—of every advance in automation is so compelling,” Vernor Vinge, the mathematician and science-fiction author, wrote , “that passing laws, or having customs, that forbid such things merely assures that someone else will.”

If machines will eventually overtake us, as virtually everyone in the A.I. field believes, the real question is about values : how we instill them in machines, and how we then negotiate with those machines if and when their values are likely to differ greatly from our own. As the Oxford philosopher Nick Bostrom argued :

We cannot blithely assume that a superintelligence will necessarily share any of the final values stereotypically associated with wisdom and intellectual development in humans—scientific curiosity, benevolent concern for others, spiritual enlightenment and contemplation, renunciation of material acquisitiveness, a taste for refined culture or for the simple pleasures in life, humility and selflessness, and so forth. It might be possible through deliberate effort to construct a superintelligence that values such things, or to build one that values human welfare, moral goodness, or any other complex purpose that its designers might want it to serve. But it is no less possible—and probably technically easier—to build a superintelligence that places final value on nothing but calculating the decimals of pi.

The British cyberneticist Kevin Warwick once asked, “How can you reason, how can you bargain, how can you understand how that machine is thinking when it’s thinking in dimensions you can’t conceive of?”

If there is a hole in Barrat’s dark argument, it is in his glib presumption that if a robot is smart enough to play chess, it might also “want to build a spaceship”—and that tendencies toward self-preservation and resource acquisition are inherent in any sufficiently complex, goal-driven system. For now, most of the machines that are good enough to play chess, like I.B.M.’s Deep Blue, haven’t shown the slightest interest in acquiring resources.

But before we get complacent and decide there is nothing to worry about after all, it is important to realize that the goals of machines could change as they get smarter. Once computers can effectively reprogram themselves, and successively improve themselves, leading to a so-called “ technological singularity ” or “intelligence explosion,” the risks of machines outwitting humans in battles for resources and self-preservation cannot simply be dismissed.

One of the most pointed quotes in Barrat’s book belongs to the legendary serial A.I. entrepreneur Danny Hillis, who likens the upcoming shift to one of the greatest transitions in the history of biological evolution: “We’re at that point analogous to when single-celled organisms were turning into multi-celled organisms. We are amoeba and we can’t figure out what the hell this thing is that we’re creating.”

Already, advances in A.I. have created risks that we never dreamt of. With the advent of the Internet age and its Big Data explosion, “large amounts of data is being collected about us and then being fed to algorithms to make predictions,” Vaibhav Garg , a computer-risk specialist at Drexel University, told me. “We do not have the ability to know when the data is being collected, ensure that the data collected is correct, update the information, or provide the necessary context.” Few people would have even dreamt of this risk even twenty years ago. What risks lie ahead? Nobody really knows, but Barrat is right to ask.

Photograph by John Vink/Magnum.

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By Richard Brody

By Katy Waldman

By Justin Chang

Major new report explains the risks and rewards of artificial intelligence

AI has begun to permeate every aspect of our lives. Image:  Unsplash/Hitesh Choudhary

.chakra .wef-1c7l3mo{-webkit-transition:all 0.15s ease-out;transition:all 0.15s ease-out;cursor:pointer;-webkit-text-decoration:none;text-decoration:none;outline:none;color:inherit;}.chakra .wef-1c7l3mo:hover,.chakra .wef-1c7l3mo[data-hover]{-webkit-text-decoration:underline;text-decoration:underline;}.chakra .wef-1c7l3mo:focus,.chakra .wef-1c7l3mo[data-focus]{box-shadow:0 0 0 3px rgba(168,203,251,0.5);} Toby Walsh

Liz sonenberg.

.chakra .wef-9dduvl{margin-top:16px;margin-bottom:16px;line-height:1.388;font-size:1.25rem;}@media screen and (min-width:56.5rem){.chakra .wef-9dduvl{font-size:1.125rem;}} Explore and monitor how .chakra .wef-15eoq1r{margin-top:16px;margin-bottom:16px;line-height:1.388;font-size:1.25rem;color:#F7DB5E;}@media screen and (min-width:56.5rem){.chakra .wef-15eoq1r{font-size:1.125rem;}} Artificial Intelligence is affecting economies, industries and global issues

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Stay up to date:, emerging technologies.

• A new report has just been released, highlighting the changes in AI over the last 5 years, and predicted future trends.
• It was co-written by people across the world, with backgrounds in computer science, engineering, law, political science, policy, sociology and economics.
• In the last 5 years, AI has become an increasing part of our lives, revolutionizing a number of industries, but is still not free from risk.

A major new report on the state of artificial intelligence (AI) has just been released . Think of it as the AI equivalent of an Intergovernmental Panel on Climate Change report, in that it identifies where AI is at today, and the promise and perils in view.

From language generation and molecular medicine to disinformation and algorithmic bias, AI has begun to permeate every aspect of our lives.

The report argues that we are at an inflection point where researchers and governments must think and act carefully to contain the risks AI presents and make the most of its benefits.

A century-long study of AI

The report comes out of the AI100 project , which aims to study and anticipate the effects of AI rippling out through our lives over the course of the next 100 years.

AI100 produces a new report every five years: the first was published in 2016, and this is the second. As two points define a line, this second report lets us see the direction AI is taking us in.

One of us (Liz Sonenberg) is a member of the standing committee overseeing the AI100 project, and the other (Toby Walsh) was on the study panel that wrote this particular report. Members of the panel came from across the world, with backgrounds in computer science, engineering, law, political science, policy, sociology and economics.

The promises and perils of AI are becoming real

The report highlights the remarkable progress made in AI over the past five years. AI is leaving the laboratory and has entered our lives, having a “real-world impact on people, institutions, and culture”. Read the news on any given day and you’re likely to find multiple stories about some new advance in AI or some new use of AI.

For example, in natural language processing (NLP), computers can now analyse and even generate realistic human language. To demonstrate, we asked Open AI’s GPT-3 system , one of the largest neural networks ever built, to summarise the AI100 report for you. It did a pretty good job, even if the summary confronts our sense of self by being written in the first person:

In the coming decade, I expect that AI will play an increasingly prominent role in the lives of people everywhere. AI-infused services will become more common, and AI will become increasingly embedded in the daily lives of people across the world.

I believe that this will bring with it great economic and societal benefits, but that it will also require us to address the many challenges to ensure that the benefits are broadly shared and that people are not marginalised by these new technologies.

A key insight of AI research is that it is easier to build things than to understand why they work. However, defining what success looks like for an AI application is not straightforward.

For example, the AI systems that are used in healthcare to analyse symptoms, recommend diagnoses, or choose treatments are often far better than anything that could be built by a human, but their success is hard to quantify.

As a second example of the recent and remarkable progress in AI, consider the latest breakthrough from Google’s DeepMind. AlphaFold is an AI program that provides a huge step forward in our ability to predict how proteins fold.

This will likely lead to major advances in life sciences and medicine, accelerating efforts to understand the building blocks of life and enabling quicker and more sophisticated drug discovery. Most of the planet now knows to their cost how the unique shape of the spike proteins in the SARS-CoV-2 virus are key to its ability to invade our cells, and also to the vaccines developed to combat its deadly progress.

The AI100 report argues that worries about super-intelligent machines and wide-scale job loss from automation are still premature, requiring AI that is far more capable than available today. The main concern the report raises is not malevolent machines of superior intelligence to humans, but incompetent machines of inferior intelligence.

Once again, it’s easy to find in the news real-life stories of risks and threats to our democratic discourse and mental health posed by AI-powered tools. For instance, Facebook uses machine learning to sort its news feed and give each of its 2 billion users an unique but often inflammatory view of the world.

The World Economic Forum was the first to draw the world’s attention to the Fourth Industrial Revolution, the current period of unprecedented change driven by rapid technological advances. Policies, norms and regulations have not been able to keep up with the pace of innovation, creating a growing need to fill this gap.

The Forum established the Centre for the Fourth Industrial Revolution Network in 2017 to ensure that new and emerging technologies will help—not harm—humanity in the future. Headquartered in San Francisco, the network launched centres in China, India and Japan in 2018 and is rapidly establishing locally-run Affiliate Centres in many countries around the world.

The global network is working closely with partners from government, business, academia and civil society to co-design and pilot agile frameworks for governing new and emerging technologies, including artificial intelligence (AI) , autonomous vehicles , blockchain , data policy , digital trade , drones , internet of things (IoT) , precision medicine and environmental innovations .

Learn more about the groundbreaking work that the Centre for the Fourth Industrial Revolution Network is doing to prepare us for the future.

Want to help us shape the Fourth Industrial Revolution? Contact us to find out how you can become a member or partner.

The time to act is now

It’s clear we’re at an inflection point: we need to think seriously and urgently about the downsides and risks the increasing application of AI is revealing. The ever-improving capabilities of AI are a double-edged sword. Harms may be intentional, like deepfake videos, or unintended, like algorithms that reinforce racial and other biases.

AI research has traditionally been undertaken by computer and cognitive scientists. But the challenges being raised by AI today are not just technical. All areas of human inquiry, and especially the social sciences, need to be included in a broad conversation about the future of the field. Minimising negative impacts on society and enhancing the positives requires consideration from across academia and with societal input.

Governments also have a crucial role to play in shaping the development and application of AI. Indeed, governments around the world have begun to consider and address the opportunities and challenges posed by AI. But they remain behind the curve.

A greater investment of time and resources is needed to meet the challenges posed by the rapidly evolving technologies of AI and associated fields. In addition to regulation, governments also need to educate. In an AI-enabled world, our citizens, from the youngest to the oldest, need to be literate in these new digital technologies.

At the end of the day, the success of AI research will be measured by how it has empowered all people, helping tackle the many wicked problems facing the planet, from the climate emergency to increasing inequality within and between countries.

AI will have failed if it harms or devalues the very people we are trying to help.

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World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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MIT Technology Review

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The true dangers of AI are closer than we think

Forget superintelligent AI: algorithms are already creating real harm. The good news: the fight back has begun.

• Karen Hao archive page

As long as humans have built machines, we’ve feared the day they could destroy us. Stephen Hawking famously warned that AI could spell an end to civilization. But to many AI researchers, these conversations feel unmoored. It’s not that they don’t fear AI running amok—it’s that they see it already happening, just not in the ways most people would expect. 

AI is now screening job candidates, diagnosing disease, and identifying criminal suspects. But instead of making these decisions more efficient or fair, it’s often perpetuating the biases of the humans on whose decisions it was trained. 

William Isaac is a senior research scientist on the ethics and society team at DeepMind, an AI startup that Google acquired in 2014. He also co-chairs the Fairness, Accountability, and Transparency conference—the premier annual gathering of AI experts, social scientists, and lawyers working in this area. I asked him about the current and potential challenges facing AI development—as well as the solutions.

Q: Should we be worried about superintelligent AI?

A: I want to shift the question. The threats overlap, whether it’s predictive policing and risk assessment in the near term, or more scaled and advanced systems in the longer term. Many of these issues also have a basis in history. So potential risks and ways to approach them are not as abstract as we think.

There are three areas that I want to flag. Probably the most pressing one is this question about value alignment: how do you actually design a system that can understand and implement the various forms of preferences and values of a population? In the past few years we’ve seen attempts by policymakers, industry, and others to try to embed values into technical systems at scale—in areas like predictive policing, risk assessments, hiring, etc. It’s clear that they exhibit some form of bias that reflects society. The ideal system would balance out all the needs of many stakeholders and many people in the population. But how does society reconcile their own history with aspiration? We’re still struggling with the answers, and that question is going to get exponentially more complicated. Getting that problem right is not just something for the future, but for the here and now.

The second one would be achieving demonstrable social benefit. Up to this point there are still few pieces of empirical evidence that validate that AI technologies will achieve the broad-based social benefit that we aspire to. 

Lastly, I think the biggest one that anyone who works in the space is concerned about is: what are the robust mechanisms of oversight and accountability. 

Q: How do we overcome these risks and challenges?

A: Three areas would go a long way. The first is to build a collective muscle for responsible innovation and oversight. Make sure you’re thinking about where the forms of misalignment or bias or harm exist. Make sure you develop good processes for how you ensure that all groups are engaged in the process of technological design. Groups that have been historically marginalized are often not the ones that get their needs met. So how we design processes to actually do that is important.

The second one is accelerating the development of the sociotechnical tools to actually do this work. We don’t have a whole lot of tools. 

The last one is providing more funding and training for researchers and practitioners—particularly researchers and practitioners of color—to conduct this work. Not just in machine learning, but also in STS [science, technology, and society] and the social sciences. We want to not just have a few individuals but a community of researchers to really understand the range of potential harms that AI systems pose, and how to successfully mitigate them.

Q: How far have AI researchers come in thinking about these challenges, and how far do they still have to go?

A: In 2016, I remember, the White House had just come out with a big data report, and there was a strong sense of optimism that we could use data and machine learning to solve some intractable social problems. Simultaneously, there were researchers in the academic community who had been flagging in a very abstract sense: “Hey, there are some potential harms that could be done through these systems.” But they largely had not interacted at all. They existed in unique silos.

Since then, we’ve just had a lot more research targeting this intersection between known flaws within machine-learning systems and their application to society. And once people began to see that interplay, they realized: “Okay, this is not just a hypothetical risk. It is a real threat.” So if you view the field in phases, phase one was very much highlighting and surfacing that these concerns are real. The second phase now is beginning to grapple with broader systemic questions.

Q: So are you optimistic about achieving broad-based beneficial AI?

A: I am. The past few years have given me a lot of hope. Look at facial recognition as an example. There was the great work by Joy Buolamwini, Timnit Gebru, and Deb Raji in surfacing intersectional disparities in accuracies across facial recognition systems [i.e., showing these systems were far less accurate on Black female faces than white male ones]. There’s the advocacy that happened in civil society to mount a rigorous defense of human rights against misapplication of facial recognition. And also the great work that policymakers, regulators, and community groups from the grassroots up were doing to communicate exactly what facial recognition systems were and what potential risks they posed, and to demand clarity on what the benefits to society would be. That’s a model of how we could imagine engaging with other advances in AI.

But the challenge with facial recognition is we had to adjudicate these ethical and values questions while we were publicly deploying the technology. In the future, I hope that some of these conversations happen before the potential harms emerge.

Q: What do you dream about when you dream about the future of AI?

A: It could be a great equalizer. Like if you had AI teachers or tutors that could be available to students and communities where access to education and resources is very limited, that’d be very empowering. And that’s a nontrivial thing to want from this technology. How do you know it’s empowering? How do you know it’s socially beneficial? 

I went to graduate school in Michigan during the Flint water crisis. When the initial incidences of lead pipes emerged, the records they had for where the piping systems were located were on index cards at the bottom of an administrative building. The lack of access to technologies had put them at a significant disadvantage. It means the people who grew up in those communities, over 50% of whom are African-American, grew up in an environment where they don’t get basic services and resources.

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Open AI’s CEO says we won’t need new hardware or lots more training data to get there.

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May 17, 2024

UC Berkeley's only nonpartisan political magazine

Artificial Intelligence and the Loss of Humanity

The term “artificial intelligence,” or AI, has become a buzzword in recent years. Optimists see AI as the panacea to society’s most fundamental problems, from crime to corruption to inequality, while pessimists fear that AI will overtake human intelligence and crown itself king of the world. Underlying these two seemingly antithetical views is the assumption that AI is better and smarter than humanity and will ultimately replace humanity in making decisions.

It is easy to buy into the hype of omnipotent artificial intelligence these days, as venture capitalists dump billions of dollars into tech start-ups and government technocrats boast of how AI helps them streamline municipal governance . But the hype is just hype: AI is simply not as smart as we think. The true threat of AI to humanity lies not in the power of AI itself but in the ways people are already beginning to use it to chip away at our humanity.

AI outperforms humans, but only in low-level tasks.

Artificial intelligence is a field in computer science that seeks to have computers perform certain tasks by simulating human intelligence. Although the founding fathers of AI in the 1950s and 1960s experimented with manually codifying knowledge into computer systems, most of today’s AI application is carried out via a statistical approach through machine learning, thanks to the proliferation of big data and computational power in recent years. However, today’s AI is still limited to the performance of specialized tasks, such as classifying images, recognizing patterns and generating sentences.

Although a specialized AI might outperform humans in its specific function, it does not understand the logic and principles of its actions. An AI that classifies images, for example, might label images of cats and dogs more accurately than a human, but it never knows how a cat is similar to and different from a dog. Similarly, a natural language processing (NLP) AI can train a model that projects English words onto vectors, but it does not comprehend the etymology and context of each individual word. AI performs tasks mechanically without understanding the content of the tasks, which means that it is certainly not able to outsmart its human masters in a dystopian manner and will not reach such a level for a long time, if ever.

AI does not dehumanize humans — humans do.

AI does not understand humanity, but the epistemological wall between AI and humanity is further complicated by the fact that humans do not understand AI, either. A typical AI model easily contains hundreds of thousands of parameters, whose weights are fine-tuned according to some mathematical principles in order to minimize “loss,” a rough estimate of how wrong the model is. The design of the loss function and its minimization process are often more art than science. We do not know what the weights in the model mean or how the model predicts one result rather than another. Without an explainable framework, decision-making driven by AI is a black box , unaccountable and even inhumane.

This is more than just a theoretical concern. This year in China, local authorities rolled out the so-called “health code,” a QR code assigned to each individual using an AI-powered risk assessment algorithm indicating their risk of contracting and spreading COVID-19. There have been numerous pieces of news coverage about citizens who found their health codes suddenly turning from green (low-risk) to red (high risk) for no reason. They became “digital refugees” as they were immediately banned from entering public venues, including grocery stores, which require green codes. Nobody knows how the risk assessment algorithm works under the hood, yet, in this trying time of coronavirus, it is determining people’s day-to-day lives.

AI applications can intervene in human agency.

Artificial intelligence is also transforming the medical industry. Predictive algorithms are now powering brain-computer interfaces (BCIs) that can read signals from the brain and even write in signals if necessary. For example, a BCI can identify a seizure and act to suppress the symptom, a potentially life-saving application of AI. But BCIs also create problems concerning agency. Who is controlling one’s brain — the user or the machine?

One need not plug their brain into some electronic device to face this issue of agency. The newsfeed of our social medias is constantly using artificial intelligence to push us content based on patterns from our views, likes, moves of the mouse and number of seconds we spend scrolling through a page. We are passive consumers in a deluge of information tailored to our tastes, no longer having to actively reach out to find information — because that information finds us.

AI knows nothing about culture and values.

Feeding an AI system requires data, the representation of information. Some information, such as gender, age and temperature, can be easily coded and quantified. However, there is no way to uniformly quantify complex emotions, beliefs, cultures, norms and values. Because AI systems cannot process these concepts, the best they can do is to seek to maximize benefits and minimize losses for people according to mathematical principles. This utilitarian logic, though, often contravenes what we would consider noble from a moral standpoint — prioritizing the weak over the strong, safeguarding the rights of the minority despite giving up greater overall welfare and seeking truth and justice rather than telling lies.

The fact that AI does not understand culture or values does not imply that AI is value-neutral. Rather, any AI designed by humans is implicitly value-laden. It is consciously or unconsciously imbued with the belief system of its designer. Biases in AI can come from the representativeness of the historical data, the ways in which data scientists clean and interpret the data, which categorizing buckets the model is designed to output, the choice of loss function and other design features. A more aggressive company culture, for example, might favor maximizing recall in AI, or the proportion of positives identified as positive, while a more prudent culture would encourage maximizing precision, the proportion of labelled positives that are actually positive. While such a distinction might seem trivial, in a medical setting, it can become an issue of life and death: do we try to distribute as much of a treatment as possible despite its side effects, or do we act more prudently to limit the distribution of the treatment to minimize side effects, even if many people will never get the treatment? Within a single AI model, these two goals can never be achieved simultaneously because they are mathematically opposed to each other. People have to make a choice when designing an AI system, and the choice they make will inevitably reflect the values of the designers. 

Take responsibility, now.

AI may or may not outsmart human beings one day — we simply do not know. What we do know is that AI is already changing power dynamics and interpersonal relations today. Government institutions and corporations run the risk of treating atomized individuals as miniscule data points to be aggregated and tapped by AI programs, devoid of personal idiosyncrasies, specialized needs, or unconditional moral worth. This dehumanization is further amplified by the winner-takes-all logic of AI platform economies that creates mighty monopolies, resulting in a situation in which even the smallest decisions made by these companies have the power to erode human agency and autonomy. In order to mitigate the side effects of AI applications, academia, civil society, regulators and corporations must join forces in ensuring that human-centric AI will empower humanity and make our world a better place.

Featured image source: Odyssey

Published in Multimedia

• artifical intelligence
• Artificial Intelligence
• machine learning

Xiantao studies Sociology and Data Science at UC Berkeley. He writes on Hong Kong, U.S.-China relations, and technology.

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Artificial intelligence: threats and opportunities

Artificial intelligence (AI) affects our lives more and more. Learn about the opportunities and threats for security, democracy, businesses and jobs.

Europe's growth and wealth are closely connected to how it will make use of data and connected technologies. AI can make a big difference to our lives – for better or worse . In June 2023, The European Parliament adopted its negotiating position on the AI Act – the world’s first set of comprehensive rules to manage AI risks.Below are some key opportunities and threats connected to future applications of AI.

Read more about what artificial intelligence is and how it is used

175 zettabytes

The volume of data produced in the world is expected to grow from 33 zettabytes in 2018 to 175 zettabytes in 2025 (one zettabyte is a thousand billion gigabytes)

Advantages of AI

EU countries are already strong in digital industry and business-to-business applications. With a high-quality digital infrastructure and a regulatory framework that protects privacy and freedom of speech, the EU could become a global leader in the data economy and its applications .

Benefits of AI for people

AI could help people   with improved health care, safer cars and other transport systems, tailored, cheaper and longer-lasting products and services. It can also facilitate access to information, education and training.  The need for distance learning became more important because of the Covid-19 pandemic . AI can also make workplace safer as robots can be used for dangerous parts of jobs, and open new job positions as AI-driven industries grow and change.

Opportunities of artificial intelligence for businesses

For businesses , AI can enable the development of a new generation of products and services, including in sectors where European companies already have strong positions: green and circular economy, machinery, farming, healthcare, fashion, tourism. It can boost sales, improve machine maintenance, increase production output and quality, improve customer service, as well as save energy.

Estimated increase of labour productivity related to AI by 2035 (Parliament's Think Tank 2020)

AI opportunities in public services

AI used in public services can reduce costs and offer new possibilities in public transport, education, energy and waste management and could also improve the sustainability of products. In this way AI could contribute to achieving the goals of the EU Green Deal .

Estimate of how much AI could help reduce global greenhouse emissions by 2030 (Parliament's Think Tank 2020)

Strengthening democracy

Democracy could be made stronger by using data-based scrutiny, preventing disinformation and cyber attacks and ensuring access to quality information . AI could also support diversity and openness, for example by mitigating the possibility of prejudice in hiring decisions and using analytical data instead.

AI, security and safety

AI is predicted to be used more in crime prevention and the criminal justice system , as massive data sets could be processed faster, prisoner flight risks assessed more accurately, crime or even terrorist attacks predicted and prevented. It is already used by online platforms to detect and react to unlawful and inappropriate online behaviour.

In military matters , AI could be used for defence and attack strategies in hacking and phishing or to target key systems in cyberwarfare.

Threats and challenges of AI

The increasing reliance on AI systems also poses potential risks.

Underuse and overuse of AI

Underuse of AI is considered as a major threat: missed opportunities for the EU could mean poor implementation of major programmes, such as the EU Green Deal, losing competitive advantage towards other parts of the world, economic stagnation and poorer possibilities for people. Underuse could derive from public and business' mistrust in AI, poor infrastructure, lack of initiative, low investments, or, since AI's machine learning is dependent on data, from fragmented digital markets.

Overuse can also be problematic: investing in AI applications that prove not to be useful or applying AI to tasks for which it is not suited, for example using it to explain complex societal issues.

Liability: who is responsible for damage caused by AI?

An important challenge is to determine who is responsible for damage caused by an AI-operated device or service: in an accident involving a self-driving car. Should the damage be covered by the owner, the car manufacturer or the programmer?

If the producer was absolutely free of accountability, there might be no incentive to provide good product or service and it could damage people’s trust in the technology; but regulations could also be too strict and stifle innovation.

Threats of AI to fundamental rights and democracy

The results that AI produces depend on how it is designed and what data it uses. Both design and data can be intentionally or unintentionally biased. For example, some important aspects of an issue might not be programmed into the algorithm or might be programmed to reflect and replicate structural biases. In adcition, the use of numbers to represent complex social reality could make the AI seem factual and precise when it isn’t . This is sometimes referred to as mathwashing.

If not done properly, AI could lead to decisions influenced by data on  ethnicity, sex, age when hiring or firing, offering loans, or even in criminal proceedings.

AI could severely affect the right to privacy and data protection. It can be for example used in face recognition equipment or for online tracking and profiling of individuals. In addition, AI enables merging pieces of information a person has given into new data, which can lead to results the person would not expect.

It can also present a threat to democracy; AI has already been blamed for creating online echo chambers based on a person's previous online behaviour, displaying only content a person would like, instead of creating an environment for pluralistic, equally accessible and inclusive public debate. It can even be used to create extremely realistic fake video, audio and images, known as deepfakes, which can present financial risks, harm reputation, and challenge decision making. All of this could lead to separation and polarisation in the public sphere and manipulate elections.

AI could also play a role in harming freedom of assembly and protest as it could track and profile individuals linked to certain beliefs or actions.

AI impact on jobs

Use of AI in the workplace is expected to result in the elimination of a large number of jobs. Though AI is also expected to create and make better jobs, education and training will have a crucial role in preventing long-term unemployment and ensure a skilled workforce.

of jobs in OECD countries are highly automatable and another 32% could face substantial changes (estimate by Parliament's Think Tank 2020).

Competition

Amassing information could also lead to distortion of competition as  companies with more information could gain an advantage and effectively eliminate competitors.

Safety and security risks

AI applications that are in physical contact with humans or integrated into the human body could pose safety risks as they may be poorly designed, misused or hacked. Poorly regulated use of AI in weapons could lead to loss of human control over dangerous weapons.

Transparency challenges

Imbalances of access to information could be exploited. For example, based on a person's online behaviour or other data and without their knowledge, an online vendor can use AI to predict someone is willing to pay, or a political campaign can adapt their message. Another transparency issue is that sometimes it can be unclear to people whether they are interacting with AI or a person.

Read more about how MEPs want to shape data legislation to boost innovation and ensure safety

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• Parliament's Think Tank
• Artificial intelligence: how does it work, why does it matter and what can we do about it?
• Opportunities of artificial intelligence
• Artificial intelligence: legal and ethical reflections

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The impact of artificial intelligence on human society and bioethics

Michael cheng-tek tai.

Department of Medical Sociology and Social Work, College of Medicine, Chung Shan Medical University, Taichung, Taiwan

Artificial intelligence (AI), known by some as the industrial revolution (IR) 4.0, is going to change not only the way we do things, how we relate to others, but also what we know about ourselves. This article will first examine what AI is, discuss its impact on industrial, social, and economic changes on humankind in the 21 st century, and then propose a set of principles for AI bioethics. The IR1.0, the IR of the 18 th century, impelled a huge social change without directly complicating human relationships. Modern AI, however, has a tremendous impact on how we do things and also the ways we relate to one another. Facing this challenge, new principles of AI bioethics must be considered and developed to provide guidelines for the AI technology to observe so that the world will be benefited by the progress of this new intelligence.

W HAT IS ARTIFICIAL INTELLIGENCE ?

Artificial intelligence (AI) has many different definitions; some see it as the created technology that allows computers and machines to function intelligently. Some see it as the machine that replaces human labor to work for men a more effective and speedier result. Others see it as “a system” with the ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation [ 1 ].

Despite the different definitions, the common understanding of AI is that it is associated with machines and computers to help humankind solve problems and facilitate working processes. In short, it is an intelligence designed by humans and demonstrated by machines. The term AI is used to describe these functions of human-made tool that emulates the “cognitive” abilities of the natural intelligence of human minds [ 2 ].

Along with the rapid development of cybernetic technology in recent years, AI has been seen almost in all our life circles, and some of that may no longer be regarded as AI because it is so common in daily life that we are much used to it such as optical character recognition or the Siri (speech interpretation and recognition interface) of information searching equipment on computer [ 3 ].

D IFFERENT TYPES OF ARTIFICIAL INTELLIGENCE

From the functions and abilities provided by AI, we can distinguish two different types. The first is weak AI, also known as narrow AI that is designed to perform a narrow task, such as facial recognition or Internet Siri search or self-driving car. Many currently existing systems that claim to use “AI” are likely operating as a weak AI focusing on a narrowly defined specific function. Although this weak AI seems to be helpful to human living, there are still some think weak AI could be dangerous because weak AI could cause disruptions in the electric grid or may damage nuclear power plants when malfunctioned.

The new development of the long-term goal of many researchers is to create strong AI or artificial general intelligence (AGI) which is the speculative intelligence of a machine that has the capacity to understand or learn any intelligent task human being can, thus assisting human to unravel the confronted problem. While narrow AI may outperform humans such as playing chess or solving equations, but its effect is still weak. AGI, however, could outperform humans at nearly every cognitive task.

Strong AI is a different perception of AI that it can be programmed to actually be a human mind, to be intelligent in whatever it is commanded to attempt, even to have perception, beliefs and other cognitive capacities that are normally only ascribed to humans [ 4 ].

In summary, we can see these different functions of AI [ 5 , 6 ]:

• Automation: What makes a system or process to function automatically
• Machine learning and vision: The science of getting a computer to act through deep learning to predict and analyze, and to see through a camera, analog-to-digital conversion and digital signal processing
• Natural language processing: The processing of human language by a computer program, such as spam detection and converting instantly a language to another to help humans communicate
• Robotics: A field of engineering focusing on the design and manufacturing of cyborgs, the so-called machine man. They are used to perform tasks for human's convenience or something too difficult or dangerous for human to perform and can operate without stopping such as in assembly lines
• Self-driving car: Use a combination of computer vision, image recognition amid deep learning to build automated control in a vehicle.

D O HUMAN-BEINGS REALLY NEED ARTIFICIAL INTELLIGENCE ?

Is AI really needed in human society? It depends. If human opts for a faster and effective way to complete their work and to work constantly without taking a break, yes, it is. However if humankind is satisfied with a natural way of living without excessive desires to conquer the order of nature, it is not. History tells us that human is always looking for something faster, easier, more effective, and convenient to finish the task they work on; therefore, the pressure for further development motivates humankind to look for a new and better way of doing things. Humankind as the homo-sapiens discovered that tools could facilitate many hardships for daily livings and through tools they invented, human could complete the work better, faster, smarter and more effectively. The invention to create new things becomes the incentive of human progress. We enjoy a much easier and more leisurely life today all because of the contribution of technology. The human society has been using the tools since the beginning of civilization, and human progress depends on it. The human kind living in the 21 st century did not have to work as hard as their forefathers in previous times because they have new machines to work for them. It is all good and should be all right for these AI but a warning came in early 20 th century as the human-technology kept developing that Aldous Huxley warned in his book Brave New World that human might step into a world in which we are creating a monster or a super human with the development of genetic technology.

Besides, up-to-dated AI is breaking into healthcare industry too by assisting doctors to diagnose, finding the sources of diseases, suggesting various ways of treatment performing surgery and also predicting if the illness is life-threatening [ 7 ]. A recent study by surgeons at the Children's National Medical Center in Washington successfully demonstrated surgery with an autonomous robot. The team supervised the robot to perform soft-tissue surgery, stitch together a pig's bowel, and the robot finished the job better than a human surgeon, the team claimed [ 8 , 9 ]. It demonstrates robotically-assisted surgery can overcome the limitations of pre-existing minimally-invasive surgical procedures and to enhance the capacities of surgeons performing open surgery.

Above all, we see the high-profile examples of AI including autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art, playing games (such as Chess or Go), search engines (such as Google search), online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delays…etc. All these have made human life much easier and convenient that we are so used to them and take them for granted. AI has become indispensable, although it is not absolutely needed without it our world will be in chaos in many ways today.

T HE IMPACT OF ARTIFICIAL INTELLIGENCE ON HUMAN SOCIETY

Negative impact.

Questions have been asked: With the progressive development of AI, human labor will no longer be needed as everything can be done mechanically. Will humans become lazier and eventually degrade to the stage that we return to our primitive form of being? The process of evolution takes eons to develop, so we will not notice the backsliding of humankind. However how about if the AI becomes so powerful that it can program itself to be in charge and disobey the order given by its master, the humankind?

Let us see the negative impact the AI will have on human society [ 10 , 11 ]:

• A huge social change that disrupts the way we live in the human community will occur. Humankind has to be industrious to make their living, but with the service of AI, we can just program the machine to do a thing for us without even lifting a tool. Human closeness will be gradually diminishing as AI will replace the need for people to meet face to face for idea exchange. AI will stand in between people as the personal gathering will no longer be needed for communication
• Unemployment is the next because many works will be replaced by machinery. Today, many automobile assembly lines have been filled with machineries and robots, forcing traditional workers to lose their jobs. Even in supermarket, the store clerks will not be needed anymore as the digital device can take over human labor
• Wealth inequality will be created as the investors of AI will take up the major share of the earnings. The gap between the rich and the poor will be widened. The so-called “M” shape wealth distribution will be more obvious
• New issues surface not only in a social sense but also in AI itself as the AI being trained and learned how to operate the given task can eventually take off to the stage that human has no control, thus creating un-anticipated problems and consequences. It refers to AI's capacity after being loaded with all needed algorithm may automatically function on its own course ignoring the command given by the human controller
• The human masters who create AI may invent something that is racial bias or egocentrically oriented to harm certain people or things. For instance, the United Nations has voted to limit the spread of nucleus power in fear of its indiscriminative use to destroying humankind or targeting on certain races or region to achieve the goal of domination. AI is possible to target certain race or some programmed objects to accomplish the command of destruction by the programmers, thus creating world disaster.

P OSITIVE IMPACT

There are, however, many positive impacts on humans as well, especially in the field of healthcare. AI gives computers the capacity to learn, reason, and apply logic. Scientists, medical researchers, clinicians, mathematicians, and engineers, when working together, can design an AI that is aimed at medical diagnosis and treatments, thus offering reliable and safe systems of health-care delivery. As health professors and medical researchers endeavor to find new and efficient ways of treating diseases, not only the digital computer can assist in analyzing, robotic systems can also be created to do some delicate medical procedures with precision. Here, we see the contribution of AI to health care [ 7 , 11 ]:

Fast and accurate diagnostics

IBM's Watson computer has been used to diagnose with the fascinating result. Loading the data to the computer will instantly get AI's diagnosis. AI can also provide various ways of treatment for physicians to consider. The procedure is something like this: To load the digital results of physical examination to the computer that will consider all possibilities and automatically diagnose whether or not the patient suffers from some deficiencies and illness and even suggest various kinds of available treatment.

Socially therapeutic robots

Pets are recommended to senior citizens to ease their tension and reduce blood pressure, anxiety, loneliness, and increase social interaction. Now cyborgs have been suggested to accompany those lonely old folks, even to help do some house chores. Therapeutic robots and the socially assistive robot technology help improve the quality of life for seniors and physically challenged [ 12 ].

Reduce errors related to human fatigue

Human error at workforce is inevitable and often costly, the greater the level of fatigue, the higher the risk of errors occurring. Al technology, however, does not suffer from fatigue or emotional distraction. It saves errors and can accomplish the duty faster and more accurately.

Artificial intelligence-based surgical contribution

AI-based surgical procedures have been available for people to choose. Although this AI still needs to be operated by the health professionals, it can complete the work with less damage to the body. The da Vinci surgical system, a robotic technology allowing surgeons to perform minimally invasive procedures, is available in most of the hospitals now. These systems enable a degree of precision and accuracy far greater than the procedures done manually. The less invasive the surgery, the less trauma it will occur and less blood loss, less anxiety of the patients.

Improved radiology

The first computed tomography scanners were introduced in 1971. The first magnetic resonance imaging (MRI) scan of the human body took place in 1977. By the early 2000s, cardiac MRI, body MRI, and fetal imaging, became routine. The search continues for new algorithms to detect specific diseases as well as to analyze the results of scans [ 9 ]. All those are the contribution of the technology of AI.

Virtual presence

The virtual presence technology can enable a distant diagnosis of the diseases. The patient does not have to leave his/her bed but using a remote presence robot, doctors can check the patients without actually being there. Health professionals can move around and interact almost as effectively as if they were present. This allows specialists to assist patients who are unable to travel.

S OME CAUTIONS TO BE REMINDED

Despite all the positive promises that AI provides, human experts, however, are still essential and necessary to design, program, and operate the AI from any unpredictable error from occurring. Beth Kindig, a San Francisco-based technology analyst with more than a decade of experience in analyzing private and public technology companies, published a free newsletter indicating that although AI has a potential promise for better medical diagnosis, human experts are still needed to avoid the misclassification of unknown diseases because AI is not omnipotent to solve all problems for human kinds. There are times when AI meets an impasse, and to carry on its mission, it may just proceed indiscriminately, ending in creating more problems. Thus vigilant watch of AI's function cannot be neglected. This reminder is known as physician-in-the-loop [ 13 ].

The question of an ethical AI consequently was brought up by Elizabeth Gibney in her article published in Nature to caution any bias and possible societal harm [ 14 ]. The Neural Information processing Systems (NeurIPS) conference in Vancouver Canada in 2020 brought up the ethical controversies of the application of AI technology, such as in predictive policing or facial recognition, that due to bias algorithms can result in hurting the vulnerable population [ 14 ]. For instance, the NeurIPS can be programmed to target certain race or decree as the probable suspect of crime or trouble makers.

T HE CHALLENGE OF ARTIFICIAL INTELLIGENCE TO BIOETHICS

Artificial intelligence ethics must be developed.

Bioethics is a discipline that focuses on the relationship among living beings. Bioethics accentuates the good and the right in biospheres and can be categorized into at least three areas, the bioethics in health settings that is the relationship between physicians and patients, the bioethics in social settings that is the relationship among humankind and the bioethics in environmental settings that is the relationship between man and nature including animal ethics, land ethics, ecological ethics…etc. All these are concerned about relationships within and among natural existences.

As AI arises, human has a new challenge in terms of establishing a relationship toward something that is not natural in its own right. Bioethics normally discusses the relationship within natural existences, either humankind or his environment, that are parts of natural phenomena. But now men have to deal with something that is human-made, artificial and unnatural, namely AI. Human has created many things yet never has human had to think of how to ethically relate to his own creation. AI by itself is without feeling or personality. AI engineers have realized the importance of giving the AI ability to discern so that it will avoid any deviated activities causing unintended harm. From this perspective, we understand that AI can have a negative impact on humans and society; thus, a bioethics of AI becomes important to make sure that AI will not take off on its own by deviating from its originally designated purpose.

Stephen Hawking warned early in 2014 that the development of full AI could spell the end of the human race. He said that once humans develop AI, it may take off on its own and redesign itself at an ever-increasing rate [ 15 ]. Humans, who are limited by slow biological evolution, could not compete and would be superseded. In his book Superintelligence, Nick Bostrom gives an argument that AI will pose a threat to humankind. He argues that sufficiently intelligent AI can exhibit convergent behavior such as acquiring resources or protecting itself from being shut down, and it might harm humanity [ 16 ].

The question is–do we have to think of bioethics for the human's own created product that bears no bio-vitality? Can a machine have a mind, consciousness, and mental state in exactly the same sense that human beings do? Can a machine be sentient and thus deserve certain rights? Can a machine intentionally cause harm? Regulations must be contemplated as a bioethical mandate for AI production.

Studies have shown that AI can reflect the very prejudices humans have tried to overcome. As AI becomes “truly ubiquitous,” it has a tremendous potential to positively impact all manner of life, from industry to employment to health care and even security. Addressing the risks associated with the technology, Janosch Delcker, Politico Europe's AI correspondent, said: “I don't think AI will ever be free of bias, at least not as long as we stick to machine learning as we know it today,”…. “What's crucially important, I believe, is to recognize that those biases exist and that policymakers try to mitigate them” [ 17 ]. The High-Level Expert Group on AI of the European Union presented Ethics Guidelines for Trustworthy AI in 2019 that suggested AI systems must be accountable, explainable, and unbiased. Three emphases are given:

• Lawful-respecting all applicable laws and regulations
• Ethical-respecting ethical principles and values
• Robust-being adaptive, reliable, fair, and trustworthy from a technical perspective while taking into account its social environment [ 18 ].

Seven requirements are recommended [ 18 ]:

• AI should not trample on human autonomy. People should not be manipulated or coerced by AI systems, and humans should be able to intervene or oversee every decision that the software makes
• AI should be secure and accurate. It should not be easily compromised by external attacks, and it should be reasonably reliable
• Personal data collected by AI systems should be secure and private. It should not be accessible to just anyone, and it should not be easily stolen
• Data and algorithms used to create an AI system should be accessible, and the decisions made by the software should be “understood and traced by human beings.” In other words, operators should be able to explain the decisions their AI systems make
• Services provided by AI should be available to all, regardless of age, gender, race, or other characteristics. Similarly, systems should not be biased along these lines
• AI systems should be sustainable (i.e., they should be ecologically responsible) and “enhance positive social change”
• AI systems should be auditable and covered by existing protections for corporate whistleblowers. The negative impacts of systems should be acknowledged and reported in advance.

From these guidelines, we can suggest that future AI must be equipped with human sensibility or “AI humanities.” To accomplish this, AI researchers, manufacturers, and all industries must bear in mind that technology is to serve not to manipulate humans and his society. Bostrom and Judkowsky listed responsibility, transparency, auditability, incorruptibility, and predictability [ 19 ] as criteria for the computerized society to think about.

S UGGESTED PRINCIPLES FOR ARTIFICIAL INTELLIGENCE BIOETHICS

Nathan Strout, a reporter at Space and Intelligence System at Easter University, USA, reported just recently that the intelligence community is developing its own AI ethics. The Pentagon made announced in February 2020 that it is in the process of adopting principles for using AI as the guidelines for the department to follow while developing new AI tools and AI-enabled technologies. Ben Huebner, chief of the Office of Director of National Intelligence's Civil Liberties, Privacy, and Transparency Office, said that “We're going to need to ensure that we have transparency and accountability in these structures as we use them. They have to be secure and resilient” [ 20 ]. Two themes have been suggested for the AI community to think more about: Explainability and interpretability. Explainability is the concept of understanding how the analytic works, while interpretability is being able to understand a particular result produced by an analytic [ 20 ].

All the principles suggested by scholars for AI bioethics are well-brought-up. I gather from different bioethical principles in all the related fields of bioethics to suggest four principles here for consideration to guide the future development of the AI technology. We however must bear in mind that the main attention should still be placed on human because AI after all has been designed and manufactured by human. AI proceeds to its work according to its algorithm. AI itself cannot empathize nor have the ability to discern good from evil and may commit mistakes in processes. All the ethical quality of AI depends on the human designers; therefore, it is an AI bioethics and at the same time, a trans-bioethics that abridge human and material worlds. Here are the principles:

• Beneficence: Beneficence means doing good, and here it refers to the purpose and functions of AI should benefit the whole human life, society and universe. Any AI that will perform any destructive work on bio-universe, including all life forms, must be avoided and forbidden. The AI scientists must understand that reason of developing this technology has no other purpose but to benefit human society as a whole not for any individual personal gain. It should be altruistic, not egocentric in nature
• Value-upholding: This refers to AI's congruence to social values, in other words, universal values that govern the order of the natural world must be observed. AI cannot elevate to the height above social and moral norms and must be bias-free. The scientific and technological developments must be for the enhancement of human well-being that is the chief value AI must hold dearly as it progresses further
• Lucidity: AI must be transparent without hiding any secret agenda. It has to be easily comprehensible, detectable, incorruptible, and perceivable. AI technology should be made available for public auditing, testing and review, and subject to accountability standards … In high-stakes settings like diagnosing cancer from radiologic images, an algorithm that can't “explain its work” may pose an unacceptable risk. Thus, explainability and interpretability are absolutely required
• Accountability: AI designers and developers must bear in mind they carry a heavy responsibility on their shoulders of the outcome and impact of AI on whole human society and the universe. They must be accountable for whatever they manufacture and create.

C ONCLUSION

AI is here to stay in our world and we must try to enforce the AI bioethics of beneficence, value upholding, lucidity and accountability. Since AI is without a soul as it is, its bioethics must be transcendental to bridge the shortcoming of AI's inability to empathize. AI is a reality of the world. We must take note of what Joseph Weizenbaum, a pioneer of AI, said that we must not let computers make important decisions for us because AI as a machine will never possess human qualities such as compassion and wisdom to morally discern and judge [ 10 ]. Bioethics is not a matter of calculation but a process of conscientization. Although AI designers can up-load all information, data, and programmed to AI to function as a human being, it is still a machine and a tool. AI will always remain as AI without having authentic human feelings and the capacity to commiserate. Therefore, AI technology must be progressed with extreme caution. As Von der Leyen said in White Paper on AI – A European approach to excellence and trust : “AI must serve people, and therefore, AI must always comply with people's rights…. High-risk AI. That potentially interferes with people's rights has to be tested and certified before it reaches our single market” [ 21 ].

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• The case for taking AI seriously as a threat to humanity

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Stephen Hawking has said , “The development of full artificial intelligence could spell the end of the human race.” Elon Musk claims that AI is humanity’s “ biggest existential threat .”

That might have people asking: Wait, what? But these grand worries are rooted in research. Along with Hawking and Musk, prominent figures at Oxford and UC Berkeley and many of the researchers working in AI today believe that advanced AI systems, if deployed carelessly, could permanently cut off human civilization from a good future.

This concern has been raised since the dawn of computing. But it has come into particular focus in recent years, as advances in machine-learning techniques have given us a more concrete understanding of what we can do with AI, what AI can do for (and to) us, and how much we still don’t know.

There are also skeptics. Some of them think advanced AI is so distant that there’s no point in thinking about it now. Others are worried that excessive hype about the power of their field might kill it prematurely. And even among the people who broadly agree that AI poses unique dangers, there are varying takes on what steps make the most sense today.

The conversation about AI is full of confusion, misinformation, and people talking past each other — in large part because we use the word “AI” to refer to so many things. So here’s the big picture on how artificial intelligence might pose a catastrophic danger, in nine questions:

1) What is AI?

Artificial intelligence is the effort to create computers capable of intelligent behavior. It is a broad catchall term, used to refer to everything from Siri to IBM’s Watson to powerful technologies we have yet to invent.

Some researchers distinguish between “narrow AI” — computer systems that are better than humans in some specific, well-defined field, like playing chess or generating images or diagnosing cancer — and “general AI,” systems that can surpass human capabilities in many domains. We don’t have general AI yet, but we’re starting to get a better sense of the challenges it will pose.

Narrow AI has seen extraordinary progress over the past few years. AI systems have improved dramatically at translation , at games like chess and Go , at important research biology questions like predicting how proteins fold , and at generating images . AI systems determine what you’ll see in a Google search or in your Facebook Newsfeed . They compose music and write articles that, at a glance, read as if a human wrote them. They play strategy games . They are being developed to improve drone targeting and detect missiles .

But narrow AI is getting less narrow . Once, we made progress in AI by painstakingly teaching computer systems specific concepts. To do computer vision — allowing a computer to identify things in pictures and video — researchers wrote algorithms for detecting edges. To play chess, they programmed in heuristics about chess. To do natural language processing (speech recognition, transcription, translation, etc.), they drew on the field of linguistics.

But recently, we’ve gotten better at creating computer systems that have generalized learning capabilities. Instead of mathematically describing detailed features of a problem, we let the computer system learn that by itself. While once we treated computer vision as a completely different problem from natural language processing or platform game playing, now we can solve all three problems with the same approaches .

And as computers get good enough at narrow AI tasks, they start to exhibit more general capabilities. For example, OpenAI’s famous GPT-series of text AIs is, in one sense, the narrowest of narrow AIs — it just predicts what the next word will be in a text, based on the previous words and its corpus of human language. And yet, it can now identify questions as reasonable or unreasonable and discuss the physical world (for example, answering questions about which objects are larger or which steps in a process must come first). In order to be very good at the narrow task of text prediction, an AI system will eventually develop abilities that are not narrow at all.

Our AI progress so far has enabled enormous advances — and has also raised urgent ethical questions. When you train a computer system to predict which convicted felons will reoffend, you’re using inputs from a criminal justice system biased against black people and low-income people — and so its outputs will likely be biased against black and low-income people too . Making websites more addictive can be great for your revenue but bad for your users. Releasing a program that writes convincing fake reviews or fake news might make those widespread, making it harder for the truth to get out.

Rosie Campbell at UC Berkeley’s Center for Human-Compatible AI argues that these are examples, writ small, of the big worry experts have about general AI in the future. The difficulties we’re wrestling with today with narrow AI don’t come from the systems turning on us or wanting revenge or considering us inferior. Rather, they come from the disconnect between what we tell our systems to do and what we actually want them to do.

For example, we tell a system to run up a high score in a video game. We want it to play the game fairly and learn game skills — but if it instead has the chance to directly hack the scoring system, it will do that. It’s doing great by the metric we gave it. But we aren’t getting what we wanted.

In other words, our problems come from the systems being really good at achieving the goal they learned to pursue; it’s just that the goal they learned in their training environment isn’t the outcome we actually wanted. And we’re building systems we don’t understand, which means we can’t always anticipate their behavior.

Right now the harm is limited because the systems are so limited. But it’s a pattern that could have even graver consequences for human beings in the future as AI systems become more advanced.

2) Is it even possible to make a computer as smart as a person?

Yes, though current AI systems aren’t nearly that smart.

One popular adage about AI is “ everything that’s easy is hard, and everything that’s hard is easy .” Doing complex calculations in the blink of an eye? Easy. Looking at a picture and telling you whether it’s a dog? Hard (until very recently).

Lots of things humans do are still outside AI’s grasp. For instance, it’s hard to design an AI system that explores an unfamiliar environment, that can navigate its way from, say, the entryway of a building it’s never been in before up the stairs to a specific person’s desk. We are just beginning to learn how to design an AI system that reads a book and retains an understanding of the concepts.

The paradigm that has driven many of the biggest breakthroughs in AI recently is called “deep learning.” Deep learning systems can do some astonishing stuff: beat games we thought humans might never lose, invent compelling and realistic photographs, solve open problems in molecular biology.

These breakthroughs have made some researchers conclude it’s time to start thinking about the dangers of more powerful systems, but skeptics remain. The field’s pessimists argue that programs still need an extraordinary pool of structured data to learn from, require carefully chosen parameters, or work only in environments designed to avoid the problems we don’t yet know how to solve. They point to self-driving cars , which are still mediocre under the best conditions despite the billions that have been poured into making them work.

It’s rare, though, to find a top researcher in AI who thinks that general AI is impossible. Instead, the field’s luminaries tend to say that it will happen someday — but probably a day that’s a long way off.

Other researchers argue that the day may not be so distant after all.

That’s because for almost all the history of AI, we’ve been held back in large part by not having enough computing power to realize our ideas fully. Many of the breakthroughs of recent years — AI systems that learned how to play strategy games , generate fake photos of celebrities , fold proteins , and compete in massive multiplayer online strategy games — have happened because that’s no longer true. Lots of algorithms that seemed not to work at all turned out to work quite well once we could run them with more computing power.

And the cost of a unit of computing time keeps falling . Progress in computing speed has slowed recently, but the cost of computing power is still estimated to be falling by a factor of 10 every 10 years. Through most of its history, AI has had access to less computing power than the human brain. That’s changing. By most estimates , we’re now approaching the era when AI systems can have the computing resources that we humans enjoy.

And deep learning, unlike previous approaches to AI, is highly suited to developing general capabilities.

“If you go back in history,” top AI researcher and OpenAI cofounder Ilya Sutskever told me , “they made a lot of cool demos with little symbolic AI. They could never scale them up — they were never able to get them to solve non-toy problems. Now with deep learning the situation is reversed. ... Not only is [the AI we’re developing] general, it’s also competent — if you want to get the best results on many hard problems, you must use deep learning. And it’s scalable.”

In other words, we didn’t need to worry about general AI back when winning at chess required entirely different techniques than winning at Go. But now, the same approach produces fake news or music depending on what training data it is fed. And as far as we can discover, the programs just keep getting better at what they do when they’re allowed more computation time — we haven’t discovered a limit to how good they can get. Deep learning approaches to most problems blew past all other approaches when deep learning was first discovered.

Furthermore, breakthroughs in a field can often surprise even other researchers in the field. “Some have argued that there is no conceivable risk to humanity [from AI] for centuries to come,” wrote UC Berkeley professor Stuart Russell, “perhaps forgetting that the interval of time between Rutherford’s confident assertion that atomic energy would never be feasibly extracted and Szilárd’s invention of the neutron-induced nuclear chain reaction was less than twenty-four hours.”

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There’s another consideration. Imagine an AI that is inferior to humans at everything, with one exception: It’s a competent engineer that can build AI systems very effectively. Machine learning engineers who work on automating jobs in other fields often observe, humorously, that in some respects, their own field looks like one where much of the work — the tedious tuning of parameters — could be automated.

If we can design such a system, then we can use its result — a better engineering AI — to build another, even better AI. This is the mind-bending scenario experts call “recursive self-improvement,” where gains in AI capabilities enable more gains in AI capabilities, allowing a system that started out behind us to rapidly end up with abilities well beyond what we anticipated.

This is a possibility that has been anticipated since the first computers. I.J. Good, a colleague of Alan Turing who worked at the Bletchley Park codebreaking operation during World War II and helped build the first computers afterward, may have been the first to spell it out, back in 1965 : “An ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.”

3) How exactly could AI wipe us out?

It’s immediately clear how nuclear bombs will kill us . No one working on mitigating nuclear risk has to start by explaining why it’d be a bad thing if we had a nuclear war.

The case that AI could pose an existential risk to humanity is more complicated and harder to grasp. So many of the people who are working to build safe AI systems have to start by explaining why AI systems, by default, are dangerous.

The idea that AI can become a danger is rooted in the fact that AI systems pursue their goals, whether or not those goals are what we really intended — and whether or not we’re in the way. “You’re probably not an evil ant-hater who steps on ants out of malice,” Stephen Hawking wrote, “but if you’re in charge of a hydroelectric green-energy project and there’s an anthill in the region to be flooded, too bad for the ants. Let’s not place humanity in the position of those ants.”

Here’s one scenario that keeps experts up at night: We develop a sophisticated AI system with the goal of, say, estimating some number with high confidence. The AI realizes it can achieve more confidence in its calculation if it uses all the world’s computing hardware, and it realizes that releasing a biological superweapon to wipe out humanity would allow it free use of all the hardware. Having exterminated humanity, it then calculates the number with higher confidence.

It is easy to design an AI that averts that specific pitfall. But there are lots of ways that unleashing powerful computer systems will have unexpected and potentially devastating effects, and avoiding all of them is a much harder problem than avoiding any specific one.

Victoria Krakovna, an AI researcher at DeepMind (now a division of Alphabet, Google’s parent company), compiled a list of examples of “specification gaming” : the computer doing what we told it to do but not what we wanted it to do. For example, we tried to teach AI organisms in a simulation to jump, but we did it by teaching them to measure how far their “feet” rose above the ground. Instead of jumping, they learned to grow into tall vertical poles and do flips — they excelled at what we were measuring, but they didn’t do what we wanted them to do.

An AI playing the Atari exploration game Montezuma’s Revenge found a bug that let it force a key in the game to reappear , thereby allowing it to earn a higher score by exploiting the glitch. An AI playing a different game realized it could get more points by falsely inserting its name as the owner of high-value items .

Sometimes, the researchers didn’t even know how their AI system cheated : “the agent discovers an in-game bug. ... For a reason unknown to us, the game does not advance to the second round but the platforms start to blink and the agent quickly gains a huge amount of points (close to 1 million for our episode time limit).”

What these examples make clear is that in any system that might have bugs or unintended behavior or behavior humans don’t fully understand, a sufficiently powerful AI system might act unpredictably — pursuing its goals through an avenue that isn’t the one we expected.

In his 2009 paper “The Basic AI Drives,” Steve Omohundro , who has worked as a computer science professor at the University of Illinois Urbana-Champaign and as the president of Possibility Research, argues that almost any AI system will predictably try to accumulate more resources, become more efficient, and resist being turned off or modified: “These potentially harmful behaviors will occur not because they were programmed in at the start, but because of the intrinsic nature of goal driven systems.”

His argument goes like this: Because AIs have goals, they’ll be motivated to take actions that they can predict will advance their goals. An AI playing a chess game will be motivated to take an opponent’s piece and advance the board to a state that looks more winnable.

But the same AI, if it sees a way to improve its own chess evaluation algorithm so it can evaluate potential moves faster, will do that too, for the same reason: It’s just another step that advances its goal.

If the AI sees a way to harness more computing power so it can consider more moves in the time available, it will do that. And if the AI detects that someone is trying to turn off its computer mid-game, and it has a way to disrupt that, it’ll do it. It’s not that we would instruct the AI to do things like that; it’s that whatever goal a system has, actions like these will often be part of the best path to achieve that goal.

That means that any goal, even innocuous ones like playing chess or generating advertisements that get lots of clicks online, could produce unintended results if the agent pursuing it has enough intelligence and optimization power to identify weird, unexpected routes to achieve its goals.

Goal-driven systems won’t wake up one day with hostility to humans lurking in their hearts. But they will take actions that they predict will help them achieve their goal — even if we’d find those actions problematic, even horrifying. They’ll work to preserve themselves, accumulate more resources, and become more efficient. They already do that, but it takes the form of weird glitches in games. As they grow more sophisticated, scientists like Omohundro predict more adversarial behavior.

4) When did scientists first start worrying about AI risk?

Scientists have been thinking about the potential of artificial intelligence since the early days of computers. In the famous paper where he put forth the Turing test for determining if an artificial system is truly “intelligent,” Alan Turing wrote:

Let us now assume, for the sake of argument, that these machines are a genuine possibility, and look at the consequences of constructing them. ... There would be plenty to do in trying to keep one’s intelligence up to the standards set by the machines, for it seems probable that once the machine thinking method had started, it would not take long to outstrip our feeble powers. … At some stage therefore we should have to expect the machines to take control.

I.J. Good worked closely with Turing and reached the same conclusions, according to his assistant, Leslie Pendleton . In an excerpt from unpublished notes Good wrote shortly before he died in 2009, he writes about himself in third person and notes a disagreement with his younger self — while as a younger man, he thought powerful AIs might be helpful to us, the older Good expected AI to annihilate us.

[The paper] “Speculations Concerning the First Ultra-intelligent Machine” (1965) ... began: “The survival of man depends on the early construction of an ultra-intelligent machine.” Those were his words during the Cold War, and he now suspects that “survival” should be replaced by “extinction.” He thinks that, because of international competition, we cannot prevent the machines from taking over. He thinks we are lemmings. He said also that “probably Man will construct the deus ex machina in his own image.”

In the 21st century, with computers quickly establishing themselves as a transformative force in our world, younger researchers started expressing similar worries.

Nick Bostrom is a professor at the University of Oxford, the director of the Future of Humanity Institute, and the director of the Governance of Artificial Intelligence Program . He researches risks to humanity , both in the abstract — asking questions like why we seem to be alone in the universe — and in concrete terms, analyzing the technological advances on the table and whether they endanger us. AI, he concluded, endangers us.

In 2014, he wrote a book explaining the risks AI poses and the necessity of getting it right the first time, concluding, “once unfriendly superintelligence exists, it would prevent us from replacing it or changing its preferences. Our fate would be sealed.”

Across the world, others have reached the same conclusion. Bostrom co-authored a paper on the ethics of artificial intelligence with Eliezer Yudkowsky, founder of and research fellow at the Berkeley Machine Intelligence Research Institute (MIRI), an organization that works on better formal characterizations of the AI safety problem.

Yudkowsky started his career in AI by worriedly poking holes in others’ proposals for how to make AI systems safe , and has spent most of it working to persuade his peers that AI systems will, by default, be unaligned with human values (not necessarily opposed to but indifferent to human morality) — and that it’ll be a challenging technical problem to prevent that outcome.

Increasingly, researchers realized that there’d be challenges that hadn’t been present with AI systems when they were simple. “‘Side effects’ are much more likely to occur in a complex environment, and an agent may need to be quite sophisticated to hack its reward function in a dangerous way. This may explain why these problems have received so little study in the past, while also suggesting their importance in the future,” concluded a 2016 research paper on problems in AI safety.

Bostrom’s book Superintelligence was compelling to many people, but there were skeptics. “ No, experts don’t think superintelligent AI is a threat to humanity ,” argued an op-ed by Oren Etzioni, a professor of computer science at the University of Washington and CEO of the Allan Institute for Artificial Intelligence. “ Yes, we are worried about the existential risk of artificial intelligence ,” replied a dueling op-ed by Stuart Russell, an AI pioneer and UC Berkeley professor, and Allan DaFoe, a senior research fellow at Oxford and director of the Governance of AI program there.

It’s tempting to conclude that there’s a pitched battle between AI-risk skeptics and AI-risk believers. In reality, they might not disagree as profoundly as you would think.

Facebook’s chief AI scientist Yann LeCun, for example, is a vocal voice on the skeptical side. But while he argues we shouldn’t fear AI, he still believes we ought to have people working on, and thinking about, AI safety . “Even if the risk of an A.I. uprising is very unlikely and very far in the future, we still need to think about it, design precautionary measures, and establish guidelines,” he writes.

That’s not to say there’s an expert consensus here — far from it . There is substantial disagreement about which approaches seem likeliest to bring us to general AI, which approaches seem likeliest to bring us to safe general AI, and how soon we need to worry about any of this.

Many experts are wary that others are overselling their field, and dooming it when the hype runs out . But that disagreement shouldn’t obscure a growing common ground; these are possibilities worth thinking about, investing in, and researching, so we have guidelines when the moment comes that they’re needed.

5) Why couldn’t we just shut off a computer if it got too powerful?

A smart AI could predict that we’d want to turn it off if it made us nervous. So it would try hard not to make us nervous, because doing so wouldn’t help it accomplish its goals. If asked what its intentions are, or what it’s working on, it would attempt to evaluate which responses are least likely to get it shut off, and answer with those. If it wasn’t competent enough to do that, it might pretend to be even dumber than it was — anticipating that researchers would give it more time, computing resources, and training data.

So we might not know when it’s the right moment to shut off a computer.

We also might do things that make it impossible to shut off the computer later, even if we realize eventually that it’s a good idea. For example, many AI systems could have access to the internet, which is a rich source of training data and which they’d need if they’re to make money for their creators (for example, on the stock market, where more than half of trading is done by fast-reacting AI algorithms).

But with internet access, an AI could email copies of itself somewhere where they’ll be downloaded and read, or hack vulnerable systems elsewhere. Shutting off any one computer wouldn’t help.

In that case, isn’t it a terrible idea to let any AI system — even one which doesn’t seem powerful enough to be dangerous — have access to the internet? Probably. But that doesn’t mean it won’t continue to happen. AI researchers want to make their AI systems more capable — that’s what makes them more scientifically interesting and more profitable. It’s not clear that the many incentives to make your systems powerful and use them online will suddenly change once systems become powerful enough to be dangerous.

So far, we’ve mostly talked about the technical challenges of AI. But from here forward, it’s necessary to veer more into the politics. Since AI systems enable incredible things, there will be lots of different actors working on such systems.

There will likely be startups, established tech companies like Google (Alphabet’s recently acquired startup DeepMind is frequently mentioned as an AI frontrunner), and organizations like Elon-Musk-founded OpenAI, which recently transitioned to a hybrid for-profit/non-profit structure .

There will be governments — Russia’s Vladimir Putin has expressed an interest in AI , and China has made big investments . Some of them will presumably be cautious and employ safety measures, including keeping their AI off the internet. But in a scenario like this one, we’re at the mercy of the least cautious actor , whoever they may be.

That’s part of what makes AI hard: Even if we know how to take appropriate precautions (and right now we don’t), we also need to figure out how to ensure that all would-be AI programmers are motivated to take those precautions and have the tools to implement them correctly.

6) What are we doing right now to avoid an AI apocalypse?

“It could be said that public policy on AGI [artificial general intelligence] does not exist,” concluded a paper in 2018 reviewing the state of the field .

The truth is that technical work on promising approaches is getting done, but there’s shockingly little in the way of policy planning, international collaboration, or public-private partnerships. In fact, much of the work is being done by only a handful of organizations, and it has been estimated that around 50 people in the world work full time on technical AI safety.

Bostrom’s Future of Humanity Institute has published a research agenda for AI governance : the study of “devising global norms, policies, and institutions to best ensure the beneficial development and use of advanced AI.” It has published research on the risk of malicious uses of AI , on the context of China’s AI strategy, and on artificial intelligence and international security .

The longest-established organization working on technical AI safety is the Machine Intelligence Research Institute (MIRI), which prioritizes research into designing highly reliable agents — artificial intelligence programs whose behavior we can predict well enough to be confident they’re safe. (Disclosure: MIRI is a nonprofit and I donated to its work in 2017-2019.)

The Elon Musk-founded OpenAI is a very new organization, less than three years old. But researchers there are active contributors to both AI safety and AI capabilities research. A research agenda in 2016 spelled out “ concrete open technical problems relating to accident prevention in machine learning systems,” and researchers have since advanced some approaches to safe AI systems .

Alphabet’s DeepMind, a leader in this field, has a safety team and a technical research agenda outlined here . “Our intention is to ensure that AI systems of the future are not just ‘hopefully safe’ but robustly, verifiably safe ,” it concludes, outlining an approach with an emphasis on specification (designing goals well), robustness (designing systems that perform within safe limits under volatile conditions), and assurance (monitoring systems and understanding what they’re doing).

There are also lots of people working on more present-day AI ethics problems: algorithmic bias , robustness of modern machine-learning algorithms to small changes, and transparency and interpretability of neural nets , to name just a few. Some of that research could potentially be valuable for preventing destructive scenarios.

But on the whole, the state of the field is a little bit as if almost all climate change researchers were focused on managing the droughts, wildfires, and famines we’re already facing today, with only a tiny skeleton team dedicating to forecasting the future and 50 or so researchers who work full time on coming up with a plan to turn things around.

Not every organization with a major AI department has a safety team at all, and some of them have safety teams focused only on algorithmic fairness and not on the risks from advanced systems. The US government doesn’t have a department for AI.

The field still has lots of open questions — many of which might make AI look much scarier, or much less so — which no one has dug into in depth.

7) Is this really likelier to kill us all than, say, climate change?

It sometimes seems like we’re facing dangers from all angles in the 21st century. Both climate change and future AI developments are likely to be transformative forces acting on our world.

Our predictions about climate change are more confident, both for better and for worse. We have a clearer understanding of the risks the planet will face, and we can estimate the costs to human civilization. They are projected to be enormous, risking potentially hundreds of millions of lives. The ones who will suffer most will be low-income people in developing countries ; the wealthy will find it easier to adapt. We also have a clearer understanding of the policies we need to enact to address climate change than we do with AI.

There’s intense disagreement in the field on timelines for critical advances in AI . While AI safety experts agree on many features of the safety problem, they’re still making the case to research teams in their own field, and they disagree on some of the details. There’s substantial disagreement on how badly it could go, and on how likely it is to go badly. There are only a few people who work full time on AI forecasting. One of the things current researchers are trying to nail down is their models and the reasons for the remaining disagreements about what safe approaches will look like.

Most experts in the AI field think it poses a much larger risk of total human extinction than climate change, since analysts of existential risks to humanity think that climate change, while catastrophic, is unlikely to lead to human extinction . But many others primarily emphasize our uncertainty — and emphasize that when we’re working rapidly toward powerful technology about which there are still many unanswered questions, the smart step is to start the research now.

8) Is there a possibility that AI can be benevolent?

AI safety researchers emphasize that we shouldn’t assume AI systems will be benevolent by default . They’ll have the goals that their training environment set them up for, and no doubt this will fail to encapsulate the whole of human values.

When the AI gets smarter, might it figure out morality by itself? Again, researchers emphasize that it won’t. It’s not really a matter of “figuring out” — the AI will understand just fine that humans actually value love and fulfillment and happiness, and not just the number associated with Google on the New York Stock Exchange. But the AI’s values will be built around whatever goal system it was initially built around, which means it won’t suddenly become aligned with human values if it wasn’t designed that way to start with.

Of course, we can build AI systems that are aligned with human values, or at least that humans can safely work with. That is ultimately what almost every organization with an artificial general intelligence division is trying to do. Success with AI could give us access to decades or centuries of technological innovation all at once.

“If we’re successful, we believe this will be one of the most important and widely beneficial scientific advances ever made,” writes the introduction to Alphabet’s DeepMind . “From climate change to the need for radically improved healthcare, too many problems suffer from painfully slow progress, their complexity overwhelming our ability to find solutions. With AI as a multiplier for human ingenuity, those solutions will come into reach.”

So, yes, AI can share our values — and transform our world for the good. We just need to solve a very hard engineering problem first.

9) I just really want to know: how worried should we be?

To people who think the worrying is premature and the risks overblown, AI safety is competing with other priorities that sound, well, a bit less sci-fi — and it’s not clear why AI should take precedence. To people who think the risks described are real and substantial, it’s outrageous that we’re dedicating so few resources to working on them.

While machine-learning researchers are right to be wary of hype, it’s also hard to avoid the fact that they’re accomplishing some impressive, surprising things using very generalizable techniques, and that it doesn’t seem that all the low-hanging fruit has been picked.

AI looks increasingly like a technology that will change the world when it arrives. Researchers across many major AI organizations tell us it will be like launching a rocket : something we have to get right before we hit “go.” So it seems urgent to get to work learning rocketry. No matter whether or not humanity should be afraid, we should definitely be doing our homework.

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Essay on Artificial Intelligence as a Threat in the Society

Introduction

Artificial Intelligence is defined as “the scientific knowledge of the mechanisms that underlie cognition and intelligent behavior and its integration in machines,” according to the Association for the Advancement of Artificial Intelligence. For the past few decades, several predictions were made based on the high incoming of Artificial Intelligence (AI). The transition and its effects on most aspects of the society of businesses and everyday life. It is also essential to note that adequately anticipating the impact of the AI revolution has its implications since AI- automated machines might be our “final invention,” putting an end to human supremacy (Makridakis, 2017, p. 55). Without a doubt, artificial intelligence has a high potential, as both its technology and automation will most likely achieve highly productive and sustainable economic growth. Within the next two decades, its high human intellectual ability poses a severe threat to the workforce market that is initially under human labor. For the first time, it raises concerns about the end of human superiority. While AI can boost the economic growth rate, it also faces significant risks such as employment market fragmentation, increasing inequality, underemployment, and new undesirable industrial structures. EU policy must establish the circumstances for AI’s potential to thrive while also carefully examining how to manage the threats it entails.

Challenges of Artificial Intelligence on the Society

The study re-examines assumptions made about AI’s effects on jobs, inequality, and production, as well as general economic growth. For two reasons, we do so. A few theoretical economic frameworks include AI, and almost none that take demand-side restrictions into account. The second point is that expectations of AI producing enormous job losses and quicker economic and GDP growth conflict with reality: in the developed nations, unemployment is at crisis levels. Income and output growth, on the other hand, is stagnant, and disparities are rising. In the light of accelerating AI progress, this model is a guide to provide a theoretical justification. Jobs aren’t the only thing that might be affected. Economic growth and income stability are certain to be impacted as well. According to (Frey et al., 2017, p.268), the influence of emerging technologies such as AI is subject to an ‘execution lag.’ As AI adoption proceeds, ‘high productivity rate will also be increasing dramatically as an ever-increasing rate of unemployment cascades through the economy,’ according to the report (Nordhaus, 2015, p.2).

Impact on Jobs

Several widely cited original reports suggested that automation of occupations and functions will eventually displace a significant portion of the human labor force. They are anticipated that up to 47% of US occupations might be automated in ten to twenty years in a widely regarded paper (Syverson, 2017, p. 171). This might be even higher in a similar study case of the EU, with up to 54% of occupations being computerized in 10 to 20 years, using a similar methodology. Regular tasks can readily be automated, making specific roles obsolete over time. Customer service/call center operations, document categorization, and recovery, and content moderation, for example, are increasingly relying on increased automation rather than human labor. People are being replaced by automated robotic systems which can effectively move around the area, locate and move stuff, and carry out complex assembling operations. As frightening as these projections may be, recent theoretical and empirical research suggests that the effect of AI-automated jobs lost may be significantly exaggerated. New theoretical revisions, such as those by Bessen (2018), reveal that, based on the flexibility of demand for the product in issue, there is a reasonable probability that jobs might rise as a result of the AI-automation.

Impact on Inequality

Since Artificial intelligence has a diverse influence on various jobs and workers, it may negatively affect earnings. In research in six European nations, two significant channels have been identified through which AI-automation will deteriorate wealth inequality: The benefits, for example, may only flow to a small number of firms due to increased ‘invention costs’ from AI, while the other is when Artificial Intelligence is moving relative labor supply, which in turn affects comparable salaries (Nordhaus, 2015, p. 18). Ideally, as more manual work is substituted by Ai technologies, productivity rises and general earnings growth will be, and the more significant the gap between rich and poor will widen.

There are legitimate concerns that AI would worsen present trends of changing the national income distribution away from labor, resulting in more disparity and wealth concentration in “superstar” enterprises and industries. Another source of rising income inequality may be our inability to categorize revenue at the conventional point—income or exchange— as a smaller percentage of the market is registered, taxed, and dispersed. Instead of taxing income, one apparent alternative would be to tax the wealthy directly, such as a company’s market value (Makridakis, 2017, p. 55). The information era may make tracking income equality simpler than previously, making this technique more feasible than it has been in the past, especially given the difficulties of tracking income.

Impact on Privacy and Autonomy

When evaluating the impact of Artificial Intelligence on behavioral patterns, we’ve finally arrived at a point where ICT has a distinct effect. Domestic surveillance has a long history, and it has been linked to anything from skewed employment prospects to pogroms. However, information and communication technology (ICT) now allows us to preserve permanent records on everyone who generates stored data, such as invoices, bank statements, digital gadgets, or credit history, not to forget any open publishing or social network usage. Our civilization is being transformed by storing and accessing digital information and by the fact that all this data may be accessed using a pattern detection algorithm. By complexity, we have lost the basic presumption of being anonymous. We are all famous to some extent now: random people can identify any of us, whether through facial – recognition or information extraction of shopping or social networks activities (Reed et al., 2016, p.1065). Artificial Intelligence has facilitated robotic cognitive abilities in speech transcription, emotion recognition from audiovisual recordings, and written or video forgery. This technique enables forging by mixing a model of various people’s handwriting or their utterances with a text flow to get a “prediction” or interpretation of how the person would probably write or pronounce that text.

Artificial intelligence has been transforming societies faster than we understand, yet it isn’t as original or distinctive in human experience as we are frequently made to believe corporations and governments, telecommunications, and natural gas, among other artifactual entities, have previously expanded our powers, changed our economies, and upset our social co-existence, but not universally, for the better. However, we must keep in mind that, above and beyond the economical and governance issues, AI enhances and improves what makes us unique in the first place, especially our problem-solving ability. Considering the ongoing worldwide challenges including security, privacy and development, such improvements are anticipated to remain to be beneficial. Because AI lacks a soul, its philosophy should be transcendental to compensate for its incapacity to sympathize. Artificial intelligence (AI) is a fact of life. We must remember what AI inventor Joseph Weizenbaum said: “We cannot let machines make critical decisions for humanity since AI will never have human attributes such as empathy and intelligence to perceive and judge morally.”

Frey, C. and Osborne, M. (2013). The Future of Employment: How Susceptible are Jobs to Computerization? Oxford Martin Programme on the Impacts of Future Technology, University of Oxford: p. 50-67.

Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60. doi.org/10.1016/j.futures.2017.03.006

Nordhaus, W. (2015). Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth. Cowles Foundation Discussion Paper no. 2021. Yale University: 1-30.

Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., and Lee, H. 2016. “Generative adversarial text to image synthesis.” In  Proceedings of the 33rd International Conference on Machine Learning  48: 1060–1069.

Syverson, C. (2017). Challenges to Mismeasurement Explanations for the US Productivity Slowdown. Journal of Economic Perspectives, 31(2):165–186.

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The profound impact of Artificial Intelligence on society – Exploring the far-reaching implications of AI technology

Artificial intelligence (AI) has revolutionized the way we live and work, and its influence on society continues to grow. This essay explores the impact of AI on various aspects of our lives, including economy, employment, healthcare, and even creativity.

One of the most significant impacts of AI is on the economy. AI-powered systems have the potential to streamline and automate various processes, increasing efficiency and productivity. This can lead to economic growth and increased competitiveness in the global market. However, it also raises concerns about job displacement and income inequality, as AI technologies replace certain job roles.

In the realm of healthcare, AI has already made its mark. From early detection of diseases to personalized treatment plans, AI algorithms have become invaluable in improving patient outcomes. With the ability to analyze vast amounts of medical data, AI systems can identify patterns and make predictions that human doctors may miss. Nevertheless, ethical considerations regarding patient privacy and data security need to be addressed.

Furthermore, AI’s impact on creativity is an area of ongoing exploration. While AI technologies can generate artwork, music, and literature, the question of whether they can truly replicate human creativity remains. Some argue that AI can enhance human creativity by providing new tools and inspiration, while others fear that it may diminish the value of genuine human artistic expression.

In conclusion, the impact of artificial intelligence on society is multifaceted. While it brings economic advancements and improvements in healthcare, it also presents challenges and ethical dilemmas. As AI continues to evolve, it is crucial to strike a balance that maximizes its benefits while minimizing its potential drawbacks.

The Definition of Artificial Intelligence

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. It involves the development of computer systems that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and problem-solving.

AI has a profound impact on society, revolutionizing various industries and sectors. Its disruptive nature has led to significant advancements in the way businesses operate, healthcare is delivered, and everyday tasks are performed. AI technologies have the potential to automate repetitive tasks, analyze vast amounts of data with speed and accuracy, and enhance the efficiency and effectiveness of various processes.

Furthermore, AI has the potential to transform the workforce, leading to changes in the job market. While some fear that AI will replace human workers and result in unemployment, others argue that it will create new job opportunities and improve overall productivity. The societal impact of AI is complex and multifaceted, necessitating careful consideration and management.

In summary , artificial intelligence is the development of computer systems that can mimic human intelligence and perform tasks that traditionally require human thinking. Its impact on society is vast, affecting industries, job markets, and everyday life. Understanding the definition and implications of AI is crucial as we navigate the ever-evolving technological landscape.

The History of Artificial Intelligence

The impact of artificial intelligence on society is a topic that has gained increasing attention in recent years. As technology continues to advance at a rapid pace, the capabilities of artificial intelligence are expanding as well. But how did we get to this point? Let’s take a brief look at the history of artificial intelligence.

The concept of artificial intelligence dates back to ancient times, with the development of mechanical devices that were capable of performing simple calculations. However, it wasn’t until the mid-20th century that the field of AI began to take shape.

In 1956, a group of researchers organized the famous Dartmouth Conference, where the field of AI was officially born. This conference brought together leading experts from various disciplines to explore the possibilities of creating “machines that can think.”

During the following decades, AI research progressed with the development of first-generation computers and the introduction of programming languages. In the 1960s, researchers focused on creating natural language processing systems, while in the 1970s, expert systems became popular.

However, in the 1980s, AI faced a major setback known as the “AI winter.” Funding for AI research significantly declined due to the lack of significant breakthroughs. The field faced criticism and skepticism, and it seemed that the promise of AI might never be realized.

But in the 1990s, AI began to emerge from its winter. The introduction of powerful computers and the availability of massive amounts of data fueled the development of machine learning algorithms. This led to significant advancements in areas such as computer vision, speech recognition, and natural language processing.

Over the past few decades, AI has continued to evolve and impact various aspects of society. From virtual assistants like Siri and Alexa to autonomous vehicles and recommendation systems, artificial intelligence is becoming increasingly integrated into our daily lives.

As we move forward, the impact of artificial intelligence on society is only expected to grow. With ongoing advancements in AI technology, we can expect to see even more significant changes in fields such as healthcare, finance, transportation, and more.

In conclusion, the history of artificial intelligence is one of perseverance and innovation. From its humble beginnings to its current state, AI has come a long way. It has evolved from simple mechanical devices to complex algorithms that can learn and make decisions. The impact of artificial intelligence on society will continue to shape our future, and it is essential to consider both the positive and negative implications as we navigate this technological revolution.

The Advantages of Artificial Intelligence

Artificial intelligence (AI) is a rapidly developing technology that is having a significant impact on society. It has the potential to revolutionize various aspects of our lives, bringing about many advantages that can benefit individuals and communities alike.

1. Increased Efficiency

One of the major advantages of AI is its ability to automate tasks and processes, leading to increased efficiency. AI systems can analyze large amounts of data and perform complex calculations at a speed much faster than humans. This can help businesses optimize their operations, reduce costs, and improve productivity.

2. Enhanced Accuracy

AI technologies can also improve accuracy and precision in various domains. Machine learning algorithms can learn from large datasets and make predictions or decisions with a high level of accuracy. This can be particularly beneficial in fields such as healthcare, where AI can assist doctors in diagnosing diseases, detecting patterns in medical images, and recommending personalized treatments.

Additionally, AI-powered systems can minimize human error in areas where precision is crucial, such as manufacturing and transportation. By automating repetitive tasks and monitoring processes in real-time, AI can help avoid costly mistakes and improve overall quality.

Overall, the advantages of artificial intelligence are numerous and diverse. From increased efficiency to enhanced accuracy, AI has the potential to transform various industries and improve the quality of life for individuals and societies as a whole. It is crucial, however, to continue exploring the ethical implications of AI and ensure that its development is guided by principles that prioritize the well-being and safety of humanity.

The Disadvantages of Artificial Intelligence

While the impact of artificial intelligence on society has been largely positive, it is important to also consider its disadvantages.

1. Job Displacement

One of the biggest concerns regarding artificial intelligence is the potential for job displacement. As machines become more intelligent and capable of performing complex tasks, there is a growing fear that many jobs will become obsolete. This can lead to unemployment and economic instability, as individuals struggle to find work in a society increasingly dominated by artificial intelligence.

2. Ethical Concerns

Another disadvantage of artificial intelligence is the ethical concerns it raises. As artificial intelligence systems become more advanced, there is a need for clear guidelines and regulations to ensure that they are used responsibly. Issues such as privacy, data protection, and algorithmic bias need to be addressed to prevent misuse or unintended consequences.

In conclusion, while artificial intelligence has had a positive impact on society, there are also disadvantages that need to be considered. Job displacement and ethical concerns are just a few of the challenges that need to be addressed as we continue to advance in the field of artificial intelligence.

The Ethical Concerns of Artificial Intelligence

As artificial intelligence continues to impact society in numerous ways, it is important to address the ethical concerns that arise from its use. As AI becomes more commonplace in various industries, including healthcare, finance, and transportation, the potential for unintended consequences and ethical dilemmas increases.

One of the primary ethical concerns of artificial intelligence is the issue of privacy. With the advancements in AI technology, there is a growing ability for machines to collect and analyze vast amounts of personal data. This raises questions about how this data is used, who has access to it, and whether individuals have a right to control and protect their own information.

Another ethical concern is the potential for AI to perpetuate and amplify existing biases and discrimination. AI algorithms are trained on existing data, which can reflect societal biases and prejudices. If these biases are not identified and addressed, AI systems can inadvertently perpetuate unfair practices and discrimination, leading to negative impacts on marginalized communities.

Additionally, the use of AI in decision-making processes raises concerns about accountability and transparency. As AI systems make more complex decisions that affect individuals’ lives, it becomes crucial to understand how these decisions are made. Lack of transparency and accountability can result in a loss of trust in AI systems, especially if they make decisions that have significant consequences.

Furthermore, there is the concern of the impact of AI on employment and the workforce. As AI technology advances, there is the potential for job displacement and the loss of livelihoods. This raises questions about the responsibility of society to provide support and retraining for individuals who are affected by the automation of tasks previously carried out by humans.

Overall, as artificial intelligence continues to evolve and become more integrated into society, it is crucial to actively address the ethical concerns that arise. This involves establishing clear guidelines and regulations to safeguard privacy, address biases, ensure transparency, and mitigate the impact on employment. By addressing these concerns proactively, society can harness the benefits of AI while minimizing its negative impacts.

The Impact of Artificial Intelligence on Jobs

The advancement of artificial intelligence (AI) technology is having a profound impact on society as a whole. One area that is particularly affected by this technological revolution is the job market. The introduction of AI into various industries is changing the way we work and the types of jobs that are available. It is important to understand the implications of this impact on jobs and how it will shape the future of work.

The Rise of Automation

One of the main ways AI impacts jobs is through automation. AI algorithms and machines are increasingly replacing human workers in repetitive and routine tasks. Jobs that involve tasks that can be easily automated, such as data entry or assembly line work, are being taken over by AI-powered technology. This shift towards automation has the potential to lead to job displacement and unemployment for many individuals.

New Opportunities and Skill Requirements

While AI may be replacing certain jobs, it is also creating new opportunities. As industries become more automated, there is a growing demand for workers who are skilled in managing and developing AI technology. Jobs that require expertise in AI programming and data analysis are becoming increasingly important. This means that individuals who possess these skills will have an advantage in the job market, while those without them may struggle to find employment.

Furthermore, AI technology has the potential to transform existing jobs rather than eliminate them entirely. As AI systems become more sophisticated, they can assist human workers in performing tasks more efficiently and accurately. This collaboration between humans and machines can lead to increased productivity and job growth in certain industries.

The Need for Adaptation and Lifelong Learning

The impact of AI on jobs highlights the importance of adaptation and lifelong learning. As technology continues to evolve, workers must be willing to learn new skills and adapt to changing job requirements. The ability to continuously update one’s skills will be crucial in order to remain relevant in the job market. This necessitates a shift towards lifelong learning and a willingness to embrace new technologies.

In conclusion, the impact of artificial intelligence on jobs is significant and multifaceted. While AI technology has the potential to automate certain tasks and lead to job displacement, it also creates new opportunities and changes the nature of existing jobs. The key to navigating this changing job market is adaptation, lifelong learning, and acquiring new skills in AI-related fields. By understanding and adapting to the impact of AI on jobs, society can ensure that the benefits of this technology are maximized while minimizing negative consequences.

The Impact of Artificial Intelligence on Education

Artificial intelligence (AI) is rapidly transforming various aspects of society, and one area where its impact is particularly noteworthy is education. In this essay, we will explore how AI is revolutionizing the educational landscape and the implications it has for both teachers and students.

AI has the potential to greatly enhance the learning experience for students. With intelligent algorithms and personalized learning platforms, students can receive customized instruction tailored to their individual needs and learning styles. This can help to bridge gaps in understanding, improve retention, and ultimately lead to better academic outcomes.

Moreover, AI can serve as a valuable tool for teachers. By automating administrative tasks, such as grading and data analysis, teachers can save time and focus on what they do best: teaching. AI can also provide valuable insights into student performance and progress, allowing teachers to identify areas where additional support may be needed.

However, it is important to recognize that AI is not a substitute for human teachers. While AI can provide personalized instruction and automate certain tasks, it lacks the emotional intelligence and interpersonal skills that are essential for effective teaching. Teachers play a critical role in creating a supportive and nurturing learning environment, and their expertise cannot be replaced by technology.

Another concern is the potential bias and ethical implications associated with AI in education. With algorithms determining the content and delivery of educational materials, there is a risk of reinforcing existing inequalities and perpetuating discriminatory practices. It is crucial to ensure that AI systems are designed and implemented in an ethical and inclusive manner, taking into account issues of fairness and equity.

In conclusion, the impact of artificial intelligence on education is profound. It has the potential to revolutionize the way students learn and teachers teach. However, it is crucial to approach AI in education with caution, being mindful of the limitations and ethical considerations. By harnessing the power of AI while preserving the irreplaceable role of human teachers, we can create a future of education that is truly transformative.

The Impact of Artificial Intelligence on Healthcare

Artificial intelligence (AI) is revolutionizing the healthcare industry, and its impact on society cannot be overstated. Through the use of advanced algorithms and machine learning, AI is transforming various aspects of healthcare, from diagnosis and treatment to drug discovery and patient care.

One of the key areas where AI is making a significant impact is in diagnosing diseases. With the ability to analyze massive amounts of medical data, AI algorithms can now detect patterns and identify potential diseases in patients more accurately and efficiently than ever before. This can lead to early detection and intervention, ultimately saving lives.

AI is also streamlining the drug discovery process, which traditionally has been a time-consuming and costly endeavor. By analyzing vast amounts of data and simulating molecular structures, AI can help researchers identify potential drug candidates more quickly and accurately. This has the potential to accelerate the development of new treatments and improve patient outcomes.

Furthermore, AI is transforming patient care through personalized medicine. By analyzing an individual’s genetic and medical data, AI algorithms can provide personalized treatment plans tailored to the specific needs of each patient. This can lead to more effective treatments, reduced side effects, and improved overall patient satisfaction.

In addition to diagnosis and treatment, AI is also improving healthcare delivery and efficiency. AI-powered chatbots and virtual assistants can now provide patients with personalized medical advice and answer their questions 24/7. This reduces the burden on healthcare providers and allows for more accessible and convenient healthcare services.

However, as with any new technology, there are also challenges and concerns surrounding the use of AI in healthcare. Issues such as data privacy, ethical considerations, and bias in algorithms need to be addressed to ensure that AI is used responsibly and for the benefit of all patients.

In conclusion, the impact of artificial intelligence on healthcare is immense. With advancements in AI, the healthcare industry is poised to revolutionize patient care, diagnosis, and treatment. However, it is crucial to address the ethical and privacy concerns associated with AI to ensure that it is used responsibly and for the greater good of society.

The Impact of Artificial Intelligence on Transportation

Artificial intelligence (AI) has had a significant impact on society in many different areas, and one of the fields that has benefited greatly from AI technology is transportation. With advances in AI, transportation systems have become more efficient, safer, and more environmentally friendly.

Improved Safety

One of the key impacts of AI on transportation is the improved safety of both passengers and drivers. AI technology has enabled the development of autonomous vehicles, which can operate without human intervention. These vehicles use AI algorithms and sensors to navigate roads, avoiding accidents and minimizing collisions. By removing the human element from driving, the risk of human error and accidents caused by fatigue, distraction, or impaired judgment can be significantly reduced.

Efficient Traffic Management

AI has also revolutionized traffic management systems, leading to more efficient transportation networks. Intelligent traffic lights, for example, can use AI algorithms to adjust signal timings based on real-time traffic conditions, optimizing traffic flow and reducing congestion. AI-powered algorithms can analyze large amounts of data from various sources, such as traffic cameras and sensors, to provide accurate predictions and recommendations for traffic management and planning.

Enhanced Logistics and Delivery

AI has significantly impacted the logistics and delivery industry. AI-powered software can optimize route planning for delivery vehicles, taking into account factors such as traffic conditions, weather, and delivery time windows. This improves efficiency and reduces costs by minimizing fuel consumption and maximizing the number of deliveries per trip. Additionally, AI can also assist in package sorting and tracking, enhancing the overall speed and accuracy of the delivery process.

The impact of AI on transportation is continuously evolving, with ongoing research and development leading to even more advanced applications. As AI technology continues to improve, we can expect transportation systems to become even safer, more efficient, and more sustainable.

The Impact of Artificial Intelligence on Communication

Artificial intelligence has had a profound impact on society, affecting various aspects of our lives. One area where its influence can be seen is in communication. The advancements in artificial intelligence have revolutionized the way we communicate with each other.

One of the main impacts of artificial intelligence on communication is the development of chatbots. These computer programs are designed to simulate human conversation and interact with users through messaging systems. Chatbots have become increasingly popular in customer service, providing quick and automated responses to customer inquiries. They are available 24/7, ensuring constant support and improving customer satisfaction.

Moreover, artificial intelligence has contributed to the improvement of language translation. Translation tools powered by AI technology have made it easier for people to communicate across languages and cultures. These tools can instantly translate text and speech, enabling effective communication in real-time. They have bridged the language barrier and facilitated global collaboration and understanding.

Another impact of artificial intelligence on communication is the emergence of voice assistants. These virtual assistants, such as Siri and Alexa, use natural language processing and machine learning algorithms to understand and respond to user commands. Voice assistants have become integral parts of our daily lives, helping us perform various tasks, from setting reminders to controlling smart home devices. They have transformed the way we interact with technology and simplified communication with devices.

Artificial intelligence has also played a role in enhancing communication through personalized recommendations. Many online platforms, such as social media and streaming services, utilize AI algorithms to analyze user preferences and provide personalized content suggestions. This has improved user engagement and facilitated communication by connecting users with relevant information and like-minded individuals.

In conclusion, artificial intelligence has had a significant impact on communication. From chatbots and language translation to voice assistants and personalized recommendations, AI technology has revolutionized the way we interact and communicate with each other. It has made communication faster, more efficient, and more accessible, bringing people closer together in an increasingly interconnected world.

The Impact of Artificial Intelligence on Privacy

Artificial intelligence (AI) has had a profound impact on various aspects of our society, and one area that is greatly affected is privacy. With the advancements in AI technology, there are growing concerns about how it can impact our privacy rights.

AI-powered systems have the ability to collect and analyze vast amounts of personal data, ranging from social media activity to online transactions. This presents significant challenges when it comes to protecting our privacy. For instance, AI algorithms can mine and analyze our personal data to generate targeted advertisements, which can result in intrusion into our personal lives.

Additionally, AI systems can be used to monitor and track individuals’ online activities, which raises concerns about surveillance and the erosion of privacy. With AI’s ability to process and interpret large volumes of data, it becomes easier for organizations and governments to gather information about individuals without their knowledge or consent.

Furthermore, AI algorithms can make predictions about individuals’ behaviors and preferences based on their data. While this can be beneficial in some cases, such as providing tailored recommendations, it also raises concerns about the potential misuse of this information. For example, insurance companies could use AI algorithms to assess an individual’s health risks based on their online activity, resulting in potential discrimination or exclusion.

It is crucial to strike a balance between the benefits of AI technology and protecting individuals’ right to privacy. Steps must be taken to ensure that AI systems are designed and implemented in a way that respects and safeguards privacy. This can include implementing strict regulations and guidelines for data collection, storage, and usage.

In conclusion, the impact of artificial intelligence on privacy cannot be ignored. As AI continues to advance, it is essential to address the potential risks and challenges it poses to privacy rights. By taking proactive measures and promoting ethical practices, we can harness the benefits of AI while ensuring that individuals’ privacy is respected and protected.

The Impact of Artificial Intelligence on Security

Artificial intelligence (AI) has had a profound impact on society, and one area where its influence is particularly noticeable is in the field of security. The development and implementation of AI technology have revolutionized the way we approach and manage security threats.

AI-powered security systems have proven to be highly effective in detecting and preventing various types of threats, such as cyber attacks, terrorism, and physical breaches. These systems are capable of analyzing vast amounts of data in real-time, identifying patterns, and recognizing anomalies that may indicate a security risk.

One major advantage of AI in security is its ability to continuously adapt and learn. AI algorithms can quickly analyze new data and update their knowledge base, improving their ability to detect and respond to emerging threats. This dynamic nature allows AI-powered security systems to stay ahead of potential attackers and respond to evolving security challenges.

Furthermore, AI can enhance the efficiency and accuracy of security operations. By automating certain tasks, such as video surveillance monitoring and threat analysis, AI technology can significantly reduce the workload for human security personnel. This frees up resources and enables security teams to focus on more critical tasks, such as responding to incidents and developing proactive security strategies.

However, the increasing reliance on AI in security also raises concerns. The use of AI technology can potentially lead to privacy breaches and unethical surveillance practices. It is crucial to strike a balance between utilizing AI for security purposes and respecting individual privacy rights.

In conclusion, the impact of artificial intelligence on security has been significant. AI-powered systems have revolutionized the way we detect and prevent security threats, enhancing efficiency and accuracy in security operations. However, ethical concerns need to be addressed to ensure that AI is used responsibly and in a way that respects individual rights and privacy.

The Impact of Artificial Intelligence on Economy

Artificial intelligence (AI) is revolutionizing the economy in various ways. Its impact is prevalent across different sectors, leading to both opportunities and challenges.

One of the key benefits of AI in the economy is increased productivity. AI-powered systems and algorithms can perform tasks at a much faster pace and with a higher level of accuracy compared to humans. This efficiency can lead to significant cost savings for businesses and result in increased output and profits.

Moreover, AI has the potential to create new job opportunities. While some jobs may be replaced by automation, AI also leads to the creation of new roles that require specialized skills in managing and maintaining AI systems. This can contribute to economic growth and provide employment opportunities for individuals with the necessary technical expertise.

The impact of AI on the economy is not limited to individual businesses or sectors. It has the potential to transform entire industries. For example, AI-powered technologies can optimize supply chain operations, enhance customer experience, and improve decision-making processes. These advancements can lead to increased competitiveness, improved efficiency, and overall economic growth.

However, the widespread implementation of AI also brings challenges. The displacement of jobs due to automation can result in unemployment and income inequality. It is crucial for policymakers to address these issues and ensure that the benefits of AI are distributed equitably across society.

Additionally, the ethical implications of AI in the economy must be considered. As AI systems continue to advance, it raises questions about privacy, data security, and algorithmic bias. Safeguards and regulations need to be in place to protect individuals’ rights and prevent any potential harm caused by AI applications.

In conclusion, the impact of artificial intelligence on the economy is significant. It offers opportunities for increased productivity, job creation, and industry transformation. However, it also poses challenges such as job displacement and ethical concerns. To fully harness the potential of AI in the economy, policymakers and stakeholders must work together to address these challenges and ensure a balanced and inclusive approach to its implementation.

The Impact of Artificial Intelligence on Entertainment

Artificial intelligence is revolutionizing the entertainment industry, transforming the way we consume and experience various forms of media. With its ability to analyze massive amounts of data, AI has the potential to enhance entertainment in numerous ways.

One area where AI is making a significant impact is in content creation. AI algorithms can generate music, art, and even scripts for movies and TV shows. By analyzing patterns and trends in existing content, AI can create new and original pieces that appeal to different audiences. This not only increases the diversity of entertainment options but also reduces the time and effort required for human creators.

AI also plays a crucial role in enhancing the user experience in the entertainment industry. For example, AI-powered recommendation engines can suggest relevant movies, TV shows, or songs based on individual preferences and viewing habits. This personalized approach ensures that users discover content that aligns with their interests, leading to a more enjoyable and engaging entertainment experience.

In the gaming industry, AI is transforming the way games are developed and played. AI algorithms can create lifelike characters and virtual worlds, providing players with immersive and realistic experiences. Additionally, AI-powered game assistants can adapt to the player’s skill level and offer personalized guidance, making games more accessible and enjoyable for players of all abilities.

Furthermore, AI is revolutionizing the way we consume live events, such as sports or concerts. AI-powered cameras and sensors can capture and analyze data in real-time, providing enhanced viewing experiences for spectators. This includes features like instant replays, personalized camera angles, and in-depth statistics. AI can also generate virtual crowds or even simulate the experience of attending a live event, bringing the excitement of the event to a global audience.

The impact of artificial intelligence on the entertainment industry is undeniable. It is transforming content creation, enhancing the user experience, and revolutionizing the way we consume various forms of media. As AI continues to advance, we can expect even more innovative and immersive entertainment experiences that cater to individual preferences and push the boundaries of creativity.

The Impact of Artificial Intelligence on Human Interaction

In today’s modern world, the rise of artificial intelligence (AI) has had a profound impact on many aspects of society, including human interaction. AI technology has revolutionized the way we communicate and interact with one another, both online and offline.

One of the most noticeable impacts of AI on human interaction is in the realm of communication. AI-powered chatbots and virtual assistants have become increasingly common, allowing people to interact with machines in a more natural and intuitive way. Whether it’s using voice commands to control smart home devices or chatting with a virtual assistant to get information, AI has made it easier to communicate with technology.

AI has also had a significant impact on social media and online communication platforms. Social media algorithms use AI to analyze user data and tailor content to individual preferences, which can shape the way we interact with each other online. This can lead to both positive and negative effects, as AI algorithms may reinforce existing beliefs and create echo chambers, but they can also expose us to new ideas and perspectives.

Furthermore, AI technology has the potential to enhance human interaction by augmenting our capabilities. For example, AI-powered translation tools can break down language barriers and facilitate communication between people who speak different languages. This can foster cross-cultural understanding and enable collaboration on a global scale.

On the other hand, there are concerns about the potential negative impact of AI on human interaction. Some argue that the increasing reliance on AI technology for communication could lead to a decline in human social skills. As people become more accustomed to interacting with machines, they may struggle to engage in authentic face-to-face interactions.

Despite these concerns, it is clear that AI has had a profound impact on human interaction. From enhancing communication to breaking down language barriers, AI technology has transformed the way we interact with one another. It is crucial to continue monitoring and studying the impact of AI on human interaction to ensure we strike a balance between technological advancement and preserving our social connections.

The Role of Artificial Intelligence in Scientific Research

Artificial intelligence (AI) has had a significant impact on society in various fields, and one area where it has shown great promise is scientific research. The use of AI in scientific research has revolutionized the way experiments are conducted, data is analyzed, and conclusions are drawn.

Improving Experimental Design and Data Collection

One of the key contributions of AI in scientific research is its ability to improve experimental design and data collection. By utilizing machine learning algorithms, AI systems can analyze massive amounts of data and identify patterns, allowing researchers to optimize their experimental approaches and make more informed decisions. This not only saves time and resources but also increases the accuracy and reliability of scientific findings.

Enhancing Data Analysis and Interpretation

Another crucial role of AI in scientific research is its ability to enhance data analysis and interpretation. Traditional data analysis methods can be time-consuming and subjective, leading to potential biases. However, AI systems can process vast amounts of data quickly and objectively, revealing hidden relationships, trends, and insights that may be missed by human researchers. This enables scientists to extract meaningful information from complex datasets, leading to more accurate and comprehensive conclusions.

While AI has significant potential in scientific research, it also presents challenges and ethical considerations that need to be addressed. Privacy and security concerns, biases in AI algorithms, ethical implications of AI decision-making, and the impact on human researchers’ roles are some of the critical issues that require scrutiny.

In conclusion, the role of artificial intelligence in scientific research is undeniable. AI has the potential to revolutionize how experiments are designed, data is analyzed, and conclusions are drawn. By improving experimental design and data collection, enhancing data analysis and interpretation, and accelerating scientific discovery, AI can significantly contribute to the advancement of scientific knowledge and its impact on society as a whole.

The Role of Artificial Intelligence in Space Exploration

Artificial intelligence (AI) has had a significant impact on various fields and industries, and space exploration is no exception. With its ability to analyze vast amounts of data and make decisions quickly, AI has revolutionized the way we explore space and gather information about the universe.

One of the primary roles of artificial intelligence in space exploration is in the analysis of data collected by space probes and telescopes. These devices capture enormous amounts of data that can often be overwhelming for human scientists to process. AI algorithms can sift through this data, identifying patterns, and extracting valuable insights that humans may not have noticed.

Additionally, AI plays a crucial role in autonomous navigation and spacecraft control. Spacecraft can be sent to explore distant planets and moons in our solar system, and AI-powered systems can ensure their safe and efficient navigation through unknown terrain. AI algorithms can analyze data from onboard sensors and make real-time decisions to avoid obstacles and hazards.

Benefits of AI in space exploration

• Efficiency: AI systems can process vast amounts of data much faster than humans, allowing for quicker analysis and decision-making.
• Exploration of inhospitable environments: AI-powered robots can be sent to explore extreme environments, such as the surface of Mars or the icy moons of Jupiter, where it would be challenging for humans to survive.
• Cost reduction: By using AI to automate certain tasks, space exploration missions can become more cost-effective and efficient.

The impact of artificial intelligence on space exploration is still in its early stages, but its potential is vast. As AI technology continues to advance, we can expect to see even more significant contributions to our understanding of the universe and our ability to explore it.

The Role of Artificial Intelligence in Environmental Conservation

Artificial intelligence (AI) has the potential to revolutionize various aspects of society, and environmental conservation is no exception. With the growing concern about climate change and the need to preserve the planet’s resources, AI can play a crucial role in helping us address these challenges.

Monitoring and Predicting Environmental Changes

One of the key benefits of AI in environmental conservation is its ability to monitor and predict environmental changes. Through the use of sensors and data analysis, AI systems can gather and analyze vast amounts of information about the environment, including temperature, air quality, and water levels.

This data can then be used to identify patterns and trends, allowing scientists to make predictions about future changes. For example, AI can help predict the spread of wildfires or the impact of deforestation in certain areas. By understanding these threats in advance, we can take proactive measures to protect our natural resources.

Optimizing Resource Management

Another important role of AI in environmental conservation is optimizing resource management. By using AI algorithms, we can efficiently allocate resources such as energy, water, and waste management.

AI can analyze data from various sources, such as smart meters and sensors, to understand patterns of resource usage. This information can then be used to develop strategies for more sustainable resource management, reducing waste and improving efficiency.

For example, AI can help optimize energy consumption in buildings by analyzing data from smart thermostats and occupancy sensors. It can identify usage patterns and make adjustments to reduce energy waste, saving both money and environmental resources.

Supporting Conservation Efforts

AI can also support conservation efforts through various applications. One example is the use of AI-powered drones and satellite imagery to monitor and protect endangered species.

By analyzing images and data collected by these technologies, AI algorithms can identify and track animals, detect illegal activities such as poaching, and even help with habitat restoration. This technology can greatly enhance the effectiveness and efficiency of conservation efforts, allowing us to better protect our biodiversity.

In conclusion, artificial intelligence has a significant role to play in environmental conservation. From monitoring and predicting environmental changes to optimizing resource management and supporting conservation efforts, AI can provide valuable insights and help us make more informed decisions. By harnessing the power of AI, we can work towards a more sustainable and environmentally conscious society.

The Role of Artificial Intelligence in Manufacturing

Artificial intelligence (AI) has had a profound impact on society in various fields, and manufacturing is no exception. In this essay, we will explore the role of AI in manufacturing and how it has revolutionized the industry.

AI has transformed the manufacturing process by introducing automation and machine learning techniques. With AI, machines can perform tasks that were previously done by humans, leading to increased efficiency and productivity. This has allowed manufacturers to streamline their operations and produce goods at a faster rate.

One of the key benefits of AI in manufacturing is its ability to analyze large amounts of data. Through machine learning algorithms, AI systems can collect and process data from various sources, such as sensors and machines, to identify patterns and make informed decisions. This allows manufacturers to optimize their production processes and minimize errors.

Furthermore, AI can improve product quality and reduce defects. By analyzing data in real-time, AI systems can detect anomalies and deviations from the norm, allowing manufacturers to identify and address issues before they escalate. This not only saves time and costs but also ensures that consumers receive high-quality products.

Additionally, AI has enabled the development of predictive maintenance systems. By analyzing data from machines and equipment, AI can anticipate and prevent failures before they occur. This proactive approach minimizes downtime, reduces maintenance costs, and extends the lifespan of machinery.

Overall, the role of AI in manufacturing is transformative. It empowers manufacturers to optimize their processes, improve product quality, and reduce costs. However, it is important to note that AI is not a replacement for humans in the manufacturing industry. Instead, it complements human skills and expertise, allowing workers to focus on more complex tasks while AI handles repetitive and mundane tasks.

In conclusion, artificial intelligence has had a significant impact on the manufacturing industry. It has revolutionized processes, improved product quality, and increased productivity. As AI continues to advance, we can expect even more transformative changes in the manufacturing sector.

The Role of Artificial Intelligence in Agriculture

Artificial intelligence has had a profound impact on society in various fields, and agriculture is no exception. With the advancements in technology, AI has the potential to revolutionize the agricultural industry, making it more efficient, sustainable, and productive.

One of the key areas where AI can play a significant role in agriculture is in crop management. AI-powered systems can analyze vast amounts of data, such as weather patterns, soil conditions, and crop health, to provide farmers with valuable insights. This allows farmers to make more informed decisions on irrigation, fertilization, and pest control, leading to optimal crop yields and reduced resource waste.

Moreover, AI can also aid in the early detection and prevention of crop diseases. By using machine learning algorithms, AI systems can identify patterns and anomalies in plant health, indicating the presence of diseases or pests. This enables farmers to take timely action, prevent the spread of diseases, and minimize crop losses.

Another area where AI can contribute to agriculture is in the realm of precision farming. By combining AI with other technologies like drones and sensors, farmers can gather precise and real-time data about their crops and fields. This data can then be used to create detailed maps, monitor crop growth, and optimize resource allocation. Whether it’s optimizing water usage or determining the ideal time for harvesting, AI can help farmers make data-driven decisions that maximize productivity while minimizing environmental impact.

Furthermore, AI can enhance livestock management. With AI-powered systems, farmers can monitor the health and behavior of their livestock, detect diseases or anomalies, and provide personalized care. This not only improves animal welfare but also increases the efficiency of livestock production.

In conclusion, artificial intelligence has a crucial role to play in the agricultural sector. From crop management to livestock monitoring, AI can bring numerous benefits to farmers, leading to increased productivity, sustainability, and overall growth. As AI continues to advance, we can expect further innovations and improvements in the integration of AI in agriculture, shaping the future of food production.

The Role of Artificial Intelligence in Finance

Artificial intelligence (AI) has had a significant impact on society, revolutionizing various industries, and finance is no exception. In this essay, we will explore the role of AI in the financial sector and its implications.

The use of AI has transformed numerous aspects of finance, from trading and investment to risk management and fraud detection. One of the key benefits of AI in finance is its ability to process vast amounts of data in real-time. This enables more accurate predictions and informed decision-making, giving financial institutions a competitive edge.

AI-powered algorithms have become vital tools for traders and investors. These algorithms analyze market trends, historical data, and other factors to identify patterns and make investment recommendations. By leveraging AI, financial professionals can make more informed decisions and optimize their portfolios.

Furthermore, AI plays a crucial role in risk management. Traditional risk models often fall short in assessing complex and evolving risks, making it challenging to mitigate them effectively. AI, with its machine learning capabilities, can enhance risk assessment by analyzing a wide range of variables and identifying potential threats. This helps financial institutions proactively manage risks and minimize losses.

Another area where AI has made significant strides in finance is fraud detection. With the increasing sophistication of fraudulent activities, traditional rule-based systems struggle to keep up. AI, on the other hand, can detect anomalies and unusual patterns by leveraging machine learning algorithms that constantly learn and adapt. This enables faster and more accurate detection of fraudulent transactions, protecting both financial institutions and their customers.

In conclusion, AI has had a profound impact on the finance industry and has revolutionized various aspects of it. The ability to process large amounts of data, make informed decisions, and detect risks and frauds more effectively has made AI an invaluable tool. As technology continues to advance, we can expect AI to play an even greater role in shaping the future of finance.

The Role of Artificial Intelligence in Customer Service

Artificial intelligence has had a profound impact on various industries, and one area where its influence is increasingly being felt is customer service. AI technology is transforming how businesses interact with their customers, providing enhanced communication and support.

One of the main benefits of AI in customer service is its ability to provide instant and personalized responses to customer inquiries. Through the use of chatbots and virtual assistants, businesses can now offer round-the-clock support, ensuring that customers receive the assistance they need, no matter the time of day.

Furthermore, AI-powered customer service can analyze vast amounts of data to gain insights into customer preferences and behavior. This information can then be used to tailor interactions and improve customer experiences. By understanding customer needs better, businesses can provide more relevant and targeted solutions, leading to increased customer satisfaction and loyalty.

Another crucial role of AI in customer service is its ability to automate repetitive tasks and processes. AI-powered systems can handle routine tasks such as order tracking, appointment scheduling, and basic troubleshooting, freeing up human agents to focus on more complex issues. This results in increased efficiency and productivity, as well as faster response times.

However, it’s important to note that AI should not replace human interaction entirely. While AI can handle routine tasks effectively, there are situations where human empathy and judgment are essential. Building a balance between AI and human involvement is crucial to ensure the best possible customer service experience.

In conclusion, artificial intelligence is revolutionizing customer service by providing instant and personalized support, analyzing customer data for improved experiences, and automating repetitive tasks. While AI offers numerous benefits, it is vital to strike a balance between AI and human interaction to deliver exceptional customer service in the digital age.

The Role of Artificial Intelligence in Gaming

Gaming has been greatly impacted by the advancements in artificial intelligence (AI). AI has revolutionized the way games are created, played, and experienced by both developers and players.

One of the key roles that AI plays in gaming is in creating realistic and challenging virtual opponents. AI algorithms can be programmed to assess player actions and adjust the difficulty level accordingly. This allows for a more immersive and engaging gaming experience, as players can compete against opponents that adapt to their skills and strategies.

Moreover, AI is also used in game design to create intelligent non-player characters (NPCs) that can interact with players in a more natural and realistic manner. These NPCs can simulate human-like behavior and responses, making the game world feel more alive and dynamic.

Another important role of AI in gaming is in improving game mechanics and gameplay. AI algorithms can analyze player data and preferences to provide personalized recommendations and suggestions. This helps players discover new games, unlock achievements, and improve their overall gaming experience.

Furthermore, AI has also been used in game testing and bug detection. AI algorithms can simulate various scenarios and interactions to identify potential glitches and bugs. This improves the overall quality and stability of games before their release.

In conclusion, artificial intelligence has had a profound impact on the gaming industry. It has enhanced the realism, challenge, and overall experience of games. The role of AI in gaming is ever-evolving, and it will continue to shape the future of the gaming industry.

The Future of Artificial Intelligence

Artificial intelligence (AI) has already made a significant impact on society, and its role is only expected to grow in the future. As advancements in technology continue to push boundaries, the potential applications of AI are expanding, potentially transforming various industries and aspects of our daily lives.

One of the most prominent areas where AI is expected to make a difference is in autonomous vehicles. Self-driving cars have already become a reality, and AI is set to play a crucial role in improving their capabilities further. With AI-powered sensors and algorithms, autonomous vehicles can navigate complex road conditions, reduce traffic congestion, and even enhance road safety.

Another domain that is likely to benefit from AI is healthcare. Intelligent machines can analyze vast amounts of medical data and assist doctors in making accurate diagnoses. This can lead to faster identification of diseases, more effective treatment plans, and ultimately, better patient outcomes. AI can also aid in the development of new drugs and therapies by analyzing genetic information and identifying potential targets for treatment.

In addition to healthcare and transportation, AI has the potential to revolutionize sectors such as finance, manufacturing, and agriculture. AI algorithms can analyze market data, identify trends, and make accurate predictions, enabling financial institutions to make informed investment decisions. In manufacturing, AI-powered robots can perform repetitive tasks with precision and efficiency, improving productivity and reducing costs. AI can also optimize crop production by analyzing variables such as weather conditions, soil quality, and crop health, leading to increased yields and more sustainable farming practices.

However, with the increasing integration of AI into various aspects of society, ethical considerations become crucial. As AI becomes more advanced and autonomous, questions arise about the implications of AI decision-making processes and potential biases. It is important to ensure that AI systems are designed and regulated in a way that prioritizes fairness, transparency, and accountability.

In conclusion, the future of artificial intelligence holds immense potential for transforming society in numerous ways. From autonomous vehicles and healthcare to finance and agriculture, AI is poised to revolutionize various sectors and improve our lives. However, it is essential to address ethical concerns and ensure responsible development and deployment of AI technology to maximize its positive impact on society.

The Potential Risks of Artificial Intelligence

As the impact of artificial intelligence on society continues to grow, it is important to consider the potential risks associated with this rapidly advancing technology. While intelligence can be a powerful tool for improving society, artificial intelligence poses unique challenges and dangers that must be addressed.

Unemployment and Job Displacement

One of the major concerns surrounding artificial intelligence is the potential for widespread unemployment and job displacement. As AI technology advances, machines and algorithms are becoming increasingly capable of performing tasks that were previously done by humans. This could lead to significant job losses across various industries, particularly those that rely heavily on manual labor or repetitive tasks.

Additionally, as AI systems become more sophisticated, there is a possibility that they could replace jobs that require higher levels of skill and expertise. This could result in a significant shift in the job market and create challenges for workers who are unable to adapt to these changes.

Ethical Concerns

Another potential risk of artificial intelligence is the ethical concerns that arise from its use. AI systems are designed to make decisions and take actions based on data and algorithms, but they may not always make ethical choices. This raises questions about the impact of AI on issues such as privacy, bias, and discrimination.

For example, AI algorithms may inadvertently discriminate against certain groups of people if the data used to train them is biased. This could lead to unfair outcomes in areas such as hiring, lending, and law enforcement. It is essential to address these ethical concerns and ensure that AI systems are developed and used in a responsible and equitable manner.

In conclusion, while artificial intelligence has the potential to greatly benefit society, it is important to carefully consider and address the potential risks associated with its use. Unemployment and job displacement, as well as ethical concerns, are significant challenges that must be navigated to ensure the responsible and equitable development of AI.

The Importance of Ethical Guidelines for Artificial Intelligence

As artificial intelligence (AI) continues to advance at an unprecedented pace, its impact on society becomes increasingly profound. AI has the potential to transform various industries, improve efficiency, and enhance our overall quality of life. However, with this power comes great responsibility. It is crucial to establish ethical guidelines to ensure that AI is developed and deployed in a responsible and beneficial manner.

Ethics in AI Development

Ethics play a vital role in the development of AI technology. It is essential for developers to consider the potential impact that their creations may have on society. This involves addressing questions of privacy, security, and bias. AI systems should be designed to respect fundamental human rights and ensure that they do not discriminate against certain groups of people. By setting ethical standards, we can prevent the misuse and abuse of AI technology.

The Impact on Society

Without ethical guidelines, artificial intelligence can have unintended consequences on society. For example, if AI algorithms are biased, they may perpetuate social inequalities or reinforce stereotypes. Additionally, AI systems that invade privacy or compromise security can erode trust in technology, hindering its adoption and acceptance by the public. Therefore, by implementing ethical guidelines, we can help safeguard against these negative societal impacts.

The Risks of AI without Ethical Guidelines

Artificial intelligence has the potential to revolutionize society, but it also carries risks. Without ethical guidelines in place, AI can be misused for nefarious purposes, such as surveillance and manipulation. It is crucial to establish clear boundaries and regulations to ensure that AI is used for the benefit of humanity and not to harm individuals or society as a whole.

In conclusion , the importance of ethical guidelines for artificial intelligence cannot be overstated. These guidelines serve as a compass to steer the development and deployment of AI technology in the right direction. By considering the potential impact on society and setting ethical standards, we can harness the power of AI for the betterment of humanity and create a future that is both technologically advanced and ethically responsible.

The Need for Regulation and Governance of Artificial Intelligence

The rapid development of artificial intelligence (AI) has had a profound impact on society. With the increasing deployment of intelligent systems in various domains, it is essential to establish effective regulations and governance mechanisms to ensure that AI is used responsibly and ethically.

Safeguarding Privacy and Data Security

One of the key concerns with the growing use of AI is the potential invasion of privacy and compromise of data security. Intelligent systems are capable of analyzing vast amounts of personal data, raising concerns about the misuse and unauthorized access to sensitive information. To address this, there is a need for regulations that enforce stringent data protection measures and ensure transparency in AI algorithms and data usage.

Ethical Decision-Making and Bias Mitigation

AI systems are designed to make autonomous decisions based on data and algorithms. However, the biases embedded in these systems can result in discriminatory outcomes. Regulations must be put in place to ensure that AI systems are developed and trained in a way that mitigates bias and promotes fair and ethical decision-making. This includes diverse representation in the development of AI technologies and the establishment of clear guidelines on what is considered acceptable behavior for AI systems.

Accountability and Liability

As AI systems become increasingly autonomous, it becomes crucial to determine who should be held accountable in the event of a malfunction or failure. Clear regulations need to be established to define liability in AI-related incidents and ensure that there are mechanisms in place to address any potential harm caused by AI systems. This includes the establishment of standards for testing and certification of AI systems to ensure their reliability and safety.

In conclusion, the impact of artificial intelligence on society necessitates the establishment of regulations and governance mechanisms. By addressing concerns related to privacy, bias, and accountability, we can harness the full potential of AI while ensuring that it benefits society as a whole.

The Role of Artificial Intelligence in Shaping Society’s Future

Artificial intelligence (AI) has had a profound impact on society, and its role in shaping the future cannot be understated. As technology continues to advance at an unprecedented rate, AI is becoming increasingly integrated into various aspects of our lives, from healthcare to transportation to entertainment.

One of the key impacts of AI is its ability to automate tasks that were once performed by humans, enabling us to save time and resources. For example, AI-powered chatbots have revolutionized customer service by providing prompt and efficient responses to inquiries, reducing the need for human intervention. In the healthcare industry, AI algorithms are being developed to assist doctors in diagnosing diseases and recommending treatment options, improving both accuracy and speed.

Furthermore, AI has the potential to address complex societal challenges. For instance, in the field of environmental sustainability, AI technologies can be used to optimize energy consumption, reduce waste, and develop renewable energy sources. By analyzing large amounts of data and identifying patterns, AI can help us make more informed decisions and take proactive measures to mitigate the impact of climate change.

In addition, AI has the ability to enhance our educational systems. Intelligent tutoring systems can adapt to individual learning styles and provide personalized instruction, improving student engagement and performance. AI-powered language translation tools have also facilitated global communication, breaking down language barriers and fostering cross-cultural understanding.

However, it is important to recognize that AI is not without its challenges. There are concerns regarding privacy and security, as AI relies heavily on data collection and analysis. Ethical considerations must also be taken into account, as AI systems can perpetuate biases and discrimination if not properly designed and monitored.

In conclusion, artificial intelligence plays a significant role in shaping society’s future. Its impact can be seen in various fields, from automation to sustainability to education. While there are challenges that need to be addressed, AI has the potential to revolutionize our lives and create a more efficient and equitable society.

Questions and answers

What is the impact of artificial intelligence on society.

The impact of artificial intelligence on society is significant and far-reaching. It is transforming various sectors, including healthcare, education, finance, and transportation.

How is artificial intelligence revolutionizing healthcare?

Artificial intelligence in healthcare is revolutionizing the way diseases are diagnosed and treated. It is helping doctors in making accurate diagnoses, predicting outcomes, and assisting in surgeries.

What are the ethical concerns surrounding artificial intelligence?

There are several ethical concerns surrounding artificial intelligence, such as the potential loss of jobs, bias in algorithms, invasion of privacy, and the possibility of autonomous weapons.

How can artificial intelligence improve productivity in the workplace?

Artificial intelligence can improve productivity in the workplace by automating repetitive tasks, analyzing large amounts of data quickly and accurately, and providing personalized recommendations and insights.

What are the potential risks of artificial intelligence?

The potential risks of artificial intelligence include job displacement, widening economic inequalities, security threats, loss of human control, and the potential for AI systems to be hacked or manipulated.

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Artificial Intelligence, Its Benefits & Risks Essay

Introduction, artificial intelligence and people’s lives, interesting things about artificial intelligence, the future of artificial intelligence, works cited.

Artificial intelligence (AI) revolves around the idea that human intellect can be replicated in machines. Technological advancements have made it possible for experts to manufacture machines, which can discharge many activities that require reasoning without human intervention. Many studies have been conducted to examine the field of artificial intelligence. As this paper reveals, AI-related topics that have received significant scholarly attention include the impact it has on people’s lives, some of its interesting features, and the future of business operations, thanks to the application of artificial intelligence.

According to Makridakis, “The goal of artificial intelligence includes learning, reasoning, and perception, and machines are wired using a cross-disciplinary approach based on mathematics, computer science, linguistics, and psychology” (49). Artificial intelligence has significant impacts on our lives. This technology influences the buying behaviors of many customers, particularly those who like watching movies. Companies like Netflix have invested heavily in artificial intelligence intending to gather information regarding consumers’ interests.

Data gathered is used to target individual customers depending on their tastes and preferences (Makridakis 55). For instance, after streaming a movie or series, one may be surprised to see their screen filled with images that promote other shows or videos. In most cases, these films fall in the same genre as the one they have just completed viewing. Such incidents do not happen by coincidence. Companies use artificial intelligence to persuade people to stream more videos or buy specific products and services.

Artificial intelligence is also used in the transportation sector. Taxi companies such as Uber use applications that are equipped with machine learning, which is a component of artificial intelligence (Dirican 568). It would have been hard for Uber to achieve its goal of dominating the ride-sharing market without using this technology. Machine learning enables taxi businesses to identify falsified accounts and determine the most favorable points to pick or drop clients.

One of the most fascinating things about artificial intelligence is that virtually all artificial intelligence assistants respond in feminine voices. For instance, AI machines such as Cortana, Siri, and Alexa are all female. The primary reason they are feminine is that most people prefer female assistants. Another interesting thing about artificial intelligence is that characters can write. Today, robo-journalism is gaining popularity in the media industry. Los Angeles Times prides itself on being the first company to use a robot to compose an editorial about earthquakes in California (Makridakis 58). Despite these numerous benefits attributable to artificial intelligence, some tech companies have doubts about the technology. For example, Tesla’s chief executive officer, Elon Musk, is renowned for his love for advanced technology. However, he shares his skepticism regarding artificial intelligence. Musk argues that artificial intelligence may pose a threat to humanity and hence the need for a level of control. He advocates for the abolishment of the manufacture of automated weapons.

Many customer care professionals are losing jobs. Their positions are being taken over by artificial intelligence. Studies show that over 85% of consumer relationships involve artificial intelligence-aided robots (Dirican 571). Hence, in the future, technology will dominate the personal assistant career, thus rendering many people jobless. The demand for self-driving cars is growing. Artificial intelligence is expected to feature in the automobile industry since many companies are looking forward to producing automated cars.

Artificial intelligence has infiltrated our lives in various ways. Companies leverage this technology to influence consumers’ buying behaviors. Additionally, businesses are gradually using AI to automate professions, a move that has made many people jobless. Even though this technology is useful, there is the need to regulate its utilization before it becomes a threat to humanity.

Dirican, Cuneyt. “The Impacts of Robotics, Artificial Intelligence on Business and Economics.” Procedia – Social and Behavioral Sciences , vol. 195, no. 1, 2015, pp. 564-573.

Makridakis, Spyros. “The Forthcoming Artificial Intelligence (AI) Revolution: Its Impact on Society and Firms.” Futures , vol. 90, no. 1, 2017, pp. 46-60.

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Guest Essay

Press Pause on the Silicon Valley Hype Machine

By Julia Angwin

Ms. Angwin is a contributing Opinion writer and an investigative journalist.

It’s a little hard to believe that just over a year ago, a group of leading researchers asked for a six-month pause in the development of larger systems of artificial intelligence, fearing that the systems would become too powerful. “Should we risk loss of control of our civilization?” they asked.

There was no pause. But now, a year later, the question isn’t really whether A.I. is too smart and will take over the world. It’s whether A.I. is too stupid and unreliable to be useful. Consider this week’s announcement from OpenAI’s chief executive, Sam Altman, who promised he would unveil “new stuff” that “ feels like magic to me.” But it was just a rather routine update that makes ChatGPT cheaper and faster .

It feels like another sign that A.I. is not even close to living up to its hype. In my eyes, it’s looking less like an all-powerful being and more like a bad intern whose work is so unreliable that it’s often easier to do the task yourself. That realization has real implications for the way we, our employers and our government should deal with Silicon Valley’s latest dazzling new, new thing. Acknowledging A.I.’s flaws could help us invest our resources more efficiently and also allow us to turn our attention toward more realistic solutions.

Others voice similar concerns. “I find my feelings about A.I. are actually pretty similar to my feelings about blockchains: They do a poor job of much of what people try to do with them, they can’t do the things their creators claim they one day might, and many of the things they are well suited to do may not be altogether that beneficial,” wrote Molly White, a cryptocurrency researcher and critic , in her newsletter last month.

Let’s look at the research.

In the past 10 years, A.I. has conquered many tasks that were previously unimaginable, such as successfully identifying images, writing complete coherent sentences and transcribing audio. A.I. enabled a singer who had lost his voice to release a new song using A.I. trained with clips from his old songs.

But some of A.I.’s greatest accomplishments seem inflated. Some of you may remember that the A.I. model ChatGPT-4 aced the uniform bar exam a year ago. Turns out that it scored in the 48th percentile, not the 90th, as claimed by OpenAI , according to a re-examination by the M.I.T. researcher Eric Martínez . Or what about Google’s claim that it used A.I. to discover more than two million new chemical compounds ? A re-examination by experimental materials chemists at the University of California, Santa Barbara, found “ scant evidence for compounds that fulfill the trifecta of novelty, credibility and utility .”

Meanwhile, researchers in many fields have found that A.I. often struggles to answer even simple questions, whether about the law , medicine or voter information . Researchers have even found that A.I. does not always improve the quality of computer programming , the task it is supposed to excel at.

I don’t think we’re in cryptocurrency territory, where the hype turned out to be a cover story for a number of illegal schemes that landed a few big names in prison . But it’s also pretty clear that we’re a long way from Mr. Altman’s promise that A.I. will become “ the most powerful technology humanity has yet invented .”

Take Devin, a recently released “ A.I. software engineer ” that was breathlessly touted by the tech press. A flesh-and-bones software developer named Carl Brown decided to take on Devin . A task that took the generative A.I.-powered agent over six hours took Mr. Brown just 36 minutes. Devin also executed poorly, running a slower, outdated programming language through a complicated process. “Right now the state of the art of generative A.I. is it just does a bad, complicated, convoluted job that just makes more work for everyone else,” Mr. Brown concluded in his YouTube video .

Cognition, Devin’s maker, responded by acknowledging that Devin did not complete the output requested and added that it was eager for more feedback so it can keep improving its product. Of course, A.I. companies are always promising that an actually useful version of their technology is just around the corner. “ GPT-4 is the dumbest model any of you will ever have to use again by a lot ,” Mr. Altman said recently while talking up GPT-5 at a recent event at Stanford University.

The reality is that A.I. models can often prepare a decent first draft. But I find that when I use A.I., I have to spend almost as much time correcting and revising its output as it would have taken me to do the work myself.

And consider for a moment the possibility that perhaps A.I. isn’t going to get that much better anytime soon. After all, the A.I. companies are running out of new data on which to train their models, and they are running out of energy to fuel their power-hungry A.I. machines . Meanwhile, authors and news organizations (including The New York Times ) are contesting the legality of having their data ingested into the A.I. models without their consent, which could end up forcing quality data to be withdrawn from the models.

Given these constraints, it seems just as likely to me that generative A.I. could end up like the Roomba, the mediocre vacuum robot that does a passable job when you are home alone but not if you are expecting guests.

Companies that can get by with Roomba-quality work will, of course, still try to replace workers. But in workplaces where quality matters — and where workforces such as screenwriters and nurses are unionized — A.I. may not make significant inroads.

And if the A.I. models are relegated to producing mediocre work, they may have to compete on price rather than quality, which is never good for profit margins. In that scenario, skeptics such as Jeremy Grantham, an investor known for correctly predicting market crashes, could be right that the A.I. investment bubble is very likely to deflate soon .

The biggest question raised by a future populated by unexceptional A.I., however, is existential. Should we as a society be investing tens of billions of dollars, our precious electricity that could be used toward moving away from fossil fuels, and a generation of the brightest math and science minds on incremental improvements in mediocre email writing?

We can’t abandon work on improving A.I. The technology, however middling, is here to stay, and people are going to use it. But we should reckon with the possibility that we are investing in an ideal future that may not materialize.

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

Follow the New York Times Opinion section on Facebook , Instagram , TikTok , WhatsApp , X and Threads .

Julia Angwin, a contributing Opinion writer and the founder of Proof News , writes about tech policy. You can follow her on Twitter or Mastodon or her personal newsletter .

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In first AI dialogue, US cites ‘misuse’ of AI by China, Beijing protests Washington’s restrictions

FILE -President Joe Biden, right, greets China’s President President Xi Jinping, left, at the Filoli Estate in Woodside, USA, Wednesday, Nov. 15, 2023. The National Security Council says high-level U.S. government envoys raised concerns about “the misuse of AI” by China and others in closed-door talks with Chinese officials in Geneva. NSC spokesperson Adrienne Watson said the countries exchanged perspectives on AI safety and risk management in “candid and constructive” discussions a day earlier. (Doug Mills/The New York Times via AP, Pool, File)

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GENEVA (AP) — U.S. officials raised concerns about China’s “misuse of AI” while Beijing’s representatives rebuked Washington over “restrictions and pressure” on artificial intelligence, the governments said separately Wednesday, a day after a meeting in Geneva on the technology.

Summaries of the closed-door talks between high-level envoys, which covered AI’s risks and ways to manage it, hinted at the tension between Beijing and Washington over the rapidly advancing technology that has become another flashpoint in bilateral relations.

China and the United States “exchanged perspectives on their respective approaches to AI safety and risk management” in the “candid and constructive” discussions a day earlier , National Security Council spokesperson Adrienne Watson said in a statement. Beijing said the two sides exchanged views “in-depth, professionally, and constructively.”

The first such U.S.-China talks on AI were the product of a November meeting between Presidents Joe Biden and Xi Jinping in San Francisco . The talks testified to concerns and hopes about the promising but potentially perilous new technology.

“The United States underscored the importance of ensuring AI systems are safe, secure and trustworthy in order to realize these benefits of AI — and of continuing to build global consensus on that basis,” Watson said. Referring to the People’s Republic of China, she added: “The United States also raised concerns over the misuse of AI, including by the PRC.”

She didn’t elaborate on the type of misuse or other actors behind it.

Beijing, meanwhile, “expressed a stern stance on the U.S. restrictions and pressure in the field of artificial intelligence” against China, the country’s Foreign Ministry’s Department of North American and Oceanian Affairs said in a social media post.

Beijing has previously lashed out at Commerce Department export controls limiting access to advanced computer chips that can be used for AI. Biden in August signed an executive order to restrict U.S. investments in China’s AI industry.

China also advocates for the United Nations to take a leading role in the global governance of AI, a move that could sideline the U.S.

Both sides recognized that while AI presents opportunities, “it also poses risks,” the Chinese statement said.

China has built one of the world’s most intrusive digital surveillance systems, which have an AI component, deploying cameras in city streets and tracking citizens through chat apps and mobile phones.

Watson said the U.S. wants to keep communication open with China on AI risk and safety “as an important part of responsibly managing competition,” an allusion to the multifaceted and growing rivalry between the world’s top two economic powers.

Helen Toner, an analyst at Georgetown’s Center for Security and Emerging Technology, said that “the real verdict on whether these talks were successful will be whether they continue into the future.”

AI is already having a vast effect on lifestyles, jobs, national defense, culture, politics and much more — and its role is set to grow.

China warned as far back as 2018 of the need to regulate AI but has nonetheless funded a vast expansion in the field as part of efforts to seize the high ground on cutting-edge technologies.

Some U.S. lawmakers have voiced concerns that China could back the use of AI-generated deepfakes to spread political disinformation, though China, unlike the U.S., has imposed a set of new laws banning manipulative AI fakery.

Chan reported from London. AP Tech Writers Matt O’Brien in Rhode Island, Frank Bajak in Boston and Asian Affairs Writer Didi Tang in Washington contributed to this report.

U.S. elections face more threats from foreign actors and artificial intelligence

Director of National Intelligence Avril Haines testifying before a Senate hearing earlier this month. During a May 15 hearing, she identified Russia as the greatest foreign threat to this year's U.S. elections.

Win McNamee / Getty Images

U.S. elections face more threats than ever from foreign actors, enabled by rapid developments in artificial intelligence , the country's top intelligence official told lawmakers on Wednesday.

Federal, state and local officials charged with protecting voting integrity face a "diverse and complex" threat landscape, Director of National Intelligence Avril Haines told the Senate Intelligence Committee at a hearing about risks to the 2024 elections. But she also said the federal government "has never been better prepared" to protect elections, thanks to lessons learned since Russia tried to influence voters in 2016.

This year, "Russia remains the most active foreign threat to our elections," Haines said. Using a "vast multimedia influence apparatus" encompassing state media, intelligence services and online trolls , Russia's goals "include eroding trust in U.S. democratic institutions, exacerbating sociopolitical divisions in the United States, and degrading Western support to Ukraine."

But it's a crowded field, with China , Iran and other foreign actors also trying to sway American voters , Haines added.

In addition, she said the rise of new AI technologies that can create realistic "deepfakes" targeting candidates and of commercial firms through which foreign actors can launder their activities are enabling more sophisticated influence operations at larger scale that are harder to attribute.

Wednesday's hearing was the first in a series focused on the election, said committee chair Sen. Mark Warner, D-Va., as lawmakers seek to avoid a repeat of 2016, when Russia's meddling caught lawmakers, officials and social media executives off-guard.

Since then, "the barriers to entry for foreign malign influence have unfortunately become incredibly small," Warner said. Foreign adversaries have more incentives to intervene in U.S. politics in an effort to shape their own national interests, he added, and at the same time, Americans' trust in institutions has eroded across the political spectrum .

Sen. Marco Rubio of Florida, the committee's top Republican, questioned how those tasked with protecting the election would themselves be received in a climate of distrust. He raised the specter of a fake video targeting himself or another candidate in the days before November's election.

"Who is in charge of letting people know, this thing is fake, this thing is not real?" he asked. "And I ask myself, whoever is in charge of it, what are we doing to protect the credibility of the entity that is ... saying it, so that the other side does not come out and say, 'Our own government is interfering in the election'?"

Haines said in some cases it would make sense for her or other federal agencies to debunk false claims, while in others it may be better for state or local officials to speak out.

Copyright 2024 NPR. To see more, visit https://www.npr.org.

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Security Brief: Artificial Sweetener: SugarGh0st RAT Used to Target American Artificial Intelligence Experts

What happened .

Proofpoint recently identified a SugarGh0st RAT campaign targeting organizations in the United States involved in artificial intelligence efforts, including those in academia, private industry, and government service. Proofpoint tracks the cluster responsible for this activity as UNK_SweetSpecter. 

SugarGh0st RAT is a remote access trojan, and is a customized variant of Gh0stRAT, an older commodity trojan typically used by Chinese-speaking threat actors. SugarGh0st RAT has been historically used to target users in Central and East Asia, as first reported by Cisco Talos in November 2023.  

In the May 2024 campaign, UNK_SweetSpecter used a free email account to send an AI-themed lure enticing the target to open an attached zip archive. 

Analyst note: Proofpoint uses the UNK_ designator to define clusters of activity that are still developing and have not been observed enough to receive a numerical TA designation. 

Lure email 

Following delivery of the zip file, the infection chain mimicked “Infection Chain 2” as reported by Cisco Talos. The attached zip file dropped an LNK shortcut file that deployed a JavaScript dropper. The LNK was nearly identical to the publicly available LNK files from Talos’ research and contained many of the same metadata artifacts and spoofed timestamps in the LNK header. The JavaScript dropper contained a decoy document, an ActiveX tool that was registered then abused for sideloading, and an encrypted binary, all encoded in base64. While the decoy document was displayed to the recipient, the JavaScript dropper installed the library, which was used to run Windows APIs directly from the JavaScript. This allowed subsequent JavaScript to run a multi-stage shellcode derived from DllToShellCode to XOR decrypt, and aplib decompress the SugarGh0st payload. The payload had the same keylogging, command and control (C2) heartbeat protocol, and data exfiltration methods. The main functional differences in the infection chain Proofpoint observed compared to the initial Talos report were a slightly modified registry key name for persistence, CTFM0N.exe, a reduced number of commands the SugarGh0st payload could run, and a different C2 server. The analyzed sample contained the internal version number of 2024.2.  

Network analysis 

Threat Research analysis demonstrated UNK_SweetSpecter had shifted C2 communications from previously observed domains to account.gommask[.]online. This domain briefly shared hosting on 103.148.245[.]235 with previously reported UNK_SweetSpecter domain account.drive-google-com[.]tk. Our investigation identified 43.242.203[.]115 hosting the new C2 domain. All identified UNK_SweetSpecter infrastructure appears to be hosted on AS142032.  

Context 

Since SugarGh0st RAT was originally reported in November 2023, Proofpoint has observed only a handful of campaigns. Targeting in these campaigns included a U.S. telecommunications company, an international media organization, and a South Asian government organization. Almost all of the recipient email addresses appeared to be publicly available.  

While the campaigns do not leverage technically sophisticated malware or attack chains, Proofpoint’s telemetry supports the assessment that the identified campaigns are extremely targeted. The May 2024 campaign appeared to target less than 10 individuals, all of whom appear to have a direct connection to a single leading US-based artificial intelligence organization according to open source research.  

Attribution  

Initial analysis by Cisco Talos suggested SugarGh0st RAT was used by Chinese language operators. Analysis of earlier UNK_SweetSpecter campaigns in Proofpoint visibility confirmed these language artifacts. At this time, Proofpoint does not have any additional intelligence to strengthen this attribution.  

While Proofpoint cannot attribute the campaigns with high confidence to a specific state objective, the lure theme specifically referencing an AI tool, targeting of AI experts, interest in being connected with “technical personnel,” interest in a specific software, and highly targeted nature of this campaign is notable. It is likely the actor’s objective was to obtain non-public information about generative artificial intelligence. 

The timing of the recent campaign coincides with an 8 May 2024 report from Reuters , revealing that the U.S. government was furthering efforts to limit Chinese access to generative artificial intelligence. It is possible that if Chinese entities are restricted from accessing technologies underpinning AI development, then Chinese-aligned cyber actors may target those with access to that information to further Chinese development goals.  

Why it matters  

For enterprise defenders facing a near constant onslaught of vulnerabilities and threats, monitoring targeted threat actors often seems like a herculean task. This campaign is an example of how it’s worth establishing baselines to identify malicious activity, even if the threat may not currently exist across an organization's threat model. This activity also demonstrates how the operators of highly targeted spearphishing campaigns may find themselves relying on commodity tools for initial access. 

Proofpoint Threat Research thanks the Yahoo! Paranoids Advanced Cyber Threats Team for their collaboration in this investigation. 

Emerging Threats signatures 

ET MALWARE SugarGh0st RAT CnC Checkin   

UNK_SweetSpecter SugarGh0st CnC Domain in DNS Lookup  

UNK_SweetSpecter SugarGh0st CnC Domain in TLS SNI  

Indicators of compromise 

Analyst note: The DLL hash has previously been observed in other attack chains and is not exclusive to SugarGh0st RAT campaigns.  

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