The Alignment Problem Machine Learning And Human Values
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| Author | : Brian Christian |
| Publisher | : W. W. Norton & Company |
| Total Pages | : 459 |
| Release | : 2020-10-06 |
| Genre | : Science |
| ISBN | : 039363583X |
A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.
| Author | : Brian Christian |
| Publisher | : Anchor |
| Total Pages | : 322 |
| Release | : 2012-03-06 |
| Genre | : Psychology |
| ISBN | : 0307476707 |
A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place. “Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there is also a prize, strange and intriguing, for the “Most Human Human.” Brian Christian—a young poet with degrees in computer science and philosophy—was chosen to participate in a recent competition. This
| Author | : Stuart Jonathan Russell |
| Publisher | : Penguin Books |
| Total Pages | : 354 |
| Release | : 2019 |
| Genre | : Business & Economics |
| ISBN | : 0525558616 |
A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.
| Author | : Melanie Mitchell |
| Publisher | : Farrar, Straus and Giroux |
| Total Pages | : 336 |
| Release | : 2019-10-15 |
| Genre | : Computers |
| ISBN | : 0374715238 |
Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
| Author | : Mark Coeckelbergh |
| Publisher | : MIT Press |
| Total Pages | : 250 |
| Release | : 2020-04-07 |
| Genre | : Computers |
| ISBN | : 0262538199 |
This overview of the ethical issues raised by artificial intelligence moves beyond hype and nightmare scenarios to address concrete questions—offering a compelling, necessary read for our ChatGPT era. Artificial intelligence powers Google’s search engine, enables Facebook to target advertising, and allows Alexa and Siri to do their jobs. AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues. Written by a philosopher of technology, AI Ethics goes beyond the usual hype and nightmare scenarios to address concrete questions. Mark Coeckelbergh describes influential AI narratives, ranging from Frankenstein’s monster to transhumanism and the technological singularity. He surveys relevant philosophical discussions: questions about the fundamental differences between humans and machines and debates over the moral status of AI. He explains the technology of AI, describing different approaches and focusing on machine learning and data science. He offers an overview of important ethical issues, including privacy concerns, responsibility and the delegation of decision making, transparency, and bias as it arises at all stages of data science processes. He also considers the future of work in an AI economy. Finally, he analyzes a range of policy proposals and discusses challenges for policymakers. He argues for ethical practices that embed values in design, translate democratic values into practices and include a vision of the good life and the good society.
| Author | : Brian Cantwell Smith |
| Publisher | : MIT Press |
| Total Pages | : 179 |
| Release | : 2019-10-08 |
| Genre | : Computers |
| ISBN | : 0262355213 |
An argument that—despite dramatic advances in the field—artificial intelligence is nowhere near developing systems that are genuinely intelligent. In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability “reckoning,” and argues that it does not lead to full human judgment—dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (“good old-fashioned AI,” or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself—what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.
| Author | : John Zerilli |
| Publisher | : MIT Press |
| Total Pages | : 233 |
| Release | : 2021-02-23 |
| Genre | : Computers |
| ISBN | : 0262044811 |
A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, voters in liberal democracies? This book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues including transparency, bias, liability, privacy, and regulation.
| Author | : Kate Crawford |
| Publisher | : Yale University Press |
| Total Pages | : 336 |
| Release | : 2021-04-06 |
| Genre | : Computers |
| ISBN | : 0300209576 |
The hidden costs of artificial intelligence, from natural resources and labor to privacy and freedom What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? In this book Kate Crawford reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequality. Drawing on more than a decade of research, award-winning science, and technology, Crawford reveals how AI is a technology of extraction: from the energy and minerals needed to build and sustain its infrastructure, to the exploited workers behind "automated" services, to the data AI collects from us. Rather than taking a narrow focus on code and algorithms, Crawford offers us a political and a material perspective on what it takes to make artificial intelligence and where it goes wrong. While technical systems present a veneer of objectivity, they are always systems of power. This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.
| Author | : William MacAskill |
| Publisher | : Oxford University Press |
| Total Pages | : 237 |
| Release | : 2020 |
| Genre | : Business & Economics |
| ISBN | : 0198722273 |
About the bookToby Ord try to fill this gap. They argue that there are distinctive norms that govern how one ought to make decisions and defend an information-sensitive account of how to make such decisions. They do so by developing an analogy between moral uncertainty and social choice, noting that different moral views provide different amounts of information regarding our reasons for action, and arguing that the correct account of decision-making under moral uncertainty must be sensitive to that. Moral Uncertainty also tackles the problem of how to make intertheoretic comparisons, and addresses the implications of their view for metaethics and practical ethics. Very often we are uncertain about what we ought, morally, to do. We do not know how to weigh the interests of animals against humans, how strong our duties are to improve the lives of distant strangers, or how to think about the ethics of bringing new people into existence. But we still need to act. So how should we make decisions in the face of such uncertainty? Though economists and philosophers have extensively studied the issue of decision-making in the face of uncertainty about matters of fact, the question of decision-making given fundamental moral uncertainty has been neglected. In Moral Uncertainty, philosophers William MacAskill, Krister Bykvist, and Toby Ord try to fill this gap. They argue that there are distinctive norms that govern how one ought to make decisions and defend an information-sensitive account of how to make such decisions. They do so by developing an analogy between moral uncertainty and social choice, noting that different moral views provide different amounts of information regarding our reasons for action, and arguing that the correct account of decision-making under moral uncertainty must be sensitive to that. Moral Uncertainty also tackles the problem of how to make intertheoretic comparisons, and addresses the implications of their view for metaethics and practical ethics.
| Author | : Eran Fisher |
| Publisher | : Routledge |
| Total Pages | : 76 |
| Release | : 2022-01-26 |
| Genre | : Computers |
| ISBN | : 1000545997 |
In this thought-provoking volume, Eran Fisher interrogates the relationship between algorithms as epistemic devices and modern notions of subjectivity. Over the past few decades, as the instrumentalization of algorithms has created knowledge that informs our decisions, preferences, tastes, and actions, and the very sense of who we are, they have also undercut, and arguably undermined, the Enlightenment-era ideal of the subject. Fisher finds that as algorithms enable a reality in which knowledge is created by circumventing the participation of the self, they also challenge contemporary notions of subjectivity. Through four case-studies, this book provides an empirical and theoretical investigation of this transformation, analyzing how algorithmic knowledge differs from the ideas of critical knowledge which emerged during modernity – Fisher argues that algorithms create a new type of knowledge, which in turn changes our fundamental sense of self and our concept of subjectivity. This book will make a timely contribution to the social study of algorithms and will prove especially valuable for scholars working at the intersections of media and communication studies, internet studies, information studies, the sociology of technology, the philosophy of technology, and science and technology studies.
