Alignment Problem

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.

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

Itâe(tm)s the summer of 1972. Maggie, a young schoolteacher, leaves the United States to settle with her boyfriend, Fletcher, on a farm near Niagara Falls. Theyâe(tm)ve made the journey to keep him out of the draft, but they also have loftier plans âe" to start a commune and work the land. As the summer passes, Maggie is haunted by the lack of word from her father, a missionary in the war-torn jungles of Laos. Then the US government announces the end of the draft, and Fletcher faces pressure from his family to return home. More people arrive at the farm, but they arenâe(tm)t who anyone expected. Tensions threaten the commune, the neighbours are suspicious, and Maggie finds herself negotiating the gap between ideals and reality, between who people want to be and who they actually are. Just as her new life seems on the brink of falling apart, Maggie receives word from Laos that her father has disappeared. Suddenly, her future depends not only on keeping everyone together, but also on discovering the truth about her fatherâe(tm)s actions and beliefs in the days before he vanished. Once We Had a Country returns us to an era we thought we knew and compels us to consider the courage of our own convictions as well as the depths of our desire for a meaningful life. It cements Robert McGillâe(tm)s standing as a writer of rare and exceptional talent.

"Clear, easy-to-read presentation of the importance of posture or body alignment with respect to appearance, maintaining physical functioning, and preventing muscle and joint pain and disability particularly as one grows older. Includes postural self-assessment and over one hundred exercises in various short menus to correct and maintain proper body alignment."

"The most important book on AI this year." --The Guardian "Mr. Russell's exciting book goes deep, while sparkling with dry witticisms." --The Wall Street Journal "The most important book I have read in quite some time" (Daniel Kahneman); "A must-read" (Max Tegmark); "The book we've all been waiting for" (Sam Harris) A leading artificial intelligence researcher lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage. If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial.

"Celebrity manual therapist and movement coach Aaron Alexander shows readers how posture and body alignment are powerful tools for building strength, achieving peak performance, reducing pain, and approaching the world with a new sense of confidence."--

Buy now to get the main key ideas from Brian Christian’s The Alignment Problem As machine-learning systems grow not only more prevalent, but also more powerful, humans want to ensure that they understand us and do what we want, eliminating the possibility of catastrophic divergence. In the field of computer science, this question is known as the alignment problem. In The Alignment Problem (2020), Brian Christian raises questions of safety and ethics in a world where humans are turning into machines and machines are turning into humans. He discusses tools that, through imitation, curiosity, inference, and shaping, exhibit human skills without being programmed to do so. The future of machine learning holds risks, but also great promise.