Algorithms to Live By: The Computer Science of Human Decisions
Brian Christian
A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind
All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us.
In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.
The Most Human Human: What Talking with Computers Teaches Us About What It Means to Be Alive
Brian Christian
The Most Human Human is a provocative, exuberant, and profound exploration of the ways in which computers are reshaping our ideas of what it means to be human. Its starting point is the annual Turing Test, which pits artificial intelligence programs against people to determine if computers can “think.”
Named for computer pioneer Alan Turing, the Turing Test convenes a panel of judges who pose questions—ranging anywhere from celebrity gossip to moral conundrums—to hidden contestants in an attempt to discern which is human and which is a computer. The machine that most often fools the panel wins the Most Human Computer Award. But there is also a prize, bizarre and intriguing, for the Most Human Human.
In 2008, the top AI program came short of passing the Turing Test by just one astonishing vote. In 2009, Brian Christian was chosen to participate, and he set out to make sure Homo sapiens would prevail.
The author’s quest to be deemed more human than a computer opens a window onto our own nature. Interweaving modern phenomena like customer service “chatbots” and men using programmed dialogue to pick up women in bars with insights from fields as diverse as chess, psychiatry, and the law, Brian Christian examines the philosophical, biological, and moral issues raised by the Turing Test.
One central definition of human has been “a being that could reason.” If computers can reason, what does that mean for the special place we reserve for humanity?
The Alignment Problem: Machine Learning and Human Values
Brian Christian
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.