The Alignment Problem: Machine Learning and Human Values
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The Alignment Problem: Machine Learning and Human Values

02 September Online

About this event

Note: Our book club requires that attendees do the assigned readings before the meeting.

Please join us for our online book club discussion series for, “The Alignment Problem: Machine Learning and Human Values” by Brian Christian.

Assigned reading for this week: The Prologue, Introduction and Chapters 1 and 2. Please Note: Completion of the assigned reading is a prerequisite for attending. If you do not have the chance to do the reading, please join us another time.

What is this book about?
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.

About the author
Christian holds degrees in computer science, philosophy, and poetry from Brown University and the University of Washington. A Visiting Scholar at the University of California, Berkeley, he lives in San Francisco.
Christian’s writing has appeared in The New Yorker, The Atlantic, Wired, and The Wall Street Journal, as well as peer-reviewed journals such as Cognitive Science. He has been featured on The Daily Show and Radiolab, and has lectured at Google, Facebook, Microsoft, the Santa Fe Institute, and the London School of Economics. His work has won several awards, including publication in Best American Science & Nature Writing, and has been translated into nineteen languages.

How this book club works.
Our book discussion will be spread over several consecutive weeks, with two-hour meetings every Tuesday evening. This gives us time to explore the readings with the depth and care they deserve. Please bring your own thought-provoking questions and insights from the reading to share with the group. We like lively discussions that challenge our own ideas and those of the author and allow us to learn from each other -- while enjoying camaraderie! All we ask is that everyone be treated as co-equals, both in respect and approximate speaking time. Feel free to post (in the Comments below) any additional resources you find -- including ones that challenge the author. We hope to see you at our Tuesday meetings!

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