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.
