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.
