Brian Christian

Brian Christian is an American author and researcher working where computer science meets cognitive science, philosophy and public life. He studied computer science and philosophy at Brown University and poetry and nonfiction at the University of Washington. He is a research fellow at UC Berkeley’s Center for Human-Compatible AI.

His nonfiction explains technical ideas through intellectual history, interviews and concrete cases. Across his books, he asks what computing can reveal about human judgment and what gets lost when values are translated into rules, scores or rewards. The Most Human Human examines machine conversation and the Turing test; Algorithms to Live By, written with cognitive scientist Tom Griffiths, applies ideas from computer science to everyday decisions.

The Alignment Problem: Machine Learning and Human Values focuses on the gap between what people intend and what machine-learning systems actually do. It traces problems involving bias, reward and control while following researchers attempting to make AI systems answer more reliably to human purposes. The book earned Christian a 2022 Eric and Wendy Schmidt Award for Excellence in Science Communications from the National Academies.

Start with The Alignment Problem. It offers the clearest route into Christian’s central subject: how technical systems absorb imperfect human goals and produce consequences their designers did not foresee. Readers more interested in personal decision-making can continue with Algorithms to Live By.