“The Problem of Coordination should be required reading for anyone who influences policy where algorithms work, and it is everywhere. But unlike many must-reads, this book is a fun read. It playfully introduces personalities and relatable pieces of scientific history that put the choices of our current moment into context.”
Jennifer Palka, Founder of Code for America and former Deputy U.S. CTO
in The problem of coordination: machine learning and human valuesBrian Christian explores the growing gap between human intent and machine behavior, a central challenge of modern artificial intelligence.
Machine learning is impacting criminal sentencing, employment, healthcare, and self-driving cars, raising urgent questions about whether these systems reflect human values.
Christian explains that machine learning relies on models learning from data rather than following explicit rules. Although this approach is powerful, it often has unintended consequences. Although the system may achieve its objectives, it still reinforces bias and diminishes responsibility.
Through many examples, Christian shows how a flawed algorithm can reveal the depth of a problem.
He also profiles researchers in computer science, psychology, and philosophy who are working to align AI systems with human goals. Their research focuses on making these systems more transparent and fair, with the aim of understanding how machines process the subtle and often contradictory signals they receive.
Alignment issues Explore how machine learning has evolved with human values and real-world influences. Christian considers how technical work relates to ethical issues, showing what progress has been made and what challenges remain.
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