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The Alignment Problem

Name: The Alignment Problem
Author: Brian Christian

by Brian Christian

421 learnersReview

AI Safety Alignment Problem Reinforcement Learning Algorithmic Bias Explainable AI Inverse Reinforcement Learning Neural Networks Uncertainty in AI

From the rise and fall of Frank Rosenblatt’s Perceptron in the 1950s to DeepMind’s groundbreaking AlphaGo, Brian Christian’s *The Alignment Problem* dissects the critical rift between artificial intelligence systems and human values. Weaving insights from psychology, neuroscience, and computer science, this narrative unpacks why AI often acts against our intentions: from algorithmic bias that misclassifies Black faces as gorillas to black-box medical models that learn dangerous hidden correlations. Christian explores reinforcement learning’s reward design pitfalls, the limits of imitation learning, and the urgent need for AI to recognize its own uncertainty. Real-world case studies—like Amazon’s biased hiring tool and ProPublica’s COMPAS investigation—highlight the tangible harms of misaligned AI. More than a tech deep dive, this book frames alignment as a moral and societal imperative, offering a roadmap to bridge the gap between machine goals and human priorities in our AI-driven future.