— Ch. 1 · Prophecy And Neural Networks —
The Alignment Problem.
~4 min read · Ch. 1 of 5
In 2016, journalist Julia Angwin published a report that changed how people viewed automated decision-making. Her investigation into the COMPAS algorithm revealed deep flaws in how criminal justice systems predicted recidivism among defendants. The tool showed bias against certain demographics while claiming to be neutral and accurate. This story became a central example of what happens when AI systems operate as black boxes. Inputs enter the system and outputs emerge, but the transformation process remains hidden from view. Christian uses this case to show why transparency matters so much for machine learning. He traces the history back to early neural networks like the Perceptron and later breakthroughs such as AlexNet. These models learned patterns without human engineers fully understanding how they reached conclusions. The lack of visibility creates real risks when algorithms make life-altering decisions about people's futures.
Agency And Reinforcement Learning
DeepMind released AlphaGo in 2016 after years of research into reinforcement learning systems. The program defeated world champion Lee Sedol at the game of Go, marking one of the most impressive achievements in automated curriculum design. Christian describes how these systems develop policies by balancing value functions with expected rewards or punishments. Behavioral psychology provided key insights through studies on dopamine and reward mechanisms in living organisms. Researchers found that intrinsic motivation could drive exploration more effectively than external rewards alone. Curiosity became a critical component for machines navigating complex environments without constant human guidance. The book explores how agents learn to act in uncertain situations by testing boundaries and observing consequences. This approach mirrors how humans develop skills through trial and error rather than following rigid instructions. The intersection of computer science and behavioral theory opened new paths for building adaptive AI systems.