In the second section, Christian similarly interweaves the history of the psychological study of reward, such as behaviorism and dopamine, with the computer science of reinforcement learning, in which AI systems need to develop policy ('what to do') in the face of a value function ('what rewards or punishment to expect'). The lack of transparency makes it difficult to know where the system is going right and where it is going wrong. One of AI's main alignment challenges is its black box nature (inputs and outputs are identifiable but the transformation process in between is undetermined). He tells the story of Julia Angwin, a journalist whose ProPublica investigation of the COMPAS algorithm, a tool for predicting recidivism among criminal defendants, led to widespread criticism of its accuracy and bias towards certain demographics. In the first section, Christian interweaves discussions of the history of artificial intelligence research, particularly the machine learning approach of artificial neural networks such as the Perceptron and AlexNet, with examples of how AI systems can have unintended behavior. Each section covers researchers and engineers working on different challenges in the alignment of artificial intelligence with human values. The book is divided into three sections: Prophecy, Agency, and Normativity. It is based on numerous interviews with experts trying to build artificial intelligence systems, particular machine learning systems, that are aligned with human values. The Alignment Problem: Machine Learning and Human Values is a 2020 non-fiction book by the American writer Brian Christian.

Brian christian's the alignment problem