Great Books for AI Engineering

The role of AI engineer has emerged prominently in 2023 with the release of GPT-4, and the most important skills and tools to build robust, useful systems are still in flux. A set of books can help others working to make the next set of advancements in AI engineering possible. "The Alignment Problem" by Brian Christian explores the gap between the intention of instructions and exhibited behaviors in AI systems, examining how our attempts to align machine behavior with human values reveal fundamental questions about intelligence and ethics. "Brave New Words" by Salman Khan focuses on how to make AI that works as an accelerator of learning and a way to increase standards in the education system. "Human Compatible" by Stuart Russell provides a different perspective on the alignment problem, attempting to start from first principles to expose the complex nuances of alignment and ways to approach AI that can mitigate some of the risks. "Hidden Games" by Erez Yoeli presents game theory as a fundamental framework for understanding complex interactions, whether between humans or artificial systems. "Guardrails" by Urs Gasser and Viktor Mayer-Schonberger discusses the design of control systems that shape and direct AI to the benefit of humans. "Optimal Illusions" by Coco Krumme examines a central paradox in artificial intelligence development: our drive for optimization often leads to systems that are brittle and inflexible. "Playing with Reality" by Kelly Clancy looks at the use of game theory in building modern systems, its pitfalls, and how we can frame problems to devise better games that will incentivize behaviors that lead to better results. "Complex Adaptive Systems" by John H. Miller and Scott E. Page is an important book that explores complex adaptive systems, which exhibit emergent behaviors and non-linear adaptive responses, and its principles can be applied to artificial intelligences.