Tom Griffiths

Examining how computer science and mathematical algorithms can explain human cognition provides a practical framework for tackling complex daily decisions and understanding cognitive processing. Tom Griffiths explores the intersection of artificial intelligence, cognitive psychology, and computational modeling to unpack how the human mind solves everyday problems. Through works like Algorithms to Live By: The Computer Science of Human Decisions, his writing translates sophisticated computational theories into accessible guidance for human choices.

Career & Background

Griffiths serves as the Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University, holding joint academic appointments in the Department of Psychology and the Department of Computer Science. At Princeton, he directs the Computational Cognitive Science Lab and the Princeton Laboratory for Artificial Intelligence. His academic work brings together graduate researchers across psychology, computer science, and neuroscience to explore the mathematical foundations of cognition.

Writing Style & Themes

His research and writing examine how mathematical structures and machine learning principles apply to human psychology. Rather than treating human cognition as inherently flawed, Griffiths explores how people solve complex computational challenges under bounded time and resources. His work bridges computer science and human behavior, examining themes such as optimal stopping, memory organization, decision-making under uncertainty, and the formal principles underlying intuitive thought.

Major Works

• Algorithms to Live By: The Computer Science of Human Decisions — Co-authored with Brian Christian, this book demonstrates how fundamental algorithms from computer science can illuminate human decision-making, covering topics such as scheduling, memory organization, and optimal stopping strategies in daily life.
• The Laws of Thought: The Quest for a Mathematical Theory of the Mind — This work examines the historical and contemporary efforts to formulate mathematical and computational theories of human cognition, tracing how formal models explain intelligence and thought processes.