This book explores a range of ways in which societies could fail to harness AI safely in coming years, such as malicious use, accidental failures, erosion of safety standards due to competition between AI developers or nation-states, and potential loss of control over autonomous systems. Grounded in the latest technical advances, this book offers a timely perspective on the challenges involved in making current AI systems safer. Ensuring that AI systems are safe is not just a problem for researchers in machine learning – it is a societal challenge that cuts across traditional disciplinary boundaries. Integrating insights from safety engineering, economics, and other relevant fields, this book provides readers with fundamental concepts to understand and manage AI risks more effectively.
This is an invaluable resource for upper-level undergraduate and postgraduate students taking courses relating to AI Safety & Alignment, AI Ethics, AI Policy, and the Societal Impacts of AI, as well as anyone trying to better navigate the rapidly evolving landscape of AI safety.
Dr. Dan Hendrycks is a machine learning researcher and Director of the Center for AI Safety (CAIS), USA. Dan holds a Ph.D. in Machine Learning from UC Berkeley. Dr. Hendrycks has given dozens of accessible and engaging talks on AI safety to diverse audiences at institutions such as OpenAI, Google, and Stanford. His expertise is regularly sought, evidenced by his role in organizing AI safety-related workshops at prestigious conferences, including NeurIPS, ICML, and ECCV. His work has not only had a substantial impact on the academic community but has also gained considerable public attention. Dr. Hendrycks has been profiled in media outlets like the Boston Globe and has had his work featured in the BBC, New York Times, TIME Magazine, and Washington Post.