AI Fairness
(MIT Press, 2025)
Decisions about important social goods like education, employment, housing, loans, healthcare, and criminal justice are all becoming increasingly automated with the help of AI systems. But because AI systems are trained on data with historical inequalities, many of these systems produce unequal outcomes for members of disadvantaged groups.
For several years now, researchers who design AI systems have investigated the causes of inequalities in AI decisions, and proposed techniques for mitigating them. It turns out that in most realistic conditions it is impossible to enforce equality across all metrics simultaneously. Because of this, companies using AI systems will have to choose which metric they think is the correct measure of fairness, and regulators will need to determine how to apply currently existing laws to AI systems.
This book will draw on traditional philosophical theories of fairness to develop a framework for evaluating these standards and measurements, which can be called a Theory of Algorithmic Justice. The theory is inspired by the Theory of Justice developed by the American philosopher John Rawls. Most books on this topic are written by computer scientists, and this book is unique in bringing important ideas from ethics and political philosophy to provide the arguments that are needed to defend the fairness of an AI system.
Ethics for Robots
(Routledge, 2018)
Ethics for Robots describes and defends a method for designing and evaluating ethics algorithms for autonomous machines, such as self-driving cars and search and rescue drones. Derek Leben argues that such algorithms should be evaluated by how effectively they accomplish the problem of cooperation among self-interested organisms, and therefore, rather than simulating the psychological systems that have evolved to solve this problem, engineers should be tackling the problem itself, taking relevant lessons from our moral psychology.
Leben draws on the moral theory of John Rawls, arguing that normative moral theories are attempts to develop optimal solutions to the problem of cooperation. He claims that Rawlsian Contractarianism leads to the ‘Maximin’ principle – the action that maximizes the minimum value – and that the Maximin principle is the most effective solution to the problem of cooperation. He contrasts the Maximin principle with other principles and shows how they can often produce non-cooperative results.
Using real-world examples – such as an autonomous vehicle facing a situation where every action results in harm, home care machines, and autonomous weapons systems – Leben contrasts Rawlsian algorithms with alternatives derived from utilitarianism and natural rights libertarianism.
Including chapter summaries and a glossary of technical terms, Ethics for Robots is essential reading for philosophers, engineers, computer scientists, and cognitive scientists working on the problem of ethics for autonomous systems.
“A great book that I recommend everyone checks out”
-Sean M. Carroll
Author of The Big Picture and From Eternity to Here
