How tech companies, journalists, and policymakers can prevent AI decision-making from going wrong.

Our lives are increasingly governed by automated systems influencing everything from medical care to policing to employment opportunities, but researchers and investigative journalists have proven that AI systems regularly get things wrong.

Auditing AI is a first-of-its-kind exploration of why and how to audit artificial intelligence systems. It offers a simple roadmap for using AI audits to make product and policy changes that benefit companies and the public alike. The book aims to convince readers that AI systems should be subject to robust audits to protect all of us from the dangers of these systems. Readers will come away with an understanding of what an AI audit is, why AI audits are important, key components of an audit that follows best practices, how to interpret an audit, and the available choices to act on an audit’s results.

The book is organized around canonical examples: from AI-powered drones mistakenly targeting civilians in conflict areas to false arrests triggered by facial recognition systems that misidentified people with dark skin tones to HR hiring software that prefers men. It explains these definitive cases of AI decision-making gone wrong and then highlights specific audits that have led to concrete changes in government policy and corporate practice.

The Marquand House Collective: Marc Aidinoff, Lena Armstrong, Esha Bhandari, Ellery Roberts Biddle, Motahhare Eslami, Karrie Karahalios, Nate Matias, Danaé Metaxa, Alondra Nelson, Christian Sandvig, and Kristen Vaccaro.

Series Overview: The MIT Press Essential Knowledge series offers accessible, concise, beautifully produced books on topics of current interest. Written by leading thinkers, the books in this series deliver expert overviews of subjects that range from the cultural and the historical to the scientific and the technical. In today’s era of instant information gratification, we have ready access to opinions, rationalizations, and superficial descriptions. Much harder to come by is the foundational knowledge that informs a principled understanding of the world. Essential Knowledge books fill that need. Synthesizing specialized subject matter for nonspecialists and engaging critical topics through fundamentals, each of these compact volumes offers readers a point of access to complex ideas.
 
Contributor Bio(s)
 
The Marquand House Collective comprises eleven experts in AI auditing spanning computing, law, policy, social science, and journalism. Members coined the term “algorithm audit” in 2014. The full group convened in 2024 at Marquand House in Princeton, New Jersey.

Author Residence: Ann Arbor, MI

Author Hometown: Ann Arbor, MI