May 1, 2024
Updated June 27, 2025
14 minute read
An Introduction to Fairness in Artificial Intelligence
Artificial Intelligence, or AI, refers to the simulation of human intelligence in machines that are programmed to think, learn, and problem-solve. These systems are increasingly integrated into our daily lives, influencing everything from the news we read to the music we hear. As AI's role expands, ensuring these technologies operate equitably has become a paramount concern. This field of study and practice is known as "Fairness in AI." At its core, it is about identifying and mitigating unjust or prejudicial treatment of individuals or groups in the outcomes of automated decisions.
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Find a path to becoming a Fairness in AI. Learn more at:
OpenCourser.com/topic/q2umrl/fairness
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Fairness in AI.
Provides a practical guide to identifying and mitigating bias in AI systems. Thomas offers a range of tools and techniques that can be used to assess the fairness of AI systems and to reduce bias.
Explores the ethical challenges of AI, including fairness, transparency, and accountability. Kearns and Roth argue that we need to develop new ethical frameworks for AI that are based on human values.
Explores the ways in which AI is being used to create a new form of surveillance capitalism. Zuboff argues that AI is being used to track and control our every move, and she calls for a new era of privacy and data protection.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/q2umrl/fairness