Bias and Fairness
Articles
- Towards a Standard for Identifying and Managing Bias in Artificial IntelligenceSpecial Publication by the National Institute of Standards and Technology, Mar. 2022
- Artificial Intelligence: Can We Trust Machines to Make Fair Decisions?Data and Computer Scientists, Ecologists, Pathologists, and Legal Scholars Study AI’s Biases by Catherine Kenny, UC Davis, Apr. 13, 2021
- Auditing the AI Auditors: A Framework for Evaluating Fairness and Bias in High Stakes AI Predictive ModelsRichard Landers and Tara S. Behrend, American Psychologist, Jan. 2023
- Finding ‘fairness’ in AI: How to combat bias in the data collection processZach Warren, Thomson Reuters, Nov. 14, 2022
Videos
- Algorithmic Bias and Fairness #18Video from Crash Course: Artificial Intelligence
- Shaping AI through Cultural DiversityVideo from Unesco
Books in the Library
An Intelligence in Our Image by
Machine learning algorithms and artificial intelligence influence many aspects of life today and have gained an aura of objectivity and infallibility. The use of these tools introduces a new level of risk and complexity in policy. This report illustrates some of the shortcomings of algorithmic decisionmaking, identifies key themes around the problem of algorithmic errors and bias, and examines some approaches for combating these problems.
Made by Humans by
Who is designing AI? A select, narrow group. How is their world view shaping our future? ;Artificial intelligence can be all too human- quick to judge, capable of error, vulnerable to bias. It's made by humans, after all. Humans make decisions about the laws and standards, the tools, the ethics in this new world. Who benefits. Who gets hurt. ;Made by Humans explores our role and responsibilities in automation. Roaming from Australia to the UK and the US, elite data expert Ellen Broad talks to world leaders in AI about what we need to do next. It is a personal, thought-provoking examination of humans as data and humans as the designers of systems that are meant to help us.
