An Introduction to Algorithmic Fairness

2021/05/12 by Hilde Weerts, Weerts, Hilde J. P.
Medicine · Neuroscience · Social Sciences · #Artificial Intelligence in Healthcare and Education #Computers and Society (cs.CY) #Ethics and Social Impacts of AI #FOS: Computer and information sciences #Neuroethics, Human Enhancement, Biomedical Innovations

paper · pdf · doi:10.48550/arxiv.2105.05595

openalex publication_date 2021/05/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In recent years, there has been an increasing awareness of both the public and scientific community that algorithmic systems can reproduce, amplify, or even introduce unfairness in our societies. These lecture notes provide an introduction to some of the core concepts in algorithmic fairness research. We list different types of fairness-related harms, explain two main notions of algorithmic fairness, and map the biases that underlie these harms upon the machine learning development process.

Citations

• Bias in computer systems
• Counterfactual Fairness
• Fairness and Abstraction in Sociotechnical Systems

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