mlsanityData to 7 Oct 2026

An Introduction to Algorithmic Fairness

arXiv 2105.05595 ↗First posted 12 May 2021cs.CYcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 May 2021.

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Citing papers per year: 2022: 1; 2023: 1; 2024: 2.

4 papers.