mlsanityData to 14 Oct 2026

Diversity and Inclusion in Artificial Intelligence

arXiv 2305.12728 ↗First posted 22 May 2023cs.AI cs.SEcited by 14

Not on the map. Why?

Abstract (arXiv)

To date, there has been little concrete practical advice about how to ensure that diversity and inclusion considerations should be embedded within both specific Artificial Intelligence (AI) systems and the larger global AI ecosystem. In this chapter, we present a clear definition of diversity and inclusion in AI, one which positions this concept within an evolving and holistic ecosystem. We use this definition and conceptual framing to present a set of practical guidelines primarily aimed at AI technologists, data scientists and project leaders.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 3 of its 25 references that are in the map. First posted on arXiv 22 May 2023.

Builds on

3 of 25 references.

References · 3

  1. 2018Why Is My Classifier Discriminatory?cited by 143
  2. 2022Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluationcited by 59
  3. 2021A Framework for Fairness: A Systematic Review of Existing Fair AI Solutionscited by 18

Built on by

Cited by year

Citing papers per year: 2023: 6; 2024: 4; 2025: 4.

14 papers.

Sort: