Stephen Cave

AI Ethics, Fairness & Society · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• AI Ethics, Fairness & Society — 7 citations into it
• Artificial Intelligence — 7 citations into it

Whom Stephen Cave trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Safiya Umoja Noble
2. William R. Easterly
3. Jessie Daniels
4. Joy Buolamwini
5. Yuting Liao

Papers from Stephen Cave's perspective

Ordered by how strongly the researchers Stephen Cave trusts endorse each paper. Same corpus, a different order for every researcher.

1. Race After Technology: Abolitionist Tools for the New Jim Code
2. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
3. Language (Technology) is Power: A Critical Survey of “Bias” in NLP
4. The White Man's Burden
5. Towards A Rigorous Science of Interpretable Machine Learning
6. Fairness in Machine Learning: Lessons from Political Philosophy
7. Challenges for Transparency
8. Algorithms of Oppression: How Search Engines Reinforce Racism
9. Google DeepMind and healthcare in an age of algorithms (Health technology)
10. Regulating Black-Box Medicine.

Their papers

• The Whiteness of AI (2020) — 211 citations
• The Role and Limits of Principles in AI Ethics: Towards a Focus on Tensions (2019) — 348 citations