Luke Stark

Safety Research · with Greene · 2016–2020

A researcher in the Science corpus: 6 papers; trusts 10 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Safety Research — 33 citations into it; #5,573 of 5,829 by trust here, #1,585 by citations
• Safety, Robustness & Interpretability — 28 citations into it; #1,062 of 2,251 by trust here, #2,014 by citations
• Sociology and Political Science — 26 citations into it; #7,667 of 22,756 by trust here, #6,353 by citations
• AI Ethics, Fairness & Society — 19 citations into it; #195 of 494 by trust here, #338 by citations
• Social Sciences & Humanities — 9 citations into it

Whom Luke Stark trusts overall

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

1. Anna Lauren Hoffmann
2. Joy Buolamwini
3. Helen Nissenbaum
4. R. Gonzales
5. Batya Friedman
6. Safiya Umoja Noble
7. Anna Jobin
8. Andrew D. Selbst
9. Timnit Gebru
10. Min Kyung Lee

Who trusts Luke Stark overall

1. Anna Lauren Hoffmann
2. Mary Anne Smart
3. Daniel Greene
4. Ben Green
5. Shakir Mohamed
6. Vili Lehdonvirta
7. Irene Solaiman
8. Alessandro Gandini
9. Christine Gerber
10. J. Schor

Papers from Luke Stark's perspective

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

1. Equality of Opportunity in Supervised Learning
2. Fairness through awareness
3. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
4. The Scored Society: Due Process for Automated Predictions
5. Fairness in Criminal Justice Risk Assessments: The State of the Art
6. A Reductions Approach to Fair Classification
7. Race After Technology: Abolitionist Tools for the New Jim Code
8. Datasheets for datasets
9. A comparative study of fairness-enhancing interventions in machine learning
10. Discrimination in online ad delivery

Their papers

• Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers (2016) — 1,278 citations
• Facial recognition is the plutonium of AI (2019) — 117 citations
• Critical Perspectives on Governance Mechanisms for AI/ML Systems (2020) — 26 citations
• When not to design, build, or deploy (2020) — 40 citations
• Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI (2020) — 520 citations
• Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning (2019) — 324 citations