Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics

17 December 2019

Papers citing "Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics"

8 / 8 papers shown

Title
Responding to Generative AI Technologies with Research-through-Design: The Ryelands AI Lab as an Exploratory Study Jesse Josua Benjamin Joseph Lindley Elizabeth Edwards Elisa Rubegni Tim Korjakow David Grist Rhiannon Sharkey 27 11 0 07 May 2024
The Perspective of Software Professionals on Algorithmic Racism Ronnie E. S. Santos Luiz Fernando de Lima C. Magalhães FaML 12 3 0 27 Jun 2023
A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners Nadia Nahar Haoran Zhang Grace A. Lewis Shurui Zhou Christian Kastner 21 36 0 31 Mar 2023
AI-Ethics by Design. Evaluating Public Perception on the Importance of Ethical Design Principles of AI Kimon Kieslich Birte Keller C. Starke 16 84 0 01 Jun 2021
Fairness Perceptions of Algorithmic Decision-Making: A Systematic Review of the Empirical Literature C. Starke Janine Baleis Birte Keller Frank Marcinkowski FaML 17 142 0 22 Mar 2021
Where Is the Normative Proof? Assumptions and Contradictions in ML Fairness Research A. Feder Cooper 10 7 0 20 Oct 2020
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness Mohammad Yaghini A. Krause Hoda Heidari FaML 11 22 0 08 Nov 2019
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016