What You See Is What You Get? The Impact of Representation Criteria on
Human Bias in Hiring

What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring

8 September 2019

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Papers citing "What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring"

10 / 10 papers shown

Title
Fair Machine Guidance to Enhance Fair Decision Making in Biased People Mingzhe Yang Hiromi Arai Naomi Yamashita Yukino Baba FaML 70 6 0 08 Apr 2024
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making Luke M. Guerdan Amanda Coston Zhiwei Steven Wu Kenneth Holstein CML 82 30 0 13 Feb 2023
Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance Andrew Bell O. Nov Julia Stoyanovich 75 29 0 10 Jun 2022
On the Relationship Between Explanations, Fairness Perceptions, and Decisions Jakob Schoeffer Maria De-Arteaga Niklas Kuehl FaML 83 6 0 27 Apr 2022
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies Vivian Lai Chacha Chen Q. V. Liao Alison Smith-Renner Chenhao Tan 123 188 0 21 Dec 2021
Social Norm Bias: Residual Harms of Fairness-Aware Algorithms Myra Cheng Maria De-Arteaga Lester W. Mackey Adam Tauman Kalai FaML 98 9 0 25 Aug 2021
Diversity in Sociotechnical Machine Learning Systems S. Fazelpour Maria De-Arteaga 88 38 0 19 Jul 2021
Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring Tom Sühr Sophie Hilgard Himabindu Lakkaraju 63 50 0 01 Dec 2020
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems Sandhya Saisubramanian S. Zilberstein Ece Kamar 99 22 0 24 Aug 2020
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism Keri Mallari K. Quinn Paul Johns Sarah Tan Divya Ramesh Ece Kamar FaML 65 30 0 04 Feb 2020