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When machine-learning algorithms are used in high-stakes decisions, we want to ensure that their deployment leads to fair and equitable outcomes.
Learning from Coarse Information: Biased Contests and Career Profiles
Meyer, Margaret A. (1991) · 1991
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The Self‐Perpetuation of Biased Beliefs
Suen, Wing (2004) · 2004
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Judgmental forecasting: A review of progress over the last 25 years
Lawrence, Michael, Paul Goodwin, Marcus O’Connor, and Dilek Önkal (2006) · 2006
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Bayesian Persuasion
Kamenica, Emir and Matthew Gentzkow (2011) · 2011
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Big data’s disparate impact
Barocas, Solon and Andrew D Selbst (2016) · 2016
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Chouldechova, Alexandra (2016) · 2016
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Inherent trade-offs in the fair determination of risk scores
Kleinberg, Jon, Sendhil Mullainathan, and Manish Raghavan (2016) · 2016
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Algorithmic Decision Making and the Cost of Fairness
Corbett-Davies, Sam, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq (2017) · 2017
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The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables
Lakkaraju, Himabindu, Jon Kleinberg, Jure Leskovec, Jens Ludwig, and Sendhil Mullainathan (2017) · 2017
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Ban the Box, Criminal Records, and Racial Discrimination: A Field Experiment
Agan, Amanda and Sonja Starr (2018) · 2018
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The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning
Corbett-Davies, Sam and Sharad Goel (2018) · 2018
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Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them
Dietvorst, Berkeley J., Joseph P. Simmons, and Cade Massey (2018) · 2018
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Judging Risk
Garrett, Brandon L. and John Monahan (2018) · 2018
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Big Data and Discrimination
Gillis, Talia B and Jann L Spiess (2018) · 2018
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A detailed treatment of Doob’s theorem
Miller, Jeffrey W (2018) · 2018
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Is algorithmic affirmative action legal
Bent, Jason R (2019) · 2019
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Beliefs about Gender
Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, and Andrei Shleifer (2019) · 2019
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From Soft Classifiers to Hard Decisions: How fair can we be?
Canetti, Ran, Aloni Cohen, Nishanth Dikkala, Govind Ramnarayan, Sarah Scheffler, and Adam Smith (2019) · 2019
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Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments
Green, Ben and Yiling Chen (2019) · 2019
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Human Decision Making with Machine Assistance: An Experiment on Bailing and Jailing
Grgić-Hlača, Nina, Christoph Engel, and Krishna P Gummadi (2019) · 2019
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Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability
Kleinberg, Jon and Sendhil Mullainathan (2019) · 2019
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Paradoxes in Fair Computer-Aided Decision Making
Morgan, Andrew and Rafael Pass (2019) · 2019
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Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care
Mullainathan, Sendhil and Ziad Obermeyer (2019) · 2019
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The Algorithmic Automation Problem: Prediction, Triage, and Human Effort
Raghu, Maithra, Katy Blumer, Greg Corrado, Jon Kleinberg, Ziad Obermeyer, and Sendhil Mullainathan (2019) · 2019
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Algorithmic Risk Assessment in the Hands of Humans
The Role of Beliefs in Driving Gender Discrimination
Coffman, Katherine B., Christine L. Exley, and Muriel Niederle (2021) · 2021
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Proposal for a regulation of the European parliament and of the council laying down harmonised rules on artificial intelligence
European Commission (2021) · 2021
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The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
Fogliato, Riccardo, Alexandra Chouldechova, and Zachary Lipton (2021) · 2021
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Human-AI Complementarity in Hybrid Intelligence Systems: A Structured Literature Review
Hemmer, Patrick, Max Schemmer, Michael Vössing, and Niklas Kühl (2021) · 2021
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Eliciting Human Judgment for Prediction Algorithms
Ibrahim, Rouba, Song-Hee Kim, and Jordan Tong (2021) · 2021
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Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies
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Stevenson, Megan and Jennifer L. Doleac (2019) · 2019
Cited alongside, same era.
The Allocation of Decision Authority to Human and Artificial Intelligence
Athey, Susan C, Kevin A Bryan, and Joshua S Gans (2020) · 2020
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From predictive to prescriptive analytics
Bertsimas, Dimitris and Nathan Kallus (2020) · 2020
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A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
De-Arteaga, Maria, Riccardo Fogliato, and Alexandra Chouldechova (2020) · 2020
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Measuring algorithmic fairness
Hellman, Deborah (2020) · 2020
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A right to a human decision
Huq, Aziz Z (2020) · 2020
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Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment
Imai, Kosuke, Zhichao Jiang, James Greiner, Ryan Halen, and Sooahn Shin (2020) · 2020
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Lai, Vivian, Chacha Chen, Q. Vera Liao, Alison Smith-Renner, and Chenhao Tan (2021) · 2021
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Algorithmic design: Fairness versus accuracy
Liang, Annie, Jay Lu, and Xiaosheng Mu (2021) · 2021
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Fragile Algorithms and Fallible Decision-Makers: Lessons from the Justice System
Ludwig, Jens and Sendhil Mullainathan (2021) · 2021
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Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds
Mishler, Alan, Edward H Kennedy, and Alexandra Chouldechova (2021) · 2021
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Human and Machine: The Impact of Machine Input on Decision-Making Under Cognitive Limitations
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The Effect of Group Identity on Hiring Decisions with Incomplete Information
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Discrimination Against Doctors: A Field Experiment
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Approaching the human in the loop–legal perspectives on hybrid human/algorithmic decision-making in three contexts
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Why do we Discriminate? The Role of Motivated Reasoning
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“Un”Fair Machine Learning Algorithms
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The input fallacy
Gillis, Talia B (2022) · 2022
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The Impact of Algorithmic Tools on Child Protection: Evidence from a Randomized Controlled Trial
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Race-aware algorithms: Fairness, nondiscrimination and affirmative action
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Algorithm Reliance Under Pressure: The Effect of Customer Load on Service Workers
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