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06/23/2023
Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints
Prediction models have been widely adopted as the basis for decision-mak...
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05/30/2023
Examining risks of racial biases in NLP tools for child protective services
Although much literature has established the presence of demographic bia...
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03/22/2023
Overcoming Algorithm Aversion: A Comparison between Process and Outcome Control
Algorithm aversion occurs when humans are reluctant to use algorithms de...
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06/20/2022
Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models
This study examines issues of algorithmic fairness in the context of sys...
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05/18/2022
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
Child welfare agencies across the United States are turning to data-driv...
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04/29/2022
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation
Effective human-AI collaboration requires a system design that provides ...
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04/12/2022
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening
Algorithmic risk assessment tools are now commonplace in public sector d...
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02/17/2022
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness
Much of machine learning research focuses on predictive accuracy: given ...
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09/03/2021
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies
As algorithmic risk assessment instruments (RAIs) are increasingly adopt...
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05/11/2021
On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes
The risk of re-offense is considered in decision-making at many stages o...
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02/01/2021
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems
Recent work in fair machine learning has proposed dozens of technical de...
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01/30/2021
The effect of differential victim crime reporting on predictive policing systems
Police departments around the world have been experimenting with forms o...
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01/24/2021
Leveraging Expert Consistency to Improve Algorithmic Decision Support
Due to their promise of superior predictive power relative to human asse...
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01/02/2021
Characterizing Fairness Over the Set of Good Models Under Selective Labels
Algorithmic risk assessments are increasingly used to make and inform de...
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11/14/2020
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
Anonymized smartphone-based mobility data has been widely adopted in dev...
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06/30/2020
Counterfactual Predictions under Runtime Confounding
Algorithms are commonly used to predict outcomes under a particular deci...
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03/30/2020
Fairness Evaluation in Presence of Biased Noisy Labels
Risk assessment tools are widely used around the country to inform decis...
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02/19/2020
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
The increased use of algorithmic predictions in sensitive domains has be...
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08/30/2019
Counterfactual Risk Assessments, Evaluation, and Fairness
Algorithmic risk assessments are increasingly used to help humans make d...
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04/10/2019
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes
There is a growing body of work that proposes methods for mitigating bia...
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01/27/2019
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
We present a large-scale study of gender bias in occupation classificati...
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10/20/2018
The Frontiers of Fairness in Machine Learning
The last few years have seen an explosion of academic and popular intere...
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07/02/2018
Learning under selective labels in the presence of expert consistency
We explore the problem of learning under selective labels in the context...
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11/19/2017
Does mitigating ML's disparate impact require disparate treatment?
Following related work in law and policy, two notions of prejudice have ...
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06/30/2017
Fairer and more accurate, but for whom?
Complex statistical machine learning models are increasingly being used ...
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02/28/2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Recidivism prediction instruments (RPI's) provide decision makers with a...
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06/11/2015