Algorithmic Fairness: Research Area — Prolific Citations Library

Discover 11 peer-reviewed studies in Algorithmic Fairness (2020–2025). Explore research findings powered by Prolific's diverse participant panel.

This page lists 11 peer-reviewed papers in the research area of Algorithmic Fairness in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (11 of 11)

Dimensions of diversity in human perceptions of algorithmic fairness

Authors: N Grgić-Hlača, G Lima, A Weller

Year: 2025

Published in: Proceedings of the 2nd ..., 2022 - dl.acm.org

Institution: Max Planck Institute, École Polytechnique Fédérale de Lausanne, University of Cambridge, The Alan Turing Institute

Research Area: Algorithmic Fairness, Human Perception, Diversity in AI Decision-Making

Discipline: Social Science, Artificial Intelligence

This study examines how sociodemographic factors and personal experience influence perceptions of fairness in algorithmic decision-making, particularly in bail decisions, highlighting the importance of diverse perspectives in regulatory oversight.

Methods: Explored perceptions of procedural fairness using surveys to assess the influence of demographics and personal experiences.

Key Findings: Impact of demographics (age, education, gender, race, political views) and personal experience on perceptions of fairness of algorithmic feature use in bail decisions.

DOI: 10.1145/3551624.3555306

Citations: 62
Lay Perceptions of Algorithmic Discrimination in the Context of Systemic Injustice

Authors: G Lima, N Grgić-Hlača, M Langer, Y Zou

Year: 2025

Published in: Proceedings of the 2025 CHI ..., 2025 - dl.acm.org

Institution: University of Maryland, Max Planck Institute, Stanford University, Cornell University

Research Area: Algorithmic Fairness, Systemic Injustice, Social Perception of AI, Algorithmic Discrimination

Discipline: Computational Social Science

The study examines how contextualizing algorithms within systemic injustice impacts perceptions of algorithmic discrimination, finding disparate effects based on participant group identity and revealing unintended consequences of such contextualization.

Methods: 2x3 between-participants experiment using the hiring context as a case-study; examined the influence of systemic injustice information and algorithms' bias perpetuation on lay perceptions.

Key Findings: Impact of systemic injustice framing and explanation of algorithmic bias perpetuation on participants' views of algorithmic fairness and discrimination.

DOI: 10.1145/3706598.3713536

Citations: 2

Sample Size: 716
Fairness Perceptions in Regression-based Predictive Models

Authors: Mukund Telukunta, Venkata Sriram Siddhardh Nadendla, Morgan Stuart, Casey Canfield

Year: 2025

Published in: ArXiv

Institution: Missouri University of Science and Technology, United Network for Organ Sharing

Research Area: Algorithmic Fairness, Healthcare AI, Decision-Making

Discipline: Artificial Intelligence

The study investigates fairness in regression-based predictive models for kidney transplantation, introducing three group fairness notions and identifying social preferences for fairness criteria, revealing biases against age groups but fairness towards gender and race groups.

Methods: Three novel fairness notions (independence, separation, sufficiency) were introduced alongside crowd feedback analysis through a Mixed-Logit discrete choice model.

Key Findings: Fairness in regression-based predictive analytics regarding group fairness criteria across social dimensions such as age, gender, and race.

Sample Size: 85
Perceived algorithmic fairness: An empirical study of transparency and anthropomorphism in algorithmic recruiting

Authors: J Ochmann, L Michels, V Tiefenbeck

Year: 2024

Published in: Information Systems ..., 2024 - Wiley Online Library

Institution: University of St. Gallen, Technische Universität München, ETH Zürich

Research Area: Algorithmic Fairness in Recruiting, Human-Algorithm Interaction, Transparency, Anthropomorphism.

Discipline: Information Systems

The study explores how transparency and anthropomorphism influence applicants' perceptions of algorithmic fairness in recruiting, revealing justice dimensions that shape these perceptions.

Methods: An online application scenario with eight experimental groups analyzing fairness perceptions using a stimulus-organism-response framework and organizational justice theory.

Key Findings: Perceptions of algorithmic fairness based on justice dimensions (procedural, distributive, interpersonal, and informational justice) and the impact of transparency and anthropomorphism interventions.

DOI: https://doi.org/10.1111/isj.12482

Citations: 65

Sample Size: 801
Do algorithms play fair? Analysing the perceived fairness of HR-decisions made by algorithms and their impacts on gig-workers

Authors: N Jabagi, AM Croteau, LK Audebrand

Year: 2024

Published in: ... International Journal of ..., 2025 - Taylor & Francis

Institution: Concordia University, John Molson School of Business

Research Area: Organizational Behavior, Human Resources, Algorithmic Fairness in the Gig Economy

Discipline: Organizational Behavior, Human Resources

DOI: https://www.tandfonline.com/doi/abs/10.1080/09585192.2024.2441448#

Citations: 12
Fairness in algorithmic management: Bringing platform-workers into the fold

Authors: N Jabagi, AM Croteau, L Audebrand, J Marsan

Year: 2024

Published in: 2024 - aisel.aisnet.org

Institution: FSA ULaval, JMSB, Concordia

Research Area: Algorithmic management, Perceived fairness, Platform work, Information Systems

Discipline: Information Systems, Social Science

DOI: https://aisel.aisnet.org/hicss-57/cl/ai_and_future_work/5

Citations: 8
Fair dealings with algorithms? Analyzing the perceived procedural fairness of managerial algorithms and their impacts on gig-workers

Authors: N Jabagi, AM Croteau, L Audebrand, J Marsan

Year: 2024

Published in: 2024 - scholarspace.manoa.hawaii.edu

Institution: Université Laval, Concordia University

Research Area: Algorithmic Fairness and Gig Economy Management

Discipline: Computational Social Science

DOI: https://doi.org/10.24251/HICSS.2024.505

Citations: 5
Perceived algorithmic fairness using organizational justice theory: An empirical case study on algorithmic hiring

Authors: G Juijn, N Stoimenova, J Reis, D Nguyen

Year: 2023

Published in: Proceedings of the 2023 ..., 2023 - dl.acm.org

Institution: Utrecht University, DEUS

Research Area: Algorithmic Fairness, Organizational Justice Theory, Algorithmic Hiring

Discipline: Human-Computer Interaction (HCI)

DOI: https://doi.org/10.1145/3600211.3604677

Citations: 20
Public perception of accuracy-fairness trade-offs in algorithmic decisions in the United States

Authors: M Mourali, D Novakowski, R Pogacar, N Brigden

Year: 2022

Published in: PloS one, 2025 - journals.plos.org

Institution: Haskayne School of Business, University of Calgary

Research Area: Algorithmic Fairness, Public Perception, AI Ethics

Discipline: Artificial Intelligence, AI Ethics, Social Psychology

Citations: 2
Transparency Fallacy: Perceived Fairness in Algorithmic Management: M. Mirbabaie et al.

Authors: M Mirbabaie, M Langer, J Rieskamp

Year: 2022

Published in: Business & Information ..., 2025 - Springer

Research Area: Algorithmic Management (AM), Perceived Fairness, Transparency, Human-Computer Interaction (HCI)

Discipline: Business, Information Systems

Citations: 2
The managerial effects of algorithmic fairness activism

Authors: B Cowgill, F Dell'Acqua, S Matz

Year: 2020

Published in: AEA Papers and Proceedings, 2020 - aeaweb.org

Institution: Columbia University, Harvard Business School

Research Area: Algorithmic Fairness in Management, Economics

Discipline: Economics

Citations: 34