Team Diversity Promotes Software Fairness: An Experiment on Fairness-Aware Requirements Prioritization
Cleyton Magalhes, Ronnie de Souza Santos, Bimpe Ayoola, Brody Stuart-Verner, Italo Santos

TL;DR
This study shows that diverse software teams, especially LGBTQ individuals, are more consistent and ethical in prioritizing requirements that promote fairness, highlighting the importance of diversity early in development.
Contribution
It provides empirical evidence that team diversity positively influences fairness-aware decision-making during requirements prioritization in software engineering.
Findings
Diverse teams more consistently reject fairness risks.
Diverse teams focus on inclusion and ethics.
Diversity enhances fairness-related decision quality.
Abstract
\textbf{Background:} Fairness and diversity are receiving growing attention in software engineering, particularly as AI and machine learning systems increasingly influence decision-making processes. While fairness is often examined at the algorithmic or data level, there is limited understanding of how it is addressed during the early stages of software development. Moreover, little is known about how team diversity affects fairness-related decisions in software projects. \textbf{Aims:} This study investigates how diversity in software teams influences fairness-aware behavior during requirements prioritization. \textbf{Method:} A controlled experiment was conducted with 27 pairs of software engineering students, including 13 LGBTQ diverse pairs and 14 non diverse pairs. Each pair prioritized user stories with varying fairness implications. Descriptive statistics were used to analyze…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEthics and Social Impacts of AI · Software Engineering Techniques and Practices · Mobile Crowdsensing and Crowdsourcing
