The role of team diversity in AI systems development

2026-03-08

AI Summary

This study addresses the critical gap in understanding how team diversity influences fairness in AI systems, which are often exacerbated by data and design flaws that perpetuate social inequities. Drawing on grounded theory, the authors conducted in-depth interviews with 25 practitioners across four AI development teams at a major software company in Brazil and Portugal, working on projects spanning education, energy, accessibility, and facial recognition. The research systematically identifies six key roles that social diversity plays in AI development: recognizing bias, infusing empathy, confronting systemic discrimination, fostering inclusive decision-making, serving as a safeguard against bias, and broadening problem-solving perspectives. Findings demonstrate that diverse teams significantly enhance the fairness and inclusivity of AI systems and offer actionable pathways for integrating fairness into software engineering practices.

Technology Category

Philosophy and Ethics of AI: Bias, Fairness & EquityMachine Learning: Ethics, Bias, and FairnessHumans and AI: Teamwork, Team formation

Application Category

Social Networks and Social Media: Fairness and bias in social network and social media analysisEconomics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systemsUser Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

The widespread integration of AI technologies has intensified concerns about fairness and bias, as these systems often perpetuate societal inequalities through flawed data and design choices. While software engineering research has largely concentrated on technical solutions, such as improving datasets and models, the social dynamics that shape AI outcomes remain underexplored. This study investigates the role of team diversity in the development of AI systems. Drawing from the experience of four AI focused teams working in a large software company operating in Brazil and Portugal, and collaborating with global clients, the study explores how diverse teams influence the development of AI systems. Using Grounded Theory, we conducted 25 interviews with software professionals involved in projects spanning domains such as education, energy, accessibility, and facial recognition. Although our study is conducted in an organizational setting, the variety of projects, from regional to multinational, ensures exposure to global development practices and diverse team dynamics, bringing a variety of perspectives into our findings. Our analysis revealed six key roles that team diversity played in AI development: diversifying perspectives for bias identification, bringing empathy to AI development, addressing systemic discrimination, supporting inclusive and participatory decision making, using diversity as a safeguard against bias, and fostering broadened thinking in problem solving. These findings highlight the importance of incorporating diverse perspectives in AI projects and offer practical recommendations for integrating fairness considerations into software development practices.

Problem

• AI fairness
• team diversity
• bias in AI
• social dynamics
• inclusive AI development

Innovation

• team diversity
• AI fairness
• bias mitigation
• Grounded Theory
• inclusive AI development