Fairness Across Fields: Comparing Software Engineering and Human Sciences Perspectives

2026-03-29

AI Summary

This study addresses the limited understanding of algorithmic fairness in software engineering, which has predominantly emphasized formal and statistical perspectives while overlooking structural inequities and power dynamics. By systematically comparing conceptualizations of “fairness” across disciplines, the work analyzes 45 software engineering and 25 humanities publications through qualitative comparative methods. It reveals that software engineering approaches typically focus on distributive outcomes, whereas humanities scholarship foregrounds historical and structural injustices. Building on this contrast, the paper proposes integrating contextual and historical perspectives into the design of fair algorithms. This interdisciplinary reframing aims to enrich the theoretical foundations of algorithmic ethics and deepen awareness of the societal implications of technical systems.

Abstract

Background. As digital technologies increasingly shape social domains such as healthcare, public safety, entertainment, and education, software engineering has engaged with ethical and political concerns primarily through the notion of algorithmic fairness. Aim. This study challenges the limits of software engineering approaches to fairness by analyzing how fairness is conceptualized in the human sciences. Methodology. We conducted two secondary studies, exploring 45 articles on algorithmic fairness in software engineering and 25 articles on fairness from the humanities, and compared their findings to assess cross-disciplinary insights for ethical technological development. Results. The analysis shows that software engineering predominantly defines fairness through formal and statistical notions focused on outcome distribution, whereas the humanities emphasize historically situated perspectives grounded in structural inequalities and power relations, with differences also evident in associated social benefits, proposed practices, and identified challenges. Conclusion. Perspectives from the human sciences can meaningfully contribute to software engineering by promoting situated understandings of fairness that move beyond technical approaches and better account for the societal impacts of technologies.

Problem

• algorithmic fairness
• software engineering
• human sciences
• structural inequality
• societal impact

Innovation

• algorithmic fairness
• cross-disciplinary comparison
• situated fairness
• structural inequality
• ethical software engineering