Fairness-First Design Thinking for Software Architecture

2026-04-20

AI Summary

This work addresses the frequent neglect of fairness concerns in digital systems during software architecture design. To bridge this gap, it proposes a fairness-driven design thinking approach that systematically integrates fairness into the software architecture process for the first time. The method employs composite architectural views to manage fairness as a cross-cutting concern and combines fairness theories with contextual awareness. Implemented and evaluated in a graduate-level course, this approach has yielded a “fairness-first” design workflow tailored to software architecture. It also distills key practical insights for addressing fairness across both problem and solution spaces, offering actionable guidance for education and professional practice in architecting equitable systems.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Machine Learning: Ethics, Bias, and Fairness
• Game Theory and Economic Paradigms: Fair Division

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Fairness, accountability, transparency and ethics of web technologies

Abstract

Fairness issues often remain hidden in digital systems, making them difficult to detect and even more difficult to address. In this study, we introduce a fairness-first Design Thinking (DT) approach to support addressing fairness concerns in software architecture (SA) design. We implemented our approach in a graduate-level course where students executed all steps of our DT approach as part of an assignment. We analyzed the assignment data to reflect on the implications for applying the DT approach in SA and teaching the DT approach in SA education. As a result of this study, we provide (i) a DT approach for SA, (ii) implications of the DT approach on handling fairness in both problem and solution spaces, and (iii) implications for education. Our reflections highlight that fairness theory and context identification are essential for a holistic, fairness-first design. We propose the use of composite views to address cross-cutting concerns such as fairness. In the future, we will update the course material to provide end-to-end fairness traceability in SA, helping students to understand how fairness concerns can be translated into actionable design decisions.

Problem

• fairness
• software architecture
• Design Thinking
• digital systems
• fairness concerns

Innovation

• fairness-first
• Design Thinking
• software architecture
• composite views
• fairness traceability