Moving beyond Principles: Identifying Actionable AI Fairness Practices

• URL: http://arxiv.org/abs/2604.18502v1
• Date: Mon, 20 Apr 2026 16:53:14 GMT
• Title: Moving beyond Principles: Identifying Actionable AI Fairness Practices
• Abstract summary: This study addresses the principles-to-practice gap in AI fairness governance.<n>We derive a structured set of AI fairness practices organized by obligation degree and organizational role.<n>The matrix provides dynamic, role-specific guidance to support implementation and sustainment of AI fairness.
• Score: 3.509273901643457
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Because artificial intelligence (AI) increasingly mediates organizational work, fairness has become a critical governance challenge. Existing frameworks often prioritize abstract ethical principles rather than fairness-specific ones and lack actionable guidance across the entire AI lifecycle. This study addresses the principles-to-practice gap in AI fairness governance. We develop actionable AI fairness practices and draw on a socio-technical and praxiological lens, conducting discourse and thematic analyses of 60 academic, policy, and practitioner sources. From these analyses, we derive a structured set of AI fairness practices in a comprehensive, AI lifecycle-spanning matrix organized by obligation degree and organizational role. The matrix provides dynamic, role-specific guidance to support implementation and sustainment of AI fairness. By extending the AI fairness beyond abstract principles to operationalized, actionable practices, we contribute to IS scholarship and offer a modular governance scaffold.

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