ExplainabilityFairnessAccountabilitycs.HC
Towards Feminist Intersectional XAI: From Explainability to Response-Ability
Goda Klumbyte, Hannah Piehl, Claude Draude
May 5, 2023
arXiv.org
6 citations
Key Takeaways
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Explainability should enable action, not just understanding: The paper argues that true explainability goes beyond technical transparency to foster "response-ability"—the capacity for people to critically evaluate AI systems and actually respond to them, suggesting current XAI approaches may fall short of empowering users to challenge or resist problematic AI decisions.
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Marginalized voices must be centered in AI design: A feminist intersectional approach requires centering the perspectives of those most affected by AI systems' harms, rather than defaulting to the viewpoints of dominant groups, fundamentally shifting whose needs and concerns shape how AI systems are explained and evaluated.
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Current XAI practices may reinforce existing power imbalances: By focusing narrowly on technical explainability without addressing broader social contexts, conventional XAI research risks legitimizing AI systems without addressing the structural inequalities they may perpetuate or amplify.
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Responsible AI requires critical, not just computational, perspectives: The paper calls for integrating feminist, decolonial, and intersectional thinking into AI research—suggesting that technical solutions alone are insufficient for addressing how AI systems affect different communities differently.
Abstract
This paper follows calls for critical approaches to computing and conceptualisations of intersectional, feminist, decolonial HCI and AI design and asks what a feminist intersectional perspective in HCXAI research and design might look like. Sketching out initial research directions and implications for explainable AI design, it suggests that explainability from a feminist perspective would include the fostering of response-ability - the capacity to critically evaluate and respond to AI systems - and would centre marginalised perspectives.