AAAI/ACM AIES paper interviews 15 data scientists on why responsible AI practice is hard to sustain
ChinasaTOkolo · x · 2026-10-15
A team including Chinasa T. Okolo published "Moral Missions" at AAAI/ACM AIES 2026, examining why data scientists struggle to sustain responsible practice even with toolkits like Fairlearn and Aequitas.
- Method: semi-structured interviews with 15 responsible data scientists and AI practitioners across industry, government, and nonprofits in the USA, Canada, Mexico, and Nigeria, analyzed via interpretative phenomenological analysis (IPA).
- Core concept: framing responsible practice as a "moral mission" — conviction-driven technical work seeking to transform social conditions — organized into Define (selfish moral analysis, domain problematizing), Guide (working within or circumventing institutional expectations), and Nurture (care ethics, community-building).
- Takeaways: practitioners often suppress their praxis; AI ethics researchers should design tools that activate moral agency; under austerity, RDS communities should strategize outside their organizations. The paper also covers implications for generative AI adoption.
Related event: Study: Treating Responsible AI as a 'Moral Mission' Makes It Last(2 posts)→
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