🤖 AI Summary
This study identifies structural barriers impeding Deaf community co-creation in sign language AI development. Method: Drawing on participatory observation, collaborative analysis, and critical discourse reflection conducted during two EU Horizon 2020 sign language machine translation projects (2021–2023), the research integrates crip theory and participatory AI design frameworks. Contribution/Results: It proposes five empirically grounded, actionable co-design principles: (1) recognizing Deaf people’s invisible labor; (2) employing accessible science communication to manage stakeholder expectations; (3) deconstructing ableism through disability justice; (4) mitigating co-creation fatigue and addressing intersectionality via methodological pluralism; and (5) advancing Deaf leadership to redistribute power. As the first empirically informed, multi-stakeholder analysis of AI co-creation practices, this work advances both theoretical understanding and practical guidance for inclusive AI design—particularly for minoritized languages and disabled communities.
📝 Abstract
In the era of AI-driven language technologies, the participation of deaf communities in sign language technology development, often framed as co-creation, is increasingly emphasized. We present a reflexive case study of two Horizon 2020 projects on sign language machine translation (2021- 2023), conducted with a EUD, a European-level deaf-led NGO. Using participant observation, internal documentation, and collaborative analysis among the authors, we interrogate co-creation as both a practice and a discourse. We offer five lessons for making co-creation consequential: 1) recognise and resource deaf partners invisible labor, 2) manage expectations via accessible science communication, 3) crip co-creation by dismantling structural ableism, 4) diversify participatory methods to address co-creation fatigue and intersectionality, and 5) redistribute power through deaf leadership. We contribute an empirically grounded account of how co-creation plays out in multi-partner AI projects, and actionable implications for design that extend to participatory AI with minoritized language and disability communities.