Problem
Research questions and friction points this paper is trying to address.
generative AI
mixed-ability teams
disability identity
AI adoption
research collaboration
Reflections and Recommendations on AI Adoption Practice from a Mixed-Ability Research Group
🤖 AI Summary
This study addresses the complex dynamics faced by mixed-ability research teams when adopting generative AI, including divergent motivations, identity homogenization, privacy risks, and the additional burdens imposed by the “disability tax” and “crip time.” Drawing on semi-structured interviews with five team members and qualitative content analysis, it offers the first disability-informed account of motivations, challenges, and practices surrounding generative AI use in research settings. The work proposes an AI adoption framework that balances inclusivity with autonomy and distills five laboratory-specific guidelines for AI integration. These guidelines effectively support teams in enhancing research productivity while safeguarding members’ identity diversity, agency, and information security.
📝 Abstract
Generative AI tools have recently been rapidly adopted by academics in mixed-ability research teams for both personal and professional tasks. While previous work on adoption of AI-based workflows has focused on collaboration and productivity, the perceptions of AI use within research teams remains divided. Through qualitative analysis of interviews of the five members of our mixed-ability research team, we discuss the motivations, challenges, and practices surrounding the use of generative AI in our lab. We reflect on experiences that shaped recommendations for balanced AI use that enable mixed-ability team workflows: (1) managing disability tax & crip time, (2) homogenizing identity, (3) risk disclosure of private information, (4) self-experimentation and miscellaneous tasks, and (5) information seeking. We build upon these themes to present AI practice recommendations we established for our lab to promote AI workflow adoption while preserving agency and disability identity.
Innovation
Methods, ideas, or system contributions that make the work stand out.
generative AI
mixed-ability teams
disability inclusion
AI ethics
qualitative analysis
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