Governing Generative AI Use through FAIR User Experience: Designing for Interactional Integrity
Abstract
Prevailing HCI paradigms in GenAI design prioritize harm prevention and abstract principles, such as transparency, but often neglect the embodied and interactive ways in which AI shapes user behavior and identity. This paper advocates for a fundamental shift, positioning “interactional integrity” as the central design goal and moving beyond a reductionist focus on harm minimization. We use the FAIR framework—grounded in the existential principles of Freedom, Authenticity, Intentionality, and Responsibility—to cultivate interactional integrity through interface-level affordances. By embedding these principles into user experience, the FAIR framework offers a systematic approach for integrating responsible AI into design practice, ensuring that responsible use becomes a lived interaction rather than a regulatory afterthought.
Fields of Study & Subjects
Research Data Management Practices
Scientific Computing and Data Management
Digital and Traditional Archives Management
Publication details
- Journal / source
- Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
- Publisher
- Hawaii International Conference on System Sciences
- Publication date
- 1 January 2026
- Language
- EN