AI Phenomenology for Understanding Human-AI Experiences Across Eras
There is no 'ordinary' when it comes to AI. The human-AI experience is extraordinarily complex and specific to each person, yet dominant measures such as usability scales and engagement metrics flatten away nuance. We argue for AI phenomenology: a research stance that asks "How did it feel?" beyond the standard questions of "How well did it perform?" when interacting with AI systems. AI phenomenology acts as a paradigm for bidirectional human-AI alignment as it foregrounds users' first-person perceptions and interpretations of AI systems over time. We motivate AI phenomenology as a framework that captures how alignment is experienced, negotiated, and updated between users and AI systems. ...
| Authors | Bhada Yun, Evgenia Taranova, Dana Feng et al. |
|---|---|
| Primary category | cs.HC |
| Published | 9 March 2026 |
| Last updated at source | 9 March 2026 |
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