aceWhat Can a Representation Support? Generative Artificial Intelligence and Professional Knowing in Practice
Abstract Generative Artificial Intelligence (GenAI) is increasingly embedded in professional university work, yet its significance cannot be inferred from individual prompts, outputs or nominal categories of use. This study examines how differently organised professional practices shape what practitioners do with GenAI and what changes, persists, or is reopened as GenAI-mediated work becomes part of continuing professional projects. Drawing on practitioner-led collaborative action research and the theory of prac…
Oversight that focuses on verifying final AI outputs misses how GenAI-mediated formulations persist, get reopened, or drift from a wider professional project, so disclosure labels and chat logs do not make AI participation inspectable.
Evidence
- Peer-reviewedPostdigital Science and Education2026-10-17
How should this claim be treated?
Truvace Impact Record TRV-2026-1831, v1: “What Can a Representation Support? Generative Artificial Intelligence and Professional Knowing in Practice.” Truvace, 2026-10-18. /record/TRV-2026-1831 (accessed at citation time). sha256 e8be9ec48d938a30…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1831 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.