Year: 2026
Type: article
Abstract: This paper critiques generative AI in leadership education as an instrument of optimization, where summarizing, coaching, and personalizing risk producing fluent, compliant leadership subjects while narrowing ethical inquiry. It develops Trickster AI, a speculative pedagogical framework informed by Ananse, Èṣù, and Māui, where contradiction, delay, reversal, humor, and refusal expose hidden premises of authority. The paper reframes friction as culturally situated and politically consequential; develops refusal as epistemic, procedural, and care-based practice; and proposes Leadership Through Rupture, where contradiction becomes information. It also addresses cultural extraction through consent, co-design and Indigenous data governance. A companion paper details implementation.
DOI: 10.1002/yd.70071
Authors: Yaw Ofosu‐Asare, Rebecca Ailís Nally
Institution: RMIT University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $3,140
Funder: RMIT University
OpenAlex ID: W7208753801