The Trickster Turn: Decolonial Epistemology for AI in Leadership Education.
Unknown authors
Sep 2026· New Directions for Student Leadership· 0 citations· 19 references
Medicine
TL;DR
Trickster AI is developed, a speculative pedagogical framework informed by Ananse, Èṣù, and Māui, where contradiction, delay, reversal, humor, and refusal expose hidden premises of authority.
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.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026
