This paper interrogates the political and philosophical stakes of AI through the lens of cyborg theory cosmotechnics and glitch feminism. It advocates for a tech-positive critically situated approach to AI as a collaborator and substrate for power relations rather than an autonomous agent of harm. By rejecting the naive pause stop narratives of the human AI binary and embracing an explainable AI XAI artistic practice within embodied intersectional and community rooted engagements AI can empower diverse voices and foster ethical creativity. It starts by examining a frontier cybersecurity AI situating its framing within AI public anxiety and arguing for a new critical stance on human navigation in an AI world.
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.
Yaw Ofosu-Asare, Rebecca Ailís Nally· New Directions for Student L...· 0 citations
Within EU governing body texts, the same discursive patterns that map agency and erase the middle ground of debate in AI are found, helping to marginalise alternative perspectives from other stakeholders and prevent nuanced understandings of potential harms.
Bríd-Áine Parnell· The International Journal of...· 0 citations
A typology structured along three axes: scale of governance, type of AI, type of AI (robotic, conversational, algorithmic), and narrative role (helper, subject, opponent) is introduced, revealing an overrepresentation of conversational, antagonistic AI at micro and meso scales in fiction whereas participants overrepres...
Lisa Dewulf, Anthony Simonofski, N. B. Rosselló et al.· EGOV-CeDEM-ePart 2026· 0 citations
The “artificial intelligence (AI) gap” in journalism describes a divide between newsrooms equipped to innovate and benefit from AI and those left behind. Rather than an objective condition, this study examines this gap as a discursive construction, drawing on articulation theory. Using the
JournalismAI Academy for S...
Nadja Schaetz, Anna Schjøtt· Journalism & Mass Commun...· 0 citations
This research paper examines how generative AI is accelerating an existing crisis of trust in higher education teaching and learning. While AI is often positioned as either a transformative opportunity or an existential threat, these polarised narratives obscure deeper epistemic and pedagogical fractures. Drawing on El...
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
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