Conference session

Methods in Motion: Generative AI and the Reinvention of Academic Practice

In the past two years, generative artificial intelligence (GenAI) has emerged not simply as a new tool but as a catalyst for rethinking the very foundations of teaching, research, and knowledge sharing. This panel convenes scholars, educators, and creative practitioners who are using GenAI to reshape how knowledge is created, disseminated, and valued. Moving beyond debates over authenticity, the panel explores how GenAI prompts a profound methodological shift, that challenges legacy hierarchies of expertise, authorship, and epistemology.

Panelists will discuss how GenAI can transform teaching practices, including the role that HSS can play in rebuilding trust, navigating mis/disinformation, and strengthening democracy. This theme invites work that addresses historical and contemporary challenges to knowledge, legitimacy, and public discourse.to support dynamic spaces of collaboration, experimentation, and critical inquiry.

Equally transformative are the research methodologies emerging through GenAI’s integration into scholarly workflows, addressing the benefits and challenges of integrating GenAI into research. Presenters will demonstrate how language models, image generators, and multimodal systems expand traditional methods—augmenting archival work, qualitative analysis, and creative scholarship. By partnering with AI, researchers can discover patterns, hypotheses, and connections previously inaccessible through human cognition alone. These tools require new literacies of critical engagement, interpretive skepticism, and ethical responsibility.

Finally, panelists will discuss how GenAI reshapes the circulation of scholarly knowledge itself. From AI-assisted publication to the democratization of access via automated translation and summarization, the boundaries between experts and publics are blurring. The panel contends that these changes demand not only new pedagogical techniques but a revaluation of what counts as scholarship in an age of algorithmic co-authorship.

By bringing together innovative examples from diverse disciplines, this panel positions GenAI as both a mirror and a motor for academic transformation. The discussion invites participants to imagine scholarly futures grounded in adaptability, transparency, and collaboration—where methods, like knowledge itself, remain perpetually in motion.

Sponsored by Athabasca University