S2E4 - AI Literacy, Equity, and the Future of Teaching with Dr. Jenny Hayman

AI in Action – Season 2, Episode 4Featuring Jenni Hayman

In this episode of AI in Action, Dr. Sidney Shapiro speaks with educator, researcher, and senior academic leader Jenni Hayman about the rapidly evolving role of generative AI in education. Their discussion moves beyond surface reactions to explore how institutions, faculty, and students can respond thoughtfully to technological change while maintaining academic integrity, equity, and rigor.

Jenni reflects on the pace of AI adoption in post-secondary education and the shift from fear-based conversations about academic misconduct to a more constructive focus on AI literacy and instructional redesign. She highlights the growing reality that students are often early adopters of generative AI tools, challenging traditional assumptions about expertise in the classroom.

The conversation examines several critical themes:

Lifelong learning in an AI eraWhy this moment represents a defining opportunity for educators to engage in continuous learning and model intellectual agility for students.

AI literacy and critical thinkingHow to teach students to question, triangulate, and analyze AI-generated outputs rather than rely on them uncritically. Jenni emphasizes deconstruction exercises and comparative analysis across tools as effective instructional strategies.

Equity and accessThe implications of paid versus free AI tools in the classroom, and how faculty can create a level playing field through intentional tool selection and structured assignments.

Assessment challengesHow generative AI complicates traditional grading models, particularly in online and digitally submitted coursework. The discussion explores the tension between maintaining learning outcomes and managing faculty workload.

Research, bias, and knowledge creationThe risks of AI-generated research proliferation, concerns about bias embedded in training data, and the importance of including dissenting perspectives in scholarly work.

Copyright and intellectual propertyOngoing uncertainty around ownership of AI-generated outputs and the ethical implications of training models on scraped content.

Preparing students for an AI-driven economyRather than focusing narrowly on tools, Jenni argues for foundational capabilities: adaptability, collaboration, communication, innovation, and the ability to evaluate and integrate new technologies responsibly.

The episode concludes with practical guidance for educators at different levels of technological comfort, including the importance of institutional support, peer learning, and contextual integration within disciplines.

This episode was made possible through support from the Social Sciences and Humanities Research Council of Canada and the University of Lethbridge.

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