Racing the Clock: Education's Response to AI's Rapid Rise

AI is transforming knowledge, learning and work at an unprecedented pace. This one-day conference brings together educators, researchers, students and industry leaders to explore how education can respond with urgency, purpose and leadership.

The future students are being prepared for is changing

AI is rapidly changing the nature of work, reshaping the skills graduates need, the ways knowledge is produced, and the roles humans will play alongside intelligent technologies. The pace of change creates an urgent challenge for education: students are being prepared for futures that are already shifting beneath them.

Students already feel this shift. Many are using AI daily, often more fluently than their educators. Yet there is growing empirical evidence of a learning-performance paradox: while AI can enhance short-term task performance, it may also undermine deeper learning, including cognitive growth, knowledge transfer, critical judgement, and metacognitive development. This creates an urgent need for education systems to move beyond simply allowing or prohibiting AI use and instead focus on helping students learn with AI in ways that strengthen, rather than replace, human capability.

Why now, and why together

National conversations are already pointing to the need for a coordinated, forward-looking response that prioritises human capability, agency, and ethical engagement with AI. Educational institutions can no longer afford fragmented or reactive approaches; the question is not whether AI will shape learning and work, but how deliberately and responsibly we respond.

Racing the Clock is a moment to bring that conversation into the same room to move beyond fragmented responses, surface what is genuinely working, confront what is not, and start building a shared response across sectors.

Conference program

The day is designed to move from framing to evidence to action, combining 2 national keynotes, a cross-sector panel, a debate with student representation on both sides, concurrent facilitated roundtables, a rapid-fire innovation showcase and an extended networking session.

8:30–9am | Registration and networking

Arrival and informal networking.

9:00–9:05am | Welcome and Acknowledgement of Country

MC: Associate Professor Hassan Khosravi

The MC opens the day and welcomes participants.

9:05–9:15am | University welcome and formal opening

Professor Kris Ryan

A welcome from UQ leadership, situating the event within institutional priorities and the broader strategic importance of AI in education.

9:15–9:25am | Setting the scene: why we must act now

Associate Professor Hassan Khosravi

An opening framing in three moves: how AI is changing the nature of work and the skills graduates will need; what that shift means for education and where current responses fall short; and how we might respond with urgency, purpose and leadership. The session closes by walking through the events of the day and how each session contributes to that response.

9:20–10:10am | Keynote: Knowing what you don't know, when the machine never says so

Professor Jason Lodge, The University of Queensland

This keynote examines what happens to learning when AI systems answer with unfailing confidence. It draws on evidence about metacognition, self-regulation and the learning-performance paradox to consider how educators can help students judge what they actually know, and design learning that strengthens rather than replaces human capability.

10:15–11am | Panel: Responding to AI, perspectives from across the education ecosystem

Moderated by Professor Greg Winslett

This panel brings together voices from higher education, schools, government and industry to examine how different parts of the sector are responding to AI. It surfaces where responses diverge, where they could align, and what a coordinated, forward-looking response would require of each of them.

11:00–11:15am | Morning tea

11:15am – 12:00noon | Debate: AI should play a central role in marking student work and providing feedback

Moderated by Associate Professor Hassan Khosravi

Assessment is under pressure from growing demands for timely feedback, scalable moderation, personalised support and credible evidence of learning. This debate asks whether AI should play a central role in marking and feedback, and whether doing so would improve consistency and reduce workload, or weaken human judgement, fairness, accountability and trust in educational decisions.

The session runs as a three against three debate, with a student representative on each side of the argument.

11:15 – 12:45 pm | Concurrent: facilitated roundtable discussions

Facilitated by Dom McGrath

Running in parallel with the debate and the AI in Action panel, these facilitated roundtables give participants a chance to work through the issues of the day in small groups and to contribute their own institutional and classroom experience.

12:00–12:45 pm | Panel: AI in Action

Moderated by Associate Professor Rachel Fitzgerald

This panel brings together educators, researchers and students who are actively using AI in real teaching and learning contexts. Moving beyond speculation, the session focuses on what is actually working, where AI is falling short, and what remains unresolved.

Panellists share practical examples across feedback, assessment and classroom practice, alongside student perspectives and emerging evidence.

12:45–1:30pm| Lunch and networking

Connect with colleagues, discuss and explore innovations with and in response to AI.

1:30–2:15pm | Keynote: The role of AI in supporting learning and educational research

Professor Ryan Baker, Adelaide University

This keynote traces the evolution of AI in education, from early learning analytics and intelligent tutoring systems to today's generative AI tools, and explores what lies ahead. Drawing on large-scale research and real-world deployments, it highlights what we have learned about how AI can support learning, where its impact has been limited, and the challenges of scaling these systems responsibly.

2:15–3:45pm | Showcasing AI innovation

Moderated by Associate Professor Amy Hubbell

Short, five-minute presentations and posters from students and staff sharing emerging AI initiatives, research projects, classroom practices and early-stage ideas. Contributors were invited through an expression of interest to present concise snapshots of their work, with a focus on practical insights, lessons learned and opportunities for collaboration.

3:45–3:55pm | Closing reflections and next steps

Professor Suzanne Le Mire

A short close drawing the threads of the day together and setting out what happens next.

4:00–5:00pm | Networking and social

The day concludes with an informal networking session, a chance to continue conversations, connect with presenters and explore potential collaborations, turning insights into ongoing dialogue and action.

*Program subject to change