(Re)framing the GenAI system shock: polycrisis, metacrisis, unicrisis?
As you may have spotted, over the last year, I’ve begun to grapple (publicly) with the question of how we make sense of the contributions that educational technology (specifically, analytics/AI empowered ed-tech) can make as we confront “the polycrisis”. This term is being used to capture the system of systems whose interactions are now presenting very sobering challenges — challenges that some now regard as existential risks (for humanity, not the Earth, which will do just fine without us). So while GenAI has obviously been a system shock for education, it feels myopic not to frame this in the context of the much larger system shocks coming our way. And from polycrisis, we move to metacrisis…
(Re)framing the GenAI system shock is how I’ve encapsulated this, and over the last month, I’m grateful to two different groups who have invited me to share current thoughts:
- Keynote address to University of Sydney Business School’s Annual Learning & Teaching Forum (25 July) – watch this for more historical context, and attention to the specifics of how GenAI is playing out in universities [replay][slides]
However, I ran out of time to get much into the reframing of GenAI with regard to the metacrisis, so this is the deeper dive:
- UTS Transdisciplinary conversation (21 August) — watch this to see some live AI demos, and if you want, jump straight to the final third on the metacrisis (@39mins) [replay][slides]
I welcome your thoughts on LinkedIn…
(Re)framing the GenAI system shock: polycrisis, metacrisis, unicrisis?
Abstract: GenAI is scoring high on the university Richter scale, with aftershocks accompanying each release. We’re witnessing the largest rollout of AI in educational history, triggered by unprecedented tech investment, extraordinary engineering advances and saturation coverage. Many hopes and fears filled the vacuum of evidence last year, which is an obvious invitation to researchers, some of which is underway here at UTS. However, amidst the urgency for fast tactical responses, we must understand AI in a larger frame. Many sober-minded people concur that humanity now finds itself at an inflection point. The disruptions to interlocking systems (ecological; political; financial; technological; medical; educational…) feel overwhelming. If we frame the challenge as grappling with this polycrisis (or is that permacrisis?), an implication is that we must equip graduates to engage with the extreme complexity of these dilemmas, harnessing AI to augment our collective intelligence. But if in fact this is also a metacrisis, this reframes our predicament more disturbingly. Do we now find ourselves in “a time between worlds” (Zak Stein)? Should we now be “hospicing modernity” (Vanessa De Oliveira)? Does neuroscience now reveal why we’re struggling to atttend relationally and holistically (Iain McGilchrist)? So, asking what we do about GenAI really leads us to deeper questions: What is the purpose of a university education? Dig deeper, and you end up asking: What does it mean to be fully human? — a question often provoked by advances in AI. (We may not resolve all of these in one session!)
Comment: I welcome this chance to share thoughts-in-progress and hear where you’re at on this. Transdisciplinary ways of thinking and working offer hope, so looking forward to finding some new soul mates!
Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, which he joined in 2014 as inaugural Director of the Connected Intelligence Centre. CIC is a transdisciplinary innovation centre inventing, piloting, evaluating and scaling data-driven personalised feedback to students, using human-centred design principles. Simon currently leads the GenAI.edu project in the UTS Education Portfolio, supporting R&D into conversational agents for teaching and learning. Prior to this he was a founding member of the UK Open University’s Knowledge Media Institute (1995-2014), working on strategic initiatives linked to major educational technology transitions, including OpenLearn (OER movement), SocialLearn (Web 2.0) and FutureLearn (MOOCs). Simon’s career-long fascination with software’s ability to make thinking visible has seen him active academically in fields including Hypertext, Design Rationale, Open Scholarly Publishing, Computational Argumentation, Computer-Supported Cooperative Work, Educational Technology and Learning Analytics/AI in education. Simon’s background in Psychology (B.Sc.), Ergonomics (M.Sc.) and Human-Computer Interaction (Ph.D.) always draws his attention to the myriad human factors that determine the effective adoption of new tools for thought, and the kinds of futures they might create at scale.
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