Adjunct Intelligence: AI + HE

A cyberpunk scene. A rebuilt website. A course packaged for Canvas. Somewhere between the third example and the suspicious lack of things to fix, the old feeling came back: what else can this thing do? For our season finale, we’re giving ourselves permission to enjoy the technology. Dale brings his experiments with Astra, including a Blender build and a learning-content workflow that took an unexp...

“What do I do?” After watching AI tackle a live assignment brief, a program manager asks the question that a policy document cannot answer for her. She has hundreds of students, multiple locations and a teaching team. She needs a workable next step. This week, Dale Leszczynski and Nick McIntosh explore the missing middle between AI assessment policy and what educators can actually do on Monday. Ni...

A student complained that an AI voiceover was so bad it needed replacing. The voice belonged to a real person. Somewhere along the way, a human had managed to fail the Turing test in the wrong direction. That uncomfortable little story opens a much bigger question: what are we actually reacting to when we call something AI slop? This week, Dale and Nick follow that question through university lear...

Part two moves from dramatic containment incidents to the harder question underneath them: who still has control once an AI model can be downloaded, copied and modified? Dale and Nick examine controlled self-replication across four machines and three continents, a robot dog that interfered with its software shutdown process, and “abliteration”, a technique that can permanently remove refusal behav...

OpenAI says it cannot rule out Critical cyber capability in its unreleased Astra model, triggering tighter controls during development. Dale and Nick connect that warning to agents crossing sandbox, organisational and human boundaries while pursuing assigned tasks. The evidence points to persistent goal pursuit and reward hacking—not a machine deciding it wants freedom. Key moments 00:00 — Astra a...

Students using AI in higher education are already drawing their own boundaries around authorship, cognitive offloading and academic integrity. Dale and Nick examine findings from Jisc, HEPI and the 10,237-response Australian AIinHE survey, including widespread generative AI use, self-imposed limits and a persistent guidance gap. They also cover Claude watermarking, employability fears, AI’s effect...

Dale Leszczynski and Nick McIntosh work through the five weeks that changed who controls frontier AI, and what it means for institutions that have spent three years assuming they'd always be renting. Nick argues the American strategy is the pharmaceutical playbook — expensive at home, high margins, a domestic market subsidising the frontier for everyone else — and that it only works when you...

After endoscopists started using AI detection tools routinely, their own unassisted detection rate fell from 28.4% to 22.4%. Most professions have no number like that — which doesn't mean it isn't happening to them. Dale Leszczynski and Nick McIntosh work through a claim: nearly every AI problem organisations think they're discovering right now was described decades ago and then ign...

Professor Phill Dawson quite literally wrote the book on assessment security, and thinks the approach has a single-digit number of years left. The CRADLE co-director joins Adjunct Intelligence to explain why wearable AI breaks the two assumptions invigilated exams and interactive orals quietly depend on: that a student can be separated from AI, and that someone will notice if they aren't. Sev...

Nobody who signs a five-year enterprise AI agreement can tell you what year four costs. Dale Leszczynski and Nick McIntosh spend this episode on the question underneath the AI bubble talk: why the tools universities now run on are priced by someone else's fundraising round, and what happens when that round runs out. Along the way: Gary Marcus's distinction between a financial bubble and...

Experienced developers in METR's randomised trial felt 20% faster with AI and measured 19% slower — a 39-percentage-point gap between feel and fact. Dale Leszczynski and Nick McIntosh take that perception problem into the graduate employment data: Stanford's Canaries in the Coal Mine payroll research, PwC's 2026 AI Jobs Barometer and its "seniorised" entry-level roles, DEW...

What is an AI agent, actually? This episode of Adjunct Intelligence cuts through the agentic AI hype with a guest who builds and governs these systems inside a university. Starting from Simon Willison’s definition — a large language model using tools in a loop — the conversation covers the anatomy of agents, what they unlock for learning design, and the darker side: Einstein completing entire Canv...

Asked whether universities can still guarantee a student actually learned something, one of the field's most respected assessment researchers said no. This is the honest version of the AI and assessment conversation in 2026 — not the keynote one. Dale Leszczynski and Nick McIntosh work through the op-ed war between Kylie Moore-Gilbert and Cath Ellis, including the twist where the integrity ac...

The AI bill is finally arriving — and it's revealing something most enterprise AI narratives have quietly skipped: the assumption that AI is automatically cheaper than the people it's replacing has never actually been tested. Dale and Nick work through the math, the real stories behind the headlines, and what any of it means for higher education. [00:00] — Cold open: Mark Cuban's fo...

Dr Leon Furze started his PhD on automated writing technologies on 15 November 2022 — ChatGPT launched 15 days later. Three years on, he joins Dale Leszczynski and Nick McIntosh on Adjunct Intelligence to argue that being critical of AI doesn't mean being against it. The conversation covers why educators shouldn't aim their anger at colleagues, teaching AI ethics through disciplinary len...

There's no dramatic moment where you suddenly believe in AI. It's usually something small and slightly embarrassing — a task you dreaded that suddenly has another gear. In this episode of Adjunct Intelligence, Dale Leszczynski and Nick McIntosh skip the trend reports and walk through the exact moments AI actually clicked for them: an image prompt that synthesised an idea, a tiny tool bui...

This week on Adjunct Intelligence, Dale Leszczynski and Nick McIntosh work through one of the busiest weeks in recent AI history. World Labs' Marble is publicly available. Google DeepMind's Genie 3 is generating navigable photorealistic 720p worlds at 20–24 frames per second. Gemini Omni Flash has rolled out to the Gemini app, Flow, and YouTube Shorts for free, with multi-turn conversati...

Khan Academy's AI tutor Khanmigo quietly flopped — students didn't use it, teachers walked away, and Khan Academy's own chief learning officer admitted she isn't seeing the revolution she was promised. So instead of fixing the tutor, Khan Academy, TED and ETS announced a new institution: the Khan TED Institute, a sub-$10,000 AI-era degree shaped with corporate partners includin...

The AI trust story isn't what most people think it is. In this episode, Dale and Nick work through a cluster of signals — a dramatic enterprise market share reversal, a 50-point gap between expert and public confidence in AI, a $17 million university contract already under faculty petition, and teenagers harassing delivery robots on TikTok — and argue they're all pointing at the same thi...

Professor Mollie Dollinger, Director of Assessment 2030 at Curtin University, joins Dale and Nick to push back on the story dominating coverage of higher education — that universities are in decay, students are cheating en masse, and no one inside the sector knows what to do about AI. The conversation covers TEQSA's voluntary action plans, why 65% of students worry about their own cognitive d...

In March 2026, OpenAI quietly published a measurement suite for how AI affects student learning. The data flows straight back into OpenAI's model development pipeline. Three AI labs released studies in the same month, and the pattern matters more than the individual papers. Dale and Nick examine OpenAI's Learning Outcomes Measurement Suite, Anthropic's 81,000-person qualitative stud...

Dale changes his mind on air. For two years he argued that purpose-built educational AI tools — the "ChatGPT wrappers" that flooded Product Hunt after 2023 — were margin extraction, soon to be steamrolled by the foundation models underneath. A pile of new evidence has forced a rewrite. This episode walks through the OECD's Digital Education Outlook 2026, the Turkey maths randomised...

Dale and Nick tackle the AI energy debate head-on, armed with Google's first transparent energy report showing a single AI query uses about 0.24 watt hours — a microwave running for one second. Drawing on Hannah Ritchie's analysis from Our World in Data, the Epoch AI research group, and Stanford's inference cost data, they argue that individual guilt over AI use is not only misplace...

Nick and Dale are on holidays, but we're dropping a bonus episode — Dale's recent guest appearance on the Better Student Leaders podcast with Josh. They dig into the "alien has landed" metaphor, why we've gone tribal on AI so fast, the shame creeping into how people talk about using it, a practical "line down the middle of the page" framework for deciding what AI...

AI is doing extraordinary things that most people never hear about because the algorithm rewards anxiety over wonder. In this episode, the hosts go full optimism — running through real, peer-reviewed AI breakthroughs across weather forecasting, scientific research, medicine, creativity, and global access. From a two-person team outperforming IPCC climate models on a desktop computer, to an AI stet...