The Skills That Don't Show Up in Completion Rates

Students using AI tools are submitting more work, faster, with fewer surface errors. That looks like progress. What it does not show is whether a student can hold an argument together under pressure, reason from incomplete evidence, or sit with a problem long enough to actually think it through.

Those skills develop through struggle. AI tools, used without structure, remove the struggle. The productivity gain is immediate and visible. The capability loss is gradual and largely invisible until graduates enter professional roles and the scaffolding is gone.

The research is still catching up to the scale of adoption. But the pattern is already legible to anyone paying close attention to how students are working, and how they are reasoning when the tool is not in front of them.

What Most Institutions Are Getting Right, and What They Are Skipping

Most universities are doing the sensible things. Updating academic integrity policies. Running staff training on AI tools. Piloting new assessment formats. These are reasonable responses to a real and fast-moving situation.

What most are not yet doing is asking the harder question: what cognitive habits are we allowing students to outsource, and what does that cost them over time? That question does not fit neatly into a policy review. It requires a different kind of institutional conversation.

The institutions already asking it tend to be the ones who noticed something odd in how their students were working, before they had the language to describe it precisely.

What Steve Covers With Education Audiences

Steve speaks to what AI dependency actually does to reasoning, specifically in learning contexts where the habit of reaching for a tool can form before the underlying skill is established. He draws on cognitive science, his own background in software, and direct work with organizations navigating these questions.

For higher education audiences, the talk typically covers how to distinguish useful AI integration from dependency that erodes graduate capability, and what institutional habits tend to protect the latter without intending to.

The goal is not to produce an anti-AI argument. It is to give academic leaders a clearer picture of what they are trading when they adopt these tools at speed, so the decisions they make are actually informed ones.

Topics for Education audiences

Steve speaks to education organizations on the following topics. Each can be delivered as a keynote, half-day workshop, or executive briefing.

Who books Steve

Vice-Chancellors, academic directors, L&D leads at universities, conference organisers for higher education events.

If you are planning an event and want to discuss whether Steve's work is a good fit, the fastest route is a short conversation. No pitch deck required.