Tom Slater

speaker

197 appearances 1 recordings 1 series first heard May 2026 last heard 11 May

Tom Slater’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in May 2026 with 1.

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Merryn Talks Money · What If AI’s Biggest Impact Isn’t Jobs, But Minds? · 11 May 2026 podcast

I want to understand why this happened.

I don't understand the relationship between factor A and factor B. You actually interact with it and think about the output and engage with it.

Then you get the same results cognitively as if you'd just handwritten the essay.

So it's that there's something about that

effortful interaction, that seeking to gain knowledge that is the crucial part in actually developing the cognitive skills.

And if you passively let the AI do it, then it's not simply as bad as you never learn it.

But actually, you will start to mistake your ability to use AI tools with your mastery of the subject that you are trying.

And so you will gain no knowledge or little knowledge and skill in the subject that you're focusing on.

You'll just get better at using the AI, but you will confuse that with thinking that you're good at the actual topic.

Yeah, that's right.

It's because you, I think it's called the Dunning-Kruger effect.

This sort of, as you put more effort into something, if you don't know what you don't know effectively, and as you put more and more effort into it, you become more aware of how little you know of the topic.

But you completely break that effect, that understanding of the limitations of your own knowledge when you start using these tools.

And that's the real weakness, the real interruption of the learning process.

Yeah, absolutely.

So I think one way of thinking about this technology is that it's not a tide that lifts all boats.

In some ways, you can think of it as a force multiplier.

And what I mean by that is if you are experienced in a topic and have a great deal of knowledge, then these tools can massively enhance your productivity.

But a key part of it, as you highlight, is you have to be able to understand, interpret the output of these systems.

And if you're a scientist who's never struggled through a statistical analysis manually, then you're probably not going to spot the results that are conceptually meaningless that are being spat out by a machine.

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