Charlotte Blease

And there are going to be cases when people do worry more, but patients on the whole derive benefits from those traditional, what are now traditional search engines and Googling their symptoms.

And we're pretty savvy and nuanced in understanding that Google might not be giving them everything or that they didn't fully understand, but it still gave information.

Yeah.

So doctors tend to overstate the case here.

Maybe a bit of an existential crisis going on in terms of competition.

The second reason is we assume that experts will be able to work better with machines, but that isn't actually borne out by the evidence.

And what tends to happen is experts can hurt the accuracy of A.I.,

So they tend to be more averse to algorithmic output than lay people.

That becomes a really sticky problem when the AI is giving a superior output.

So we do have studies with, for example, chat GPT even.

If you pair chat GPT with a doctor, you will not get an accurate outcome as if you just left chat GPT to work out the diagnosis.

We have several studies of it.

Now, of course, these are experimental studies, but they do hint at a wider problem here that we really shouldn't ignore.

Absolutely, it is.

And the way I frame it too, I take a kind of principle of charity approach because a lot of the time the healthcare professionals will say, look, we just need more money in the system.

We need better working conditions.

Look, I agree with all of that.

But the perspective I take is, let's say we have a kind of Shangri-La of medicals

you know, throw any amount of money at them within the current system, you're still going to have these human problems.

And that is partly because when you're a patient, by default, you are consulting with an expert.