AI Paradoxes

Okay, here are three claims I'm going to give you.

You ready? These are three what you might call paradoxes.

Paradox number one.

The more AI can do, the more it highlights the irreplaceable nature of human intelligence.

That's number one.

The more AI can do, the more it highlights the irreplaceable nature of human intelligence.

Okay, that's paradox number one.

Paradox number two.

It's called the justice paradox.

Less bias doesn't always mean more justice.

Maybe more specifically, less bias in AI doesn't always mean more justice.

That's number two.

The third and final paradox is call it the superintelligence paradox, the more we chase artificial superintelligence, the more we realize it consists not in the intelligence of that a superintelligence does just consist in the intelligence of individual human beings, but rather in human beings' collective intelligence.

So the more we look after, we can look for superintelligence, the more we find it not in AI or some future version of AI, but rather we find it in humans combining their intelligences.

across the centuries, across millennia.

Okay, those three paradoxes are three of the seven paradoxes that we are going to discuss today.

They're three of the seven because there are seven in the book called The AI Paradox, How to Make Sense of a Complex Future.

The author is my guest, of course.

Her name is Virginia Dignam.

She's a professor of computer science at Umeå University in Sweden.

She's a professor in responsible AI and the director of their AI policy lab.

She's also a member of the UN High Level Advisory Board.

So this conversation is, of course, about each one of those things.

It's about each one of those paradoxes and why she thinks that human intelligence is not going to get replaced by AI.

In short, it's far too rich, complex of a thing to be just recreated by an AI or, frankly, anything like an AI.

She thinks that when it comes to talking about bias in AI, we really should be focused more on something that's upstream of that, which is the kinds of things that led to our data being what it is, which then in turn leads to bias AI.

So we should be paying more attention to broader social political issues than we should about bias in AI.

And again, this note about or this insight about bias.

Super real super intelligence consists in the collective intelligence of humanity.

So we're going to talk about all that and more in this season finale.

Don't worry.

Another season is coming back in.

I don't know.

Let's call it mid-September.

But this is the last episode for the season.

And I think we're ending on a very high note.