Arvind Narayanan

So, I mean, I'm quite struck with, you know, you mentioned Zach Corman and, you know, obviously I've done some work with Marcus Hutchins and the other side of the argument, say someone like Joshua Sachs.

And he's influenced the latest paper from Arvind Narayanan and Saish Kapoor in their AI is normal technology framework, which goes way beyond cyber.

But they've done something whose intent I applaud, which is like try and get these two groups talking constructively, you know, safety and security talking constructively.

I don't agree with a lot of what's in it, but I agree with some of it.

0% to 51.1%.

Arvind Narayanan and Sayesh Kapoor pointed out that the test contained only primes, so a shift in which answer the model leaned toward could look like a change in mathability.

That's a fair correction, though a product built on those prompts would still have behaved differently in June.

Now check your own code.

And so he's had, uh, uh, he's had Jensen Wong.

He said, he said, uh, Arvind Narayanan, the guy, the AIS normal technology guy.

He's yeah.

Yeah.

This is either a real citation that supports the point or it's not.

And so we see here someone who didn't catch it getting really embarrassed Right? And again, when we see sharp edged with motion with AI agents, here's a paper from Arvind Narayanan's group at Princeton, where they're studying reliability of AI agents.

And again, we're seeing that these agents are not always consistent and robust.

And it has yielded, as I'm just quoting here from the bottom of their abstract, recent capability gains have only yielded small improvements in reliability.

The more your job is just doing the thing, the more at risk you are.

So there's um, there's a professor at Princeton University in the US, um, called Arvind Narayanan, and he and a colleague or a couple of colleagues have done some really interesting research, and they come up with this framework that jobs, especially in knowledge work, consist of decide, execute, deliver.

So-

Mm

So I really have to ask you listening, is rebranding this as super intelligence a necessary psychological wake-up call for the public? Or is it just political window dressing while we wait for actual laws to catch up?

To contextualize that debate, computer scientist Arvind Narayanan provided a brilliant framework recently on the Ezra Klein Show.

He argues that society is currently torn between two opposing paradigms.

Okay, what are they?

[clicks tongue] Uh, your editorial this week focuses on, uh, y- you don't call it the ethic of, of engineering, the principle of engineering.

You focus on a really interesting, I thought, um, interview on, uh, the Ezra Klein Show between Klein and Arvind Narayanan, who's a Princeton, uh, computer scientist and expert on AI.

Um, does Narayanan, in your view, represent if not the ethic of engineering, the logic of the engineer when it comes to making sense of AI?

Yeah.

That's nytimes.com/genentech-film.

[upbeat music] Pulsing through the episodes we've been doing, the debate the country's been having about artificial intelligence is, I think, this pretty simple but hard question, which is: What sort of technology is artificial intelligence? Is it a technology that works somewhat the way past ones have worked? Is it comparable to electricity, the internet, bicycle, something like that? Or is it something new? Is the addition of intelligence and volition to these systems the creation of something more like a, like an alien mind, such that analogies to the way we have treated transformational technologies before no longer holds? Arvind Narayanan is a professor of computer science at Princeton University and the director of the Center for Information Technology and Policy.

And he's a co-author, alongside Sash Kapur, of the very, very influential essay, "AI as Normal Technology." There is a Substack of the same name and then a series of essays, including a very good one, I think, recently on the Hugging Face hacks.

And they, in this set of arguments, put forward the idea that actually AI is something we have seen before, or at least it bears enough resemblance to things we've seen before, that we have a roadmap for how to deal with it.

So I want to bring him on the show to articulate that perspective.

He joins me now.

[upbeat music] Arvind Narayanan, welcome to the show.

Great to be here, Ezra.