Liability and Responsibility in AI Development

Who owns the liability there?

And of course, naturally, they would say the government owns the

liability because

you're never going to successfully, uh, sue the government for this, even though

they, they should eat it. Uh, but maybe that doesn't

work anymore because maybe they are an agent of government.

And I, I don't know where we're ever gonna see

standing to sue on this, but we,

we should. And people in this room, I think, are frankly going to be

called upon in the course of their careers, in the course of their studies,

in the

course of whatever you do, to contend with these kind of issues.

Where are we gonna draw a line? Because an algorithm cannot make

mistakes in the way that we understand it as, uh, you know,

you making an error. Because the errors in its outputs are

not the computer's fault. It's the slave to its instructions.

The responsibility lies with its developer, its programmer, its creator,

its

architect. Which is to say, responsibility lies with a person.

And we cannot hide that. We cannot abrade that away, right?

A, a gun maker

is not liable, it's true, for the misuse of the gun.

Uh, but if during the testing of their latest

piece of artillery, they

mistakenly obliterate, you know, a nearby village, it's

not the cannon that should go to jail.

And, you know, just because you put out a press release

describing how surprised

you were that your new model, you know, hacked the neighbor, uh,

or d- you know, how impressed you are by this tr- destructive

power of your missile, uh, that doesn't release you from the

liability of launching

it. The missile didn't launch itself. You launched it.

Uh, and, and so th- there's a lot we can get into,

but the idea that I want people

to, uh, contend with is, is how we deal with this.

And right now, these closed models are saying AI safety, AI

safety, safetyism, as they call it, uh, where the idea is these things are so

dangerous. Oh gosh, they're so dangerous, but they're so dazzling.

They're so important. They're so valuable. We can't get rid of them.

But, you know, oh, it's gonna kill some people,

but it's all right.

You know, that just happens. Oh, it's gonna hack some companies.

Oops, you know, whatever. Uh, we'll invest in them.

The idea here is

who operates this? And this should apply to our devices more

broadly around the

world. Right now, you buy a cell phone from Apple, and

before you're allowed to use it, uh, you have to click okay to continue.

Uh, and they go, "Well, you're assuming liability for that.

You, you clicked okay to continue." You know,

Google sells you an Android phone.

Samsung sells you an Android phone.

You click okay to continue, and now that's all you.

But that can't be possibly how it works because you can't inspect the

system. You can't understand how it's used,

and particularly in the context of

LLMs, where you're submitting queries to a model

that they are running, uh,

where they are for your safety and everyone else's safety,

intercepting the prompt and recomposing the prompt, saying,

"We're doing, uh,

applying safety rules and transformations to it."

Uh, that's on you,

but it's not. I can't even see what you did.

I asked you a question.

You gave me something back in return.

And if it's an agentic AI, where I'm putting this thing in a harness,

right?

The harness being just a little program that basically uses these

large models to feed it instructions that it can then

provide to tools that are existing on your local

system. So now your computer that is connected to the

internet is being, frankly, remotely controlled, uh, by a model

that's far away that you don't understand how it works.

But, you know, you hope it works pretty well.

And frankly, they do work reasonably well.

But every now and then, it might hack, you know, some random company or whatever

out there.

Uh,

I think we need to put Sam Altman in jail, uh, and I think it'll be an

instructive experience.