this post was submitted on 29 Aug 2023
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When the idea of self-driving cars first started becoming mainstream, I remember a lot of debate about liability. If an accident occurs, who would be at fault? I think a lot of those questions are still unanswered.

Fast forward and now we have software like ChatGPT. I assume they'll only become more capable (and connected) over time.

Which makes it strange I haven't really heard any similar discussion around liability. What happens when it makes mistakes or causes damage?

Maybe in people's minds it doesn't matter, because AI is either something that helps with homework questions, or something that's taking over humanity. Reality is probably in between those two, with much more mundane mistakes or damages done.

What happens when the first ransomware is deployed by AI, on behalf of a user who just wanted tips on how to make more side income?

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[–] catreadingabook@kbin.social 11 points 1 year ago* (last edited 1 year ago) (1 children)

Completely speculating, because I don't know many courts that have been willing to decide either way, but maybe:

If it causes harm in a way that was reasonably foreseeable, the person who turned it on and/or the person "operating" it might be generally liable on a theory of negligence (but not always).

If the harm was unpredictable, it might be on the manufacturer and the retailer under a theory of products liability (but not always).

Or it could be treated as "ferae naturae," where owners are liable for their 'dangerous animal' pets because they knew the pets were dangerous and still decided to keep them (but not always).

If it's an AI not associated with a physical device, maybe the programmer who "authored" the lines of code could be criminally liable for criminal "speech" (writing an AI) that incites and enables crime, even as a conspirator -- that's reeeaaally doubtful on Due Process grounds, but it would definitely light a fire under every developer's chair to make sure their algorithms are explicitly trained against criminal behavior. (but still not always.)

[–] eager_eagle@lemmy.world 7 points 1 year ago (1 children)

I mostly agree, with the exception of the last paragraph. The software world today is built on open source software that is distributed without guarantees and this is an amazing thing. If a liability like that is applied to AI, it would be easily generalized to any piece of software that might be used in malicious ways the author did not intend or predict. It would be akin to punishing a knife manufacturer for a stabbing.

It is ridiculously easy to write a genuinely well intentioned script that encrypts your files and a minor modification can turn that into a ransomware.

[–] catreadingabook@kbin.social 1 points 1 year ago* (last edited 1 year ago) (1 children)

That's true, but thinking about AI that is made to generate speech, processing power is still expensive enough that developers are careful with it. But what happens as memory gets cheaper and calculations get faster, and ordinary developers are able to train their own generative AI?

For example, what happens when a developer decides to train a LLM extensively on scam emails, and spammers love to buy copies of it - but the developer markets it as just "a helpful generative AI"? Or, what if a person trains their LLM on an extremist forum full of hate speech and disinformation, then offers it to a suicide prevention center as a 24/7 alternative to human labor? (Treating these as hypotheticals, where we assume the difference isn't immediately obvious. Perhaps they also used some legitimate training data, so that most outputs seem innocent enough.)

To me it sounds more involved than selling just a word processor with autocorrect, but less involved than selling an instruction manual for committing crimes.

[–] eager_eagle@lemmy.world 1 points 1 year ago (1 children)

But what happens as memory gets cheaper and calculations get faster, and ordinary developers are able to train their own generative AI?

That happens all the time since GANs entered the scene, and before that since alexnet broke image classification records in 2012 using consumer hardware. Anyone can train neural nets.

[–] catreadingabook@kbin.social 1 points 1 year ago* (last edited 1 year ago)

Ok, let me be more specific so that it's not open to uncharitable interpretation.

What happens when it becomes easy to make something as reliable and complete as, e.g., ChatGPT-4 without the hardware costs and other costs currently associated with it?