The bad thing is that people still think LLMs can be trusted at all. Companies integrating them into their offerings are not helping the public adopt the correct mental framing of these tools as "plausible text generators".
"Not helping" seems a wild understatement. "Deceiving people into taking the wrong frame" seems more accurate.
I'm only sorta kidding. I am surprised at the number of people who are comfortable with such a shallow conclusion.
b) Windows Recall data is never going to make its way into public models.
It doesn't need to. It just needs to make its way into OpenAI's models, which it will.
LLMs are as trustworthy as humans.
Humans have been being wrong for about as long as we have been lying.
Whether you get information from a human or an LLM, check it.
I worry about the people who insist on credible sources rather than checking information for themselves. I think 80% or more of them are trolling me, but there are some who genuinely do not apply the Scientific Method to check facts in their everyday life. I truly feel sorry for them.
You'd like to think so, right? However, this isn't really a solid thesis. Decent people will admit when they don't know. Is that normal? I've worked with so many people that just do not fit that definition at all, to the point it just seems like that's the normal way to behave. Maybe I'm jaded grossly overweighting it, but it just seems I have been in way too many meets with too many arguments over something because someone refused to back down and admit their ignorance/arrogance wasted valuable time because of refusal to accept input from others.
Let's get 1000 random people in a surgery room and ask them to perform brain surgery.
You actually think that most of them will say "sure I know exactly how to do this".
Be serious.
When was the last time Trump admitted he was wrong?
The number of times I've been told that yes, resetting my iPhone's network settings and reinstalling an app will resolve my billing issue or similar...
If a customer support agent gives you incorrect information, you can often hold the company liable for it (assuming you can prove it; I suppose there's a reason for why companies prefer certain support channels over others).
If an AI "lies" to you, you're largely on your own right now.
Notwithstanding differences in jurisdiction, applying that idea to this case would rely on finding that Meta owed Gaudreau a duty of care that extended to the Meta AI chatbot.
It would be more difficult to make this claim if Gaudreau had asked the question of Google, since Google itself is not usually responsible for false information uncovered by its searches.
My gut feeling is that it should be possible for companies to distinguish an AI product (i.e. as something provided to customers like a search engine, as you say) from an AI "working for them", but I can see a lot more disclaimers showing up in Meta's various AI chat channels soon.
"Messages are generated by Meta AI. Some may be inaccurate or inappropriate. Learn more."
Which leads to a pop-up further explaining that use cases include things like "creating something new like text or images".
I think it's going to be really interesting to see whether that's considered enough by courts, or if they'll take the position that these things pretend too well to be a real person to make such a disclaimer sufficient, similarly to how e.g. a brokerage can't disclaim "no investment advice" and then go on to say "but buy this stock, it's gonna moon tomorrow, trust me bro".
My point is just that credible sources are absolutely necessary for information to disperse. Nobody can afford to figure out the modern world from first principles.
A skilled motorcycle rider explaining how to take corners in a widely watched youtube video, with hundreds of comments confirming the advice and several recommended videos from other riders that basically say the same thing is an extremely strong positive signal.
The same answer gotten from a magic AI answer box is just as likely to be right as wrong, 50/50.