HedyL

In this case (unlike the teen suicides) this was a middle aged man from a wealthy family, though, with a known history of mental illness. Quite likely, he would have had sufficient access to professional help. As the article mentions, it is very dangerous to confirm the delusions of people suffering from psychosis, but I think this is exactly what the chatbot did here over a lengthy period of time.

To me, in terms of the chatbot's role, this seems possibly even more damning than the suicides. Apparently, the chatbot didn't just support this man's delusions about his mother and his ex-girlfriend being after him, but even made up additional delusions on its own, further "incriminating" various people including his mother, whom he eventually killed. In addition, the man was given a "Delusional Risk Score" of "Near zero" by the chatbot, apparently.

On the other hand, I'm sure people are going to come up with excuses even for this by blaming the user, his mental illness, his mother or even society at large.

because made-up stats/sources will get their entire grift thrown out if they’re discovered

I believe it is not just that. Making up some of those references as a human (in a way that sounds credible) would require quite a lot of effort and creativity. I think this is a case where the AI actually performs “excellently” at a task that is less than useless in practice.

This is a theory I had put forward before: Made-up (but plausible-sounding) sources are probably one of the few reliable “AI detectors.” Lazy people would not normally bother to come up with something like this themselves.

The most useful thing would be if mid-level users had a system where they could just go “I want these cells to be filled with the second word of the info of the cell next to it”,

In such a case, it would also be very useful if the AI would ask for clarification first, such as: "By 'the cell next to it', you mean the cells in column No. xxx, is that correct?"

Now I wonder whether AI chatbots typically do that. In my (limited) experience, they often don't. They tend to hallucinate an answer rather than ask for clarification, and if the answer is wrong, I'm supposedly to blame because I prompted them wrong.

Also, AI is super cheap, supposedly, because it is only $ 0.40 an hour (where did that number come from?). Unlike humans, AI doesn't need any vacations and is never sick, either. Furthermore, it is never to blame for any mistakes. The user always is. So at the very least, we still need humans for shouldering all the blame, I guess.

This week I heard that supposedly, all of those failed AI initiatives did in fact deliver the promised 40% productivity gains, but the companies (supposedly) didn't reap any returns "because they failed to make the necessary organizational changes" (which happens all the time, supposedly).

Is this the new "official" talking point?

Also, according to the university professor (!) who held the talk, the blockchain and web3 are soon going to solve the problems related to AI-generated deepfakes. They were dead serious, apparently. And someone paid them to hold that talk.

What happened to good old dice?

I'm not even sure I understand the point of this supposed "feature". Isn't their business model mainly targeted at people who want to sell merch to their fanbase or their followers? In this case, I would imagine that most creators would want strong control over the final product in order to protect their "brand". This seems very different from stock photography / stock art, where creators knowingly relinquish (most) control over how their work is being used.

It's a bit tangential, but using ChatGPT to write a press release and then being unable to answer any critical questions about it is a little bit like using an app to climb a mountain wearing shorts and flip-flops without checking the weather first and then being unable to climb back down once the inevitable thunderstorm has started.

A while ago, I uploaded a .json file to a chatbot (MS Copilot, I believe). It was a perfectly fine .json, with just one semicolon removed (by me). The chatbot was unable to identify the problem. Instead, it claimed to have found various other "errors" in the file. Would be interesting to know if other models (such as GPT-5) would perform any better here, as to me (as a layperson) this sounds somewhat similar to the letter counting problem.

Turns out I had overlooked the fact that he was specifically seeking to replace chloride rather than sodium, for whatever reason (I'm not a medical professional). If Google search (not Google AI) tells the truth, this doesn't sound like a very common idea, though. If people turn to chatbots for questions like these (for which very little actual resources may be available), the danger could be even higher, I guess, especially if chatbots had been trained to avoid disappointing responses.