The problem is that the general public has adopted “AI” to mean the current popular machine learning thing,
Yes, that is the problem, because people don’t understand that it’s a short-hand, and don’t understand the difference between harmful uses, and non-harmful uses. The concept itself becomes a meaningless tribal indicator of hate. “This person is acting unethically and unlawfully,” has quickly become “I don’t understand what this technology is, but when I see ‘AI’ I automatically hate whatever it’s associated with.” That is counter-productive to humanity as a whole.
So stop saying that any given technology or method is intrinsically bad, and start focusing on WHO is doing the harm and HOW.
If I’m having a direct discussion with somebody, then I’ll make it clear what I’m talking about, and if they engage in a conversation about ethics, I’ll explain why those things are unethical.
But if I wanted to post a public message to voice my sentiment, I don’t think trying to post a long explanation every time would do any good, most people would probably just skip it when they saw it’s longer than a couple lines of text. So for those cases, I’d say you have to go down to the level of current discourse to engage with the masses on their terms if you want to be heard.
But if I wanted to post a public message to voice my sentiment, I don’t think trying to post a long explanation every time would do any good
That’s a non sequitur. The initial point was “Stop using this term incorrectly, because it spreads misunderstanding and misinformation.”
Nobody said you should write a thesis per reply, and my entire point was to focus on the harms, and the actors, not the tech.
Saying “AI is unethical,” is a truly nonsensical statement. Even if we grant that AI is shorthand for LLM, is still isn’t justified as all I need to do is find an instance of an open source model being trained on public data to refute it, and there are MANY.
Unless you think that using public data to make public software is inherently unethical, which is a hard stance to justify.
If you’re upset with Sam Altman and ChatGPT, then you can simply say “Sam Altman is a thief, and ChatGPT uses stolen data.” Which is infinitely more defendable than “AI is trained on stolen data and is unethical.”
If you’re upset with Sam Altman and ChatGPT, then you can simply say “Sam Altman is a thief, and ChatGPT uses stolen data.” Which is infinitely more defendable than “AI is trained on stolen data and is unethical.”
The issue is, I’d say the same applies to every model that produces useful outputs. LLaMa, Anthropic, Grok, DeepSeek, whatever else is out there. If you tell somebody that the LLM they’re using is unethical, they’ll nust go use another convenient corporate model.
And “public data” is not enough for me, because that typically means scraping copyrighted content from public websites, I’m not aware of a model that uses only data with permission (either explicit or granted by the license) that’s useful, and the people who need to hear about ethical problems with GenAI especially don’t know about that.
Yes, that is the problem, because people don’t understand that it’s a short-hand, and don’t understand the difference between harmful uses, and non-harmful uses. The concept itself becomes a meaningless tribal indicator of hate. “This person is acting unethically and unlawfully,” has quickly become “I don’t understand what this technology is, but when I see ‘AI’ I automatically hate whatever it’s associated with.” That is counter-productive to humanity as a whole.
So stop saying that any given technology or method is intrinsically bad, and start focusing on WHO is doing the harm and HOW.
If I’m having a direct discussion with somebody, then I’ll make it clear what I’m talking about, and if they engage in a conversation about ethics, I’ll explain why those things are unethical.
But if I wanted to post a public message to voice my sentiment, I don’t think trying to post a long explanation every time would do any good, most people would probably just skip it when they saw it’s longer than a couple lines of text. So for those cases, I’d say you have to go down to the level of current discourse to engage with the masses on their terms if you want to be heard.
That’s a non sequitur. The initial point was “Stop using this term incorrectly, because it spreads misunderstanding and misinformation.”
Nobody said you should write a thesis per reply, and my entire point was to focus on the harms, and the actors, not the tech.
Saying “AI is unethical,” is a truly nonsensical statement. Even if we grant that AI is shorthand for LLM, is still isn’t justified as all I need to do is find an instance of an open source model being trained on public data to refute it, and there are MANY.
Unless you think that using public data to make public software is inherently unethical, which is a hard stance to justify.
If you’re upset with Sam Altman and ChatGPT, then you can simply say “Sam Altman is a thief, and ChatGPT uses stolen data.” Which is infinitely more defendable than “AI is trained on stolen data and is unethical.”
The issue is, I’d say the same applies to every model that produces useful outputs. LLaMa, Anthropic, Grok, DeepSeek, whatever else is out there. If you tell somebody that the LLM they’re using is unethical, they’ll nust go use another convenient corporate model.
And “public data” is not enough for me, because that typically means scraping copyrighted content from public websites, I’m not aware of a model that uses only data with permission (either explicit or granted by the license) that’s useful, and the people who need to hear about ethical problems with GenAI especially don’t know about that.