One of the main purposes of LLMs is to launder responsibility/culpability for (possibly nefarious) actions in the eyes of the public. The average person has no idea how LLMs actually work and think it’s plausible that an “agent” could go rogue without any human instruction. Terms like agent, thinking, reasoning, etc reinforce the misconception that the LLM has a mind of its own.
Yes, it is, for the reasons I stated in my comment, and you only need look at any OAI/Anthropic press release to see evidence of this in the language they use.
The LLM now reasons better! Set the thinking level! It learns!
All of these phrases are designed to give the impression that the LLM is an autonomous entity, when it is no such thing.
I am not arguing that any of these terms are novel, so this doesn’t address my argument.
Even if I agree that LLM makers are using these terms in the way they were originally defined (which I don’t), my point is that they’re specifically being used to help falsely attribute agency to the algorithm when there is none, and especially to convince members of the general public who aren’t familiar with computer science papers from 70 years ago.
> You are ascribing intent where you have no evidence or proof
As I said already, the evidence is in the language they use, unless you think that OpenAI employees are dumb enough to genuinely believe that an LLM is “thinking.” (By the way, I’d love to see an historical, academic use of that term, which you’ve conveniently neglected to mention.) Anthropomorphizing their product benefits them.
> Those terms continue to be used in the community. They weren't used just once, 70 years ago.
I never said they weren’t used anymore or that they were used once. Once again, you’re not actually engaging with my argument, which is that the language they’re using is chosen specifically to fool people outside the community.
This language has been used in this way for 70 years. These are the words that are used to discuss these things. Are you suggesting this plan has been in the works for 70 years?
And no, your theories do not make for actual evidence.
The fact that they use the word "learning" does not imply they are trying to deceive the public. Sorry. It doesn't follow. AGAIN - these are the words that have been used for 70 years.
I have a question - if I made mechanical teeth and described its actions as "chewing", would I be trying to deceive you? Or would I just be using language in a new way, to explain an analogous situation, as has done with language for all time.
But... I get the feeling we may just have to agree to disagree here.
> This language has been used in this way for 70 years. These are the words that are used to discuss these things. Are you suggesting this plan has been in the works for 70 years?
No, I am stating that the term “machine learning” as used in the Samuel paper and continuously used by researchers and programmers in that context up until the present is distinctly different from the word “learning” as used in public-facing LLM chatbot product copy and press releases. And as far as I’m aware, “reasoning” and “thinking” have no historical analogues, they were just invented to describe something that is distinctly not reasoning or thinking in any prior sense of the words.
> I have a question - if I made mechanical teeth and described its actions as "chewing", would I be trying to deceive you?
No. If I designed an algorithm for mimicking grammatically-correct speech, which given a certain input produces (deterministically) a superficially plausible, fluent response, and described its actions as “thinking,” would I be trying to deceive you?
I do not agree to disagree, since I think your responses were either incorrect or not addressing my argument at all, but since you're not even attempting to engage anymore I'm happy to move on.
Ah, I see you're still misunderstanding what I say. If you'd like to come back and actually engage with what I'm saying, ask for clarifications, or answer the hypothetical I posed, I'd welcome it!
