Actually I agree with them a new name would be helpful. I would propose inorganic intelligence to try to pick a term with less value judgments.
AI is really an overloaded term that includes 70 years of snake oil, Skynet, the Singularity and killer robots. I think we need a new name to start fresh.
And personally, I think we are extremely biased by our sci-fi to think of this tech as malevolent. As far as we can see, it can only know what we teach it since it relies on all of our perceptions to learn. LLMs seem both extremely promising as a useful tool and very pliant to the operator’s wishes. I’m way beyond “this is a fancy next word predictor” as I think it’s emergent behavior has many of the hallmarks of reasoning and novel inference, but at best I think it is only part of a mind and an unconscious one at that.
It could be useful for a similar reason as the euphemism treadmill. We could leave behind all of the misguided assumptions about AI with the old 'artificial intelligence' nomenclature and move forward with 'synthetic intelligence' which has our new understanding of what systems like GPT-4 can do.
>Since nobody actually knows what "intelligence" is
Everybody knows what intelligence is. Even if we can't agree on a precise definition, it's pretty obvious that it's the thing that humans and other animals do that involves learning, reasoning, planning, and problem solving. We can also agree that being successful at certain tasks constitutes intelligence. Solving a math problem is intelligence. Writing a poem is intelligence.
The devil is in the details and rather generic words that describe a gradient can never capture the exact nature of what we're trying to define in specific situations.
Only if you care about those details. Almost no one does.
In almost any conversation, everyone does in fact know what intelligence, porn, god and beauty are. Yes, all those ideas are fuzzy at the borders, but we almost never need to resolve them in detail when talking about them. When we do, then yes, things get tricky and there's a lot of disagreement - but at the end of the day, as the phrase I once read on the Internet goes, it all has to add up to normality. You can still work with fuzzy, casual concepts, even though you can't define them precisely.
You can never capture the exact nature of anything outside of logic and math. That's too high of a bar. Philosophers who have worked on this problem like Wittgenstein talk about concepts in terms of family resemblances, not exact definitions. If I'm trying to understand whether a system is intelligent, I don't need a logical proof. I learn whether it is intelligent by testing whether it can successfully do many of the same things that other intelligent systems do.
I disagree. I think that nobody knows what it is, as demonstrated by the fact that there is such a wide disagreement about what it is.
> We can also agree that being successful at certain tasks constitutes intelligence. Solving a math problem is intelligence. Writing a poem is intelligence.
As an example, I don't agree that either of those things indicates intelligence all by themselves. We've had programs that nobody would call "intelligent" to do both of those things for decades.
>We've had programs that nobody would call "intelligent" to do both of those things for decades.
So you're right that if I have separate algorithms, each designed for a specific purpose, that those algorithms aren't intelligent. However, if I have a general system that can learn how to solve a math problem, write a poem, and do a bunch of other things that humans can do, then that system is intelligent.
I think Artificial Intelligence has taken on the meaning that the intelligence is real but just that it's coming from machines. Synthetic intelligence (at least to me) sounds more like we're acknowledging that the machines aren't really intelligent and just simulating intelligence.
Why not just eliminate the middle man and call it simulated intelligence? That at least implies that there are different levels of fidelity as quantified by number of parameters and training data set size.
AI is really an overloaded term that includes 70 years of snake oil, Skynet, the Singularity and killer robots. I think we need a new name to start fresh.
And personally, I think we are extremely biased by our sci-fi to think of this tech as malevolent. As far as we can see, it can only know what we teach it since it relies on all of our perceptions to learn. LLMs seem both extremely promising as a useful tool and very pliant to the operator’s wishes. I’m way beyond “this is a fancy next word predictor” as I think it’s emergent behavior has many of the hallmarks of reasoning and novel inference, but at best I think it is only part of a mind and an unconscious one at that.