I cannot see anything that remotely makes these two contexts architecturally, practically, or ethically similar, except in the narrow sense of query responses that might have been mistakenly thought of as defining sentience in earlier decades.
This leads to believing that GPT has solved many of these issues.
Of course that's not a criticism of the ML achievement, except that everyone and their mother has started making some extreme arguments about the thing.
In his research, he argues that it’s the other way around; we have an innate intelligence for acquiring language.
To put it another way, language has made us more knowledgeable (because it’s a great mechanism for building and transferring context), but intelligence or aptitude for language was present before we developed languages.
Does this align with how your views were reshaped post LLMs?
> language enables intelligence
was just a poor choice of words here. i understood GP as "the structure of a language influences its speakers' worldview or cognition, and thus people's perceptions are relative to their spoken language"[0]
My argument is just that:
- Sentience is variable. We might regard primitive organisms as biological machines. As some of these machines have slowly evolved to become more complex, sentience/consciousness has emerged, effectively by 'redesigning' and scaling the same hardware. It is an emergent property. At the same time this has been happening, other aspects of what we call intelligence have been developing.
- Artificial networks being scaled, are also displaying emergent behaviours, some of which overlap with aspects of intelligence. This does not imply they are sentient, but it does strongly support some previous assumptions that sentience, like intelligence, is emergent and hence there will be no better answer coming.
There's very clear definitions for sentience & sapience.
The only confusion is that laypeople tend to conflate sentience & sapience.
A sentient AI is not necessarily a sapient one, by definition.
The skeptics are really not making any claims are they? If not then there's no burden of proof on them, is there?
Whoever says or implies that ChatBots are or are "becoming" "sentient" are the ones making a claim. They should prove it if they make or imply such a claim.
Skeptics are rightly skeptical, until they see a proof with clear definitions of terms from those who are saying or implying that ChatBots are 'approaching sentience".
There are no two "sides" making claims about AI. There is one side, making claims such as "AI can be/is/may be sentient".
If somebody makes such claims they have the "burden of proof" because they are the ones making the claim. It's not a moral obligation to prove it. "Burden of proof" simply means if you don't provide a proof, nobody (I would hope) will believe you.
Note the skeptics are not making any counter-claims, they are simply saying if you make such fantastic claims about current AI, please show us the proof, else we rationally cannot trust your judgment.
Just as a made up discription lets say this
Them: "If $object does A, B, and C, then it is a bajork"
Me "I have $object that does A, B, and C, it is a bajork"
Them: "No, it also doesn't do D"
Me: "That's goalpost moving"
Them: "Well, it doesn't do B in the way we expected, so it doesn't really do B"
Me: "Maybe we poorly defined what B was in the first place, that doesn't mean we didn't do B, it seems to mean no one understands what B is in the first place"
Like if we have models that are plainly more intelligent and "emotionally responsive" than say, frogs or even dogs, do we still do we still take the approach of "If you can't prove its sentient, do whatever you want to it". Which of of course, we can't even prove dogs have consciousness.
OP said:
> plainly programmed algorithmic systems
Compare that to a human brain which is not a linear, 1D algorithm.
The reason recent results are significant in this discussion is because:
- Larger networks are already displaying emergent behaviours that couldn't have been predicted beforehand. It doesn't have to be 'human-like' intelligence for that to be significant.
- We're getting close to a point where our models will start exhibiting something of the order of the same level of intelligence of primitive creatures.
So the wide-eyed hysteria you're seeing is really just new data points confirming what many of us always assumed would be the case.
This explains nothing. Stating it's an emergent phenomenon gives us just as much information as saying it's magic. Arguably even less, because it sounds like an explanation, whereas "magic" doesn't pretend to explain anything.
> displaying emergent behaviours that couldn't have been predicted beforehand.
Same problem here. You say "couldn't have been predicted". Which is only true if you explain it away with emergence. The behaviours weren't predicted, because we don't understand how these networks work. Saying they couldn't have been predicted implies that we can't understand them. Which is a very bold statement and I'm fairly certain that it's not true.
I don't think that's the case. Of course at one level we can understand how GPT4 works, we have a working implementation of it after all. But that doesn't help us predict how it will behave, because its properties are emergent, and have to be studied separately at that level. That's not saying it's magic.
Reality can be unsatisfying because it does not owe us explanations.
I mean, you experienced the reality of consciousness while talking about the last digit of 22/7.
If there is anything in our world that needs explaining it’s consciousness.
Reality doesn’t owe us an explanation of consciousness (obviously). We owe it to ourselves though.
That is not at all quite plain. Respectable philosophical views include the proposition it is at least as fundamental as space or time.
Dismissing serious ideas with thousands of years of philosophical history behind them as "magic thinking" is either a failure of imagination or education; you can rectify the latter by reading up on the subject.
Edit: I wonder if there are studies that have determined whether or not new born infants are self aware or does it take time for it to emerge after the brain has been trained on its environment for a while
Isn't most ethical behavior driven by self-interest? We want to follow general principles that promote respecting those who are similar to us in the hope that others follow the same principles when interacting with us.
AI is too dissimilar for us to worry about whether its "mistreatment" would make it more likely for others to start mistreating ourselves.
What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990's and 2000's. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I've encountered is anywhere near as convincing.
I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there's lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.
My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar's lab at UC Irvine, possibly. Dr. Edelman's roadmap to a conscious machine is at https://arxiv.org/abs/2105.10461