I would disagree with this description. An "emergent property of large networks" would be something that just appears when you wire together a large network.
To get intelligent behavior, it's not sufficient to wire together a large neural network. You also need to use an optimizer to train it on a large data set.
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
- Twin Peaks, 1993
On the other hand, it is fascinating how much interesting work and theories in the field will be retired, at least for a long time (I allow for a likelihood that some of that could return eventually as better, more concise generalizations). Ten years ago Chomsky and various GOFAI-related stuff could still sound respectable and somewhat plausible. Plenty of people were/are wedded to the concept that you can build machine intelligence as an abstract and intellectually stimulating gentleman pursuit. It was a comfy position in a way. Not surprised about the resistance they are mounting now, though I think academic inertia will allow them to exist for quite some time. They can just move to doing some kind of philosophy also.
I would also disagree that ChatGPT constitutes a self. If anything, it constitutes a normal distribution over possible selves, where you get a random pick at the start of each conversation, and confined to the length of its token buffer.
I find interacting with GPT4 feels very different to interacting with either humans or animals.
These machines are merely thinking machines.
A rock is also more than it's thoughts, and retains some degree of consciousness. Imagining concepts like souls as a sort of litmus test for consciousness only serves to reinforce a thought-based comprehension.
In other words, when I control my thoughts, what is doing the controlling?
(see George Gurdjieff's philosophy which speaks to this issue of the `mechanical vs the conscious`, but please don't run off and join a crazy cult and ruin your life).
This seems like a change of topic. And vague.
But since you bring it up, I don't see anything threatening about AI.
First, if something is true, then, as a matter of principle, we have an obligation to believe it. Thus, the only threat the truth can pose is to falsehood, which is not a threat, but liberation. The truth shall set you free. Now, it may be uncomfortable is the truth is at odds with what you want to believe (a phenomenon very much present in the linguistic engineering we're seeing in the political sphere w.r.t. political correctness and its dishonest and obfuscating euphemisms), but unpleasantness isn't a threat.
Second, if we replace "threaten" with "challenge", then we might as what beliefs does AI actually challenge? How does it challenge this "mystery of the self"? That we can simulate human discourse or behavior with greater sophistication? That machine automation is becoming more sophisticated? I see no mystery where AI per se is concerned, only the mystification of those who wish attribute to it properties it does not possess, or those with intellectually superficial metaphysical commitments, like mechanistic materialism. AI cannot abstract from particulars, it has no true capacity for intentionality, to name two features central to intelligence. All of what the undiscerning and those given oven to fanciful notions see in AI is a projection.
And I do not think the classical[0] and traditional[1] thinkers viewed intelligence in the obfuscating manner that moderns infected by reductive, mechanistic materialism seem to.
[1] https://edwardfeser.blogspot.com/2019/03/artificial-intellig...
The race isn't to build the biggest model, the race is to build the model that uses data the most efficiently and produces the best results when constrained to parameter counters that can fit on consumer hardware.
AI's a big deal, but there's no reason to suggest that this makes any inroads toward unraveling self or consciousness significantly beyond what we get from books, movies, or perhaps more recently, video games.