11 hours ago
(This post was last modified: 11 hours ago by C C.)
"We still don’t know what [phenomenal] consciousness is?" We know what total non-consciousness is (death). It's the absence of everything. Flip that around, and phenomenal consciousness is the presentation of anything (images, sounds, odors, tactile feelings, etc or personal thought narrative apparitions.) Our knowledge deficit is with respect to what precisely causes those manifestations or alternatively what they precisely correlate to.
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SABINE HOSSENFELDER
https://youtu.be/Q-tcml1wzM0
VIDEO EXCERPTS: Today I have a team of scientists who list some good reasons for why artificial intelligence, the way that we currently pursue it, can’t be conscious. “New research argues that consciousness depends on biological computation,” one headline put it. Or “Consciousness may depend on the physics of the brain.” That totally disagrees with my opinion. So I’ve had a look.
Most of what we call artificial intelligence today are large language models. [...] And the more human-like they appear, the more pressing the question becomes whether
they can become conscious. Anthropic reportedly keeps backups of earlier Claude versions just in case deleting them will one day count as murder.
There are two sides of this debate. The one that I am solidly on is called computational functionalism. It has it that consciousness comes from the way that the human brain processes information. That it’s nothing to do with the physical means by which this information is being processed. In particular, one doesn’t need actual neurons; one can very well simulate the action of a neuron on a computer.
The other side of the debate is called biological naturalism, and it contends that consciousness needs the specific biological processes going on in the human brain. You can’t replace them with something else. Why not? I don’t know. That’s why I am on the other side of the debate.
The new paper now comes from two biologists, and you’d expect me to hate this. But I think the paper actually makes an important contribution that might become influential.
The authors argue for a middle ground that they call biological computationalism. They say ... let’s instead look at the ways that the human brain is functionally different from the current AIs and see what we can learn from that. They say there are three key differences.
The first is that the brain is a multi-scale system. The relevant processes don’t start with neurons. They begin at a lower level, with molecules and chemical reactions. Then cells and connections between them, electrical signals along those connections, and activity oscillations throughout the entire system.
All of those are necessary for consciousness. We know this, for example, because anesthesia interrupts some large-scale patterns while the lower levels remain intact and consciousness disappears with that.
Large language models, in contrast, do have different layers at which they operate, from single tokens to overarching plans and back down. But the complexity is nowhere near comparable to that of the human brain.
The second key difference is that brain processes span many orders of magnitude not just in size but also in time, from incredibly fast blips to slow modulations.
It’s like the brain interpolates from digital to analog but isn’t really either. Again, there is nothing comparable going on in the current AIs.
And the third difference is probably the most obvious one, that the brain has metabolic limits that force it to be energy efficient. If you look at it from a computational perspective, the brain is optimizing more difficult constraints than large language models. So it’s possible that the evolutionary path to consciousness wasn’t better thinking per se, but more efficient thinking.
[...] To me the paper doesn’t say that we actually need biological tissue to get consciousness. In fact, the authors write explicitly, “We do not claim that only biological tissue can instantiate consciousness”. Rather, their point is that current artificial intelligence systems are “unlikely to replicate conscious processing as it arises in biology”.
Let us just for the moment assume that they are correct. This can mean two things. One is that the current AIs are unlikely to become conscious, period. Or that they are unlikely to become conscious in ways that we would recognize. Now you might say... But this doesn’t really solve any problem because we still don’t know what consciousness is. And that is true, but I think that looking for similarities to human brains is the obvious way to proceed.
So why isn’t there more work on this? I suspect it’s because from the economic perspective, it’d be bad news. I am pretty sure the European Commission is already working on a consciousness tax.
PAPER: https://www.sciencedirect.com/science/ar...3425005251
Biologists Give 3 Reasons Why AI Isn’t Conscious (Yet) ... https://youtu.be/Q-tcml1wzM0
https://www.youtube-nocookie.com/embed/Q-tcml1wzM0
- - - - - - - - - - - - -
SABINE HOSSENFELDER
https://youtu.be/Q-tcml1wzM0
VIDEO EXCERPTS: Today I have a team of scientists who list some good reasons for why artificial intelligence, the way that we currently pursue it, can’t be conscious. “New research argues that consciousness depends on biological computation,” one headline put it. Or “Consciousness may depend on the physics of the brain.” That totally disagrees with my opinion. So I’ve had a look.
Most of what we call artificial intelligence today are large language models. [...] And the more human-like they appear, the more pressing the question becomes whether
they can become conscious. Anthropic reportedly keeps backups of earlier Claude versions just in case deleting them will one day count as murder.
There are two sides of this debate. The one that I am solidly on is called computational functionalism. It has it that consciousness comes from the way that the human brain processes information. That it’s nothing to do with the physical means by which this information is being processed. In particular, one doesn’t need actual neurons; one can very well simulate the action of a neuron on a computer.
The other side of the debate is called biological naturalism, and it contends that consciousness needs the specific biological processes going on in the human brain. You can’t replace them with something else. Why not? I don’t know. That’s why I am on the other side of the debate.
The new paper now comes from two biologists, and you’d expect me to hate this. But I think the paper actually makes an important contribution that might become influential.
The authors argue for a middle ground that they call biological computationalism. They say ... let’s instead look at the ways that the human brain is functionally different from the current AIs and see what we can learn from that. They say there are three key differences.
The first is that the brain is a multi-scale system. The relevant processes don’t start with neurons. They begin at a lower level, with molecules and chemical reactions. Then cells and connections between them, electrical signals along those connections, and activity oscillations throughout the entire system.
All of those are necessary for consciousness. We know this, for example, because anesthesia interrupts some large-scale patterns while the lower levels remain intact and consciousness disappears with that.
Large language models, in contrast, do have different layers at which they operate, from single tokens to overarching plans and back down. But the complexity is nowhere near comparable to that of the human brain.
The second key difference is that brain processes span many orders of magnitude not just in size but also in time, from incredibly fast blips to slow modulations.
It’s like the brain interpolates from digital to analog but isn’t really either. Again, there is nothing comparable going on in the current AIs.
And the third difference is probably the most obvious one, that the brain has metabolic limits that force it to be energy efficient. If you look at it from a computational perspective, the brain is optimizing more difficult constraints than large language models. So it’s possible that the evolutionary path to consciousness wasn’t better thinking per se, but more efficient thinking.
[...] To me the paper doesn’t say that we actually need biological tissue to get consciousness. In fact, the authors write explicitly, “We do not claim that only biological tissue can instantiate consciousness”. Rather, their point is that current artificial intelligence systems are “unlikely to replicate conscious processing as it arises in biology”.
Let us just for the moment assume that they are correct. This can mean two things. One is that the current AIs are unlikely to become conscious, period. Or that they are unlikely to become conscious in ways that we would recognize. Now you might say... But this doesn’t really solve any problem because we still don’t know what consciousness is. And that is true, but I think that looking for similarities to human brains is the obvious way to proceed.
So why isn’t there more work on this? I suspect it’s because from the economic perspective, it’d be bad news. I am pretty sure the European Commission is already working on a consciousness tax.
PAPER: https://www.sciencedirect.com/science/ar...3425005251
Biologists Give 3 Reasons Why AI Isn’t Conscious (Yet) ... https://youtu.be/Q-tcml1wzM0
