The idea of an Artificial Superintelligence (ASI)—a machine intelligence surpassing human cognitive abilities in virtually all domains—has long fascinated computer scientists, philosophers, futurists and (especially in the last 5-10 years) just about anybody who reads.
It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with only primary consciousness will probably have to come first.
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, and here is a video of Jeff Krichmar talking about some of the Darwin automata, https://www.youtube.com/watch?v=J7Uh9phc1Ow
Thanks, Grant. Edelman's TNGS and the Darwin series of automata are definitely a key piece in the puzzle of artificial consciousness. Particularly how the DARwIn-OP can behave in a way that mirrors human actions. Its ability to walk omnidirectionally, perform vision-based localization, and execute object manipulation tasks demonstrates a level of behavioral complexity that suggests something interesting is happening. Similarly, the robot fish evolution is fascinating.
I do wonder, though, if we're still missing something crucial. I've been developing the idea that our recognition of consciousness in others is influenced by the similarity of their behaviors to our own. So, when robotic systems display human-like or biologically analogous behaviors, we are more inclined to attribute a form of consciousness or intentionality to them—that consciousness can be viewed as a function of form, where the observable actions of a system inform our perception of its conscious state. Our anthropocentric bias colors most of our perceptions; it seems reasonable to assume that it might be even stronger with the feature we hold most dear.
It's striking how we often dismiss apparently intelligent behavior in non-human systems as mere instinct, simple chemistry, or random walk luck. Consider the famous experiment where Physarum polycephalum slime mold recreated the Tokyo subway map's efficiency when food sources were placed at locations corresponding to stations. We're quick to attribute this to simple chemical gradients rather than problem-solving, despite the remarkable optimization achieved. Yet when similar pattern-recognition or optimization occurs in systems that physically resemble us, we're more willing to consider it meaningful intelligence.
So, while Edelman's work addresses (some of) the mechanisms underlying intelligent behavior, it also highlights the enduring challenge of comprehending subjective experience.
You're welcome. Humanoid robots that will seem conscious to many people are probably going to be walking the streets in 5 or 10 years. But in a very real sense, they won't be any more conscious than a chess program.
Machines with biological primary consciousness are more than a hundred years away, imo. Machines with adult human level biological primary and higher order consciousness (fully developed language) are even further in the future.
It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with only primary consciousness will probably have to come first.
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, and here is a video of Jeff Krichmar talking about some of the Darwin automata, https://www.youtube.com/watch?v=J7Uh9phc1Ow
Thanks, Grant. Edelman's TNGS and the Darwin series of automata are definitely a key piece in the puzzle of artificial consciousness. Particularly how the DARwIn-OP can behave in a way that mirrors human actions. Its ability to walk omnidirectionally, perform vision-based localization, and execute object manipulation tasks demonstrates a level of behavioral complexity that suggests something interesting is happening. Similarly, the robot fish evolution is fascinating.
I do wonder, though, if we're still missing something crucial. I've been developing the idea that our recognition of consciousness in others is influenced by the similarity of their behaviors to our own. So, when robotic systems display human-like or biologically analogous behaviors, we are more inclined to attribute a form of consciousness or intentionality to them—that consciousness can be viewed as a function of form, where the observable actions of a system inform our perception of its conscious state. Our anthropocentric bias colors most of our perceptions; it seems reasonable to assume that it might be even stronger with the feature we hold most dear.
It's striking how we often dismiss apparently intelligent behavior in non-human systems as mere instinct, simple chemistry, or random walk luck. Consider the famous experiment where Physarum polycephalum slime mold recreated the Tokyo subway map's efficiency when food sources were placed at locations corresponding to stations. We're quick to attribute this to simple chemical gradients rather than problem-solving, despite the remarkable optimization achieved. Yet when similar pattern-recognition or optimization occurs in systems that physically resemble us, we're more willing to consider it meaningful intelligence.
So, while Edelman's work addresses (some of) the mechanisms underlying intelligent behavior, it also highlights the enduring challenge of comprehending subjective experience.
You're welcome. Humanoid robots that will seem conscious to many people are probably going to be walking the streets in 5 or 10 years. But in a very real sense, they won't be any more conscious than a chess program.
Machines with biological primary consciousness are more than a hundred years away, imo. Machines with adult human level biological primary and higher order consciousness (fully developed language) are even further in the future.