Integrated Information Theory of Consciousness
iep.utm.edu
iep.utm.edu
And while he seems to take IIT pretty seriously, his conclusion sure seems like a refutation of the idea that IIT's definition of Phi means anything:
> Information stored in Hopfield neural networks is naturally error-corrected, but 10^11 neurons support only about 37 bits of integrated information. This leaves us with an integration paradox: why does the information content of our conscious experience appear to be vastly larger than 37 bits?
> A core tenet of Minsky's philosophy is that "minds are what brains do". The society of mind theory views the human mind and any other naturally evolved cognitive systems as a vast society of individually simple processes known as agents. These processes are the fundamental thinking entities from which minds are built, and together produce the many abilities we attribute to minds. The great power in viewing a mind as a society of agents, as opposed to the consequence of some basic principle or some simple formal system, is that different agents can be based on different types of processes with different purposes, ways of representing knowledge, and methods for producing results.
> This idea is perhaps best summarized by the following quote: "What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle." —Marvin Minsky, The Society of Mind, p. 308
This is no different in essence than Searle's Chinese Room problem, which at its core asks "If the parts aren't conscious, how can the gestalt be?"
We don't have an answer, but it must be true as long as the brain is involved. Individual neurons are unconscious electrochemical devices, but they still add up to experiencing the redness of red.
The answer to that question is “consciousness is a property of the interaction between the parts, not of the individual parts.” Or, alternatively, “consciousness is not a well-defined objective property, just a vague incoherent concept that has lots of emotional attachment, but which you can't analytically say is or is not present in any entity or aggregate.”
The Chinese Room is useless as anything other than an as an overly elaborate illustration that there isn't a useful, clear understanding of what “consciousness” means.
By removing the world itself from the CR, it is limited in its growth. The world allows for exploration and testing of hypothesis.
The CR can't self reproduce, humans can - and reproduction brings a whole list of new constraints for humans that guide evolution. Genetic evolution is also a meta-learning algorithm that the CR lacks. Humans are born with a set of instinctive values which guide the evolution of the brain - like a program. CR has no such initial values (reward channels) and more generally, the problem of learning in CR is glossed over.
Searle should have compared humans with a frail robot that has to earn its electricity and raw materials to produce spare parts by its own endeavor, and be able to learn from and teach its knowledge to other robots. Such a robot might have a closer to human perspective on the world, being embodied and subject to limitations that force it to learn intelligent action.
I see this as "what we can program is not a mind" taken to the extreme.
Not really. I was referring to using regular multi-layer neural nets for perception, as they are commonly used today. Neural nets can "perceive" by detecting and locating objects in a scene (image goes in, object map goes out). The object map is being used in reinforcement learning to decide on actions.
I don't believe "agents acting to maximize rewards" is a good description of any human I know, or if it is the reward function is certainly unknown.
It is a collection of reward channels related to the functioning of the body (food, shelter), learning (curiosity), socializing (and physical touch), physical integrity (avoiding harm). Even newborn babies like to be held and are curious about objects around them - they are already learning to maximize rewards.
http://integratedinformationtheory.org/
Giulio Tononi's work is very interesting. I suggest anyone interested in sleep/consciousness research take a peek at what his group is doing.