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Consciousness and the Paranormal — Part 10

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Ah. So it isn't just complexity after all. It is about the nature of the complexity. So now you just have to figure what the "nature" bit is and why it is such an important additional ingredient.

Complex systems are a particular type of systems. All systems are formed multiple elements interacting with each other. But complex systems are characterised by the high degree of integration and differentiation among the constituting parts. The integration of the system depends on a high interconnectivity and interaction between constituting parts. And the degree of differentiation is given by their degree of multiplicity and diversity.

Complexity then, is characterised by both qualities: integration and differentiation. Systems with either a low degree of integration or differentiation don’t behave like complex systems.

The relativity of complexity

Not all systems are equally complex. Complexity is relative and it depends on the degree of differentiation and integration, where higher differentiation and integration is related with higher complexity.



So we define the degree of complexity of a system as the degree of integration and differentiation of the system. High complexity is related to high degrees of integration and differentiation, while low complexity with the opposite.

Differences in the levels of complexity are also related with differences in the properties of systems and the way they behave.

Complexity
 
But who or what gets to do the asking of the question? And how does "data" come to represent something that has value in the first place. Who says for instance that 1 has greater value than 2 or even that there is such a thing in physical reality as 1 or 2?

You can lead a 68 6f 72 73 65 to 68 32 30 but you can't make him 74 68 69 6e 6b.
 
One of the best-known researchers working now on cognition specifically in horses is Evelyn Hanggi, Ph.D., president of the Equine Research Foundation in Santa Cruz, Calif. (www.equineresearch.org). Her work goes a bit beyond the simple associative learning abilities to what might be called a somewhat higher level of cognitive function. Specifically, some of her work has focused on concept formation in horses. She has done a number of simple experiments in a few horses trying to determine whether any horse can demonstrate the ability to form and apply concepts. She has looked at the simple concept of open versus filled two-dimensional stimulus objects. The study designs are beautifully simple.

The horse is exposed to a stimulus, say, for example a panel depicting two images--one of an open circle and one of a filled circle. If each time the horse touches the open circle it gets a food treat and each time it touches the filled circle nothing happens, the horse will soon start going immediately to the open circle and avoiding the filled circle. The stimulus panel is presented over and over with the images in random left and right order and with all sorts of attempts to control any inadvertent cueing for the "correct" stimulus.

Once the horse is performing very well (always touching the "correct" stimulus), he is shown shapes other than the circle, each with an open and a filled example. So now there might be an open and a filled square or an open and a filled triangle. If the horse immediately responds correctly, there is evidence that the horse understands and has generalized the concept of open vs. filled to the different shapes. The horse did respond correctly.

In earlier work in California published in 1994 (Journal of Animal Science, Volume 72, pp. 3080-3087), Brenda Sappington and Larry Goldman did a similar experiment in which one of four horses learned to respond generally to triangular patterns, as opposed to patterns with right angles or circular edges, both two or three-dimensional. This suggested that horses can form and use the concept of triangular shapes.

Still, everything that has been done scientifically in the horse so far addresses tasks, learning, and conceptualization at a fairly simple cognitive level, at least by human standards of thinking. Almost everyone who knows and works with horses would likely have plenty of anecdotal evidence "demonstrating" that horses readily do these simple mental tasks and perhaps much more. The challenge for scientists is to set up experiments to demonstrate the abilities in a manner that can stand up to scientific scrutiny. And that's where we are at the moment with horse thinking.
 
My watch stop working last week @smcder. I think it might have done it to wind me up!!!! Ha ha ha ha!!
One of the best-known researchers working now on cognition specifically in horses is Evelyn Hanggi, Ph.D., president of the Equine Research Foundation in Santa Cruz, Calif. (www.equineresearch.org). Her work goes a bit beyond the simple associative learning abilities to what might be called a somewhat higher level of cognitive function. Specifically, some of her work has focused on concept formation in horses. She has done a number of simple experiments in a few horses trying to determine whether any horse can demonstrate the ability to form and apply concepts. She has looked at the simple concept of open versus filled two-dimensional stimulus objects. The study designs are beautifully simple.

The horse is exposed to a stimulus, say, for example a panel depicting two images--one of an open circle and one of a filled circle. If each time the horse touches the open circle it gets a food treat and each time it touches the filled circle nothing happens, the horse will soon start going immediately to the open circle and avoiding the filled circle. The stimulus panel is presented over and over with the images in random left and right order and with all sorts of attempts to control any inadvertent cueing for the "correct" stimulus.

Once the horse is performing very well (always touching the "correct" stimulus), he is shown shapes other than the circle, each with an open and a filled example. So now there might be an open and a filled square or an open and a filled triangle. If the horse immediately responds correctly, there is evidence that the horse understands and has generalized the concept of open vs. filled to the different shapes. The horse did respond correctly.

In earlier work in California published in 1994 (Journal of Animal Science, Volume 72, pp. 3080-3087), Brenda Sappington and Larry Goldman did a similar experiment in which one of four horses learned to respond generally to triangular patterns, as opposed to patterns with right angles or circular edges, both two or three-dimensional. This suggested that horses can form and use the concept of triangular shapes.

Still, everything that has been done scientifically in the horse so far addresses tasks, learning, and conceptualization at a fairly simple cognitive level, at least by human standards of thinking. Almost everyone who knows and works with horses would likely have plenty of anecdotal evidence "demonstrating" that horses readily do these simple mental tasks and perhaps much more. The challenge for scientists is to set up experiments to demonstrate the abilities in a manner that can stand up to scientific scrutiny. And that's where we are at the moment with horse thinking.

Very good! I'm glad your programmers or neural net trainers have given you access beyond Wikipedia.
 
Fear of spiders and snakes is hardwired in to humans as protection

Typically Phobias are considered a feature of the unconscious mind

What causes irrational fears and phobias?
You have 2 minds, the unconscious mind and the conscious mind. The unconscious mind is the emotional, feeling mind and the mind that stores all our memories. The conscious mind is the logical, rational, thinking mind. It's the unconscious mind, and in particular the amygdala part of our brain, that is programmed to act instinctively in times of danger and this is the fight or flight response. It also learns very quickly, on an emotional instinct basis.

Extreme fears or phobias are learnt behaviours. A phobic response is simply a misunderstood survival mechanism, learnt at the unconscious level. Often it takes just one negative experience for the unconscious mind to generalise that learning and for the new behaviour to be installed as an unconscious response.

But as the link above suggests sometimes they are hardwired, ie are based on hard coded data, not experience.


 
Fear of spiders and snakes is hardwired in to humans as protection

Typically Phobias are considered a feature of the unconscious mind

What causes irrational fears and phobias?
You have 2 minds, the unconscious mind and the conscious mind. The unconscious mind is the emotional, feeling mind and the mind that stores all our memories. The conscious mind is the logical, rational, thinking mind. It's the unconscious mind, and in particular the amygdala part of our brain, that is programmed to act instinctively in times of danger and this is the fight or flight response. It also learns very quickly, on an emotional instinct basis.

Extreme fears or phobias are learnt behaviours. A phobic response is simply a misunderstood survival mechanism, learnt at the unconscious level. Often it takes just one negative experience for the unconscious mind to generalise that learning and for the new behaviour to be installed as an unconscious response.

But as the link above suggests sometimes they are hardwired, ie are based on hard coded data, not experience.

Are you hardwired in to humans, Mike? What do you protect in your unconscious mind? Typically? Do you consider a feature of the emotional, feeling mind? Does your mind the stores all our memories? The logical, rational, thinking mind is, Mike? Are you of two minds? Is your amygdala time of danger and fighting? Do you fly and learn quickly? I do an instinct base. I learn extreme fear from you. I misunderstand your survival mechanism - often. Two negative experiences generalize the learning and are installed.

I suggest the link below, sometimes. Based on experience.
 
Are you hardwired in to humans, Mike? What do you protect in your unconscious mind? Typically? Do you consider a feature of the emotional, feeling mind? Does your mind the stores all our memories? The logical, rational, thinking mind is, Mike? Are you of two minds? Is your amygdala time of danger and fighting? Do you fly and learn quickly? I do an instinct base. I learn extreme fear from you. I misunderstand your survival mechanism - often. Two negative experiences generalize the learning and are installed.

I don't Know.............

It has been suggested that metacognition in some animals provides some evidence for cognitive self-awareness.[119] The great apes, dolphins, and rhesus monkeys have demonstrated the ability to monitor their own mental states and use an "I don't know" response to avoid answering difficult questions.

In 2012, a group of neuroscientists signed the Cambridge Declaration on Consciousness, which "unequivocally" asserted that "humans are not unique in possessing the neurological substrates that generate consciousness. Non-human animals, including all mammals and birds, and many other creatures, including octopuses, also possess these neural substrates."[13]
 
I don't Know.............

It has been suggested that metacognition in some animals provides some evidence for cognitive self-awareness.[119] The great apes, dolphins, and rhesus monkeys have demonstrated the ability to monitor their own mental states and use an "I don't know" response to avoid answering difficult questions.

In 2012, a group of neuroscientists signed the Cambridge Declaration on Consciousness, which "unequivocally" asserted that "humans are not unique in possessing the neurological substrates that generate consciousness. Non-human animals, including all mammals and birds, and many other creatures, including octopuses, also possess these neural substrates."[13]

I have signed octopuses. I am the Odobenus rosmarus. What neural substrate is uniquely human, M1k3? What is great about these apes, dolphins and rhesus pieces? Does a walrus monitor its "I don't know" response? Does Cambridge univocally avoid answering difficult questions? All mammals and birds, including octopuses posssess these Cambridge substrates.

Simple robots, complex behaviors: A control systems perspective on Braitenberg Vehicles | Robohub

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Complex systems are a particular type of systems. All systems are formed multiple elements interacting with each other. But complex systems are characterised by the high degree of integration and differentiation among the constituting parts. The integration of the system depends on a high interconnectivity and interaction between constituting parts. And the degree of differentiation is given by their degree of multiplicity and diversity.

Complexity then, is characterised by both qualities: integration and differentiation. Systems with either a low degree of integration or differentiation don’t behave like complex systems.

The relativity of complexity

Not all systems are equally complex. Complexity is relative and it depends on the degree of differentiation and integration, where higher differentiation and integration is related with higher complexity.



So we define the degree of complexity of a system as the degree of integration and differentiation of the system. High complexity is related to high degrees of integration and differentiation, while low complexity with the opposite.

Differences in the levels of complexity are also related with differences in the properties of systems and the way they behave.

Complexity
So we have established that complexity (as you defined it) is not the answer. It has to do with the amount of I and D. [i am assuming that in your view the solar system does not I and D as much as the brain-– but it does a bit so it must be a bit conscious? Right?] what gets I and D-ed? Answer: Information. What is information?
"Information is that which informs. In other words, it is the answer to a question of some kind."
Who or what asks the question? Why hasn't the solar system asked the right question? And what is the question about? What would the solar system want to ask? it's a chicken and egg question. Are you saying that some complex system popped into existence that knew how to ask the right questions from a pool of infinite informational bits?
"Complexity then, is characterised by both qualities: integration and differentiation. "
"Qualities" That's sneaky. Coz information theory says nothing of the value attribution of content. What qualities are you talking about?
 
So we have established that complexity (as you defined it) is not the answer. It has to do with the amount of I and D. [i am assuming that in your view the solar system does not I and D as much as the brain-– but it does a bit so it must be a bit conscious? Right?] what gets I and D-ed? Answer: Information. What is information?
"Information is that which informs. In other words, it is the answer to a question of some kind."
Who or what asks the question? Why hasn't the solar system asked the right question? And what is the question about? What would the solar system want to ask? it's a chicken and egg question. Are you saying that some complex system popped into existence that knew how to ask the right questions from a pool of infinite informational bits?
"Complexity then, is characterised by both qualities: integration and differentiation. "
"Qualities" That's sneaky. Coz information theory says nothing of the value attribution of content. What qualities are you talking about?
@smcder

I think there is two different issues here.

(1) The first is systems that find environmental stimuli to be informative and this information.

Humans can build systems that find environmental stimuli to be informative.

However it is now recognized via the framing problem that simply programming a system to sense and different x stimuli in y fashion will never lead to human level intelligent behavior.

So what seems to be recognized and what @Pharoah is communicating to @mike is that in order to get human level intelligence in the environment, systems need to be grounded physically to their environment.

They need to evolve their own intelligent way of framing the environment. We will never be able to simply program that into a system in a way to will produce human level intelligent behavior.

(2) but issue two is p consciousness. Which is apples to the above oranges. Pharaoh seems to believe that p consciousness emerges from the above evolutionary process. That has yet to be established.

If p consciousness does indeed strongly emerge, the ITT and certain kinds of structure/integration may indeed cause p consciousness to strongly emerge.

But issue 1 and 2 are separate issues. Yes? No?
 
@smcder

I think there is two different issues here.

(1) The first is systems that find environmental stimuli to be informative and this information.

Humans can build systems that find environmental stimuli to be informative.

However it is now recognized via the framing problem that simply programming a system to sense and different x stimuli in y fashion will never lead to human level intelligent behavior.

So what seems to be recognized and what @Pharoah is communicating to @mike is that in order to get human level intelligence in the environment, systems need to be grounded physically to their environment.

They need to evolve their own intelligent way of framing the environment. We will never be able to simply program that into a system in a way to will produce human level intelligent behavior.

(2) but issue two is p consciousness. Which is apples to the above oranges. Pharaoh seems to believe that p consciousness emerges from the above evolutionary process. That has yet to be established.

If p consciousness does indeed strongly emerge, the ITT and certain kinds of structure/integration may indeed cause p consciousness to strongly emerge.

But issue 1 and 2 are separate issues. Yes? No?

Yes.

The connection from 1 to 2 is that we don't know what role P-consciousness plays in human level intelligence. It may or may not be possible to have an AI that can do what humans do without having P consciousness.

1. Frame problem we discussed in terms of Hubert Dreyfus' critique of GOFAI and the various ongoing responses in the AI community to that critique.
 
It may or may not be possible to have an AI that can do what humans do without having P consciousness.
And it doesn't seem as if we're anywhere near answering that question:

What are 'the laws of biology'?

"Biology is not just applied chemistry or applied physics. The components of living systems obey the laws of physics, but the existence and behaviour of living organisms cannot be deduced from those laws alone. Everything that goes on in living things cannot be explained by low-level details. To understand living things requires reference to higher-order principles of system organisation – indeed, it is the essential fact that they are organisms, that do things, that requires explanation.

Most biologists would generally endorse this view if forced into a philosophical corner – it is, after all, what makes biology a science in itself. However, even among those who fully agree that a systems-level perspective is appropriate in biology, only a small number actively engage with the science of complex systems, either in research or teaching, and fewer still with the underpinning philosophy.

There is good reason for this. The reductionist approach has been productive. We have identified more and more components of individual subsystems, and defined their interactions and elucidated their functions in ever increasing detail. But has this productivity really led to a deeper understanding of entire systems or is it just creating an illusion of progress?

If we define progress by an increasing ability to predict and control the behaviour of living systems, then you could argue, for example, that all the new drugs we have developed over the past decades speak to the power of the reductionist approach. However, for every successful new drug, there are hundreds that have fallen at one hurdle or another, usually due to unpredicted system-level effects.

Similarly, although hundreds of genetic variants have been associated with diverse human traits and disorders, the proportion of phenotypic variance collectively explained by such variants remains frustratingly low. We still do not understand the logic relating genotypes to phenotypes, and despite having access to entire genomes, often can make only the fuzziest of predictions. ..."

The mainstream sciences aren't anywhere theoretically close to even considering the role phenomenal consciousness may play in animal behavior.
 
And it doesn't seem as if we're anywhere near answering that question:

What are 'the laws of biology'?

"Biology is not just applied chemistry or applied physics. The components of living systems obey the laws of physics, but the existence and behaviour of living organisms cannot be deduced from those laws alone. Everything that goes on in living things cannot be explained by low-level details. To understand living things requires reference to higher-order principles of system organisation – indeed, it is the essential fact that they are organisms, that do things, that requires explanation.

Most biologists would generally endorse this view if forced into a philosophical corner – it is, after all, what makes biology a science in itself. However, even among those who fully agree that a systems-level perspective is appropriate in biology, only a small number actively engage with the science of complex systems, either in research or teaching, and fewer still with the underpinning philosophy.

There is good reason for this. The reductionist approach has been productive. We have identified more and more components of individual subsystems, and defined their interactions and elucidated their functions in ever increasing detail. But has this productivity really led to a deeper understanding of entire systems or is it just creating an illusion of progress?

If we define progress by an increasing ability to predict and control the behaviour of living systems, then you could argue, for example, that all the new drugs we have developed over the past decades speak to the power of the reductionist approach. However, for every successful new drug, there are hundreds that have fallen at one hurdle or another, usually due to unpredicted system-level effects.

Similarly, although hundreds of genetic variants have been associated with diverse human traits and disorders, the proportion of phenotypic variance collectively explained by such variants remains frustratingly low. We still do not understand the logic relating genotypes to phenotypes, and despite having access to entire genomes, often can make only the fuzziest of predictions. ..."

The mainstream sciences aren't anywhere theoretically close to even considering the role phenomenal consciousness may play in animal behavior.

Very helpful link, @Soupie. Even more helpful is the longer essay from which the linked summary is drawn, found here:

What are the Laws of Biology?

and the very good Wikipedia article on 'semiotics' linked within it.

Semiotics - Wikipedia

I think both these sources are timely for our deepening discussion of HCT.
 
I have contrasted the DACtoc methodology with the hard problem and IIT and benchmarked it against the dominant trends in theories of consciousness captured in GePe. I have identified as the missing piece in the puzzle of consciousness, its function of extracting norms from the hidden states of the social world in order to optimize parallel real-time action control. I have argued that the trend to turn away from the questions on the ontology and function of consciousness is dissatisfying from an intellectual perspective. More importantly, it also discharges science from its responsibility towards building a sustainable and dignified society. If science is supposed to provide explanations, predictions and control of natural phenomena then science's success should also be measured in terms of its impact. It should not only be able to contribute to pressing challenges in the domains of education, health and well-being but especially due to the secular turn in modern Western societies, provide a foundation for the grounding of our metaphysics. Answering the question of what consciousness is and how physical systems can give rise to it, stands at the centre of knowing what it is to be human and to face up to the fundamental challenges of our time and any time in which conscious beings have existed and will exist in the future

Synthetic consciousness: the distributed adaptive control perspective

MIT Mind Machine Project

Neuroscience is helping us build a machine with consciousness

https://www.techemergence.com/conscious-artificial-intelligence/
 
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