ᛕᎥᕼᗷᗴᖇᑎᗴ丅Ꭵᑕᔕ @Kihbernetics@qoto.org

Most theories of #consciousness start with #information while a proper way to address any neural theory of consciousness should be as a #control science because the primary function of the nervous system is not to process information but to control the body.

Most control is internal to the system, a distributed, analog, homeostatic ***unconscious*** #regulation 1️⃣ of essential internal variables that are keeping the body alive and well. None of the mechanisms on this level "cares" about what is happening outside of the body.

Only on the next level do we find the kind of information necessary for the rate-dependent negative #feedback_control mechanisms 2️⃣ keeping some *external* controlled variables within limits engaging (through the use of regulators) in performing whole-body actions (behavior) in the immediate environment. Those actions can be conducted either ***consciously or unconsciously***.

Finally, on the highest level, we have the rate-independent, open loop always ***conscious*** #governance 3️⃣ maintaining the long-term goals and providing stability and direction to the lower level of control that will plan, implement, and track the fulfillment of those goals.

Even if you are gullible enough to believe LLMs are like brains, with their own 'minds', you must surely realize that they are 'brains in a vat'.
There are three ways one can take from here:
1️⃣ Use them as intelligence amplification tools;
2️⃣ Equip them with bodies;
3️⃣ Join them inside the vat.😏

For David Chalmers, virtual reality is genuine reality, at least until lunchtime 😀

https://youtu.be/7s0SzcUnzZo?feature=shared&t=637

A #representation is not something that can be found in an observer's mind. Representations are physical copies or models of the object they represent and they are all residing in the same domain external to the observer's mind.

According to #CS_Peirce, a #sign (the ***representation***) is something that brings its #interpretant (the #observer), into *the same sort of correspondence* (#state of mind) as the #object it stands for. Therefore, #information and #knowledge exist in a different domain internal to the system

#Representation = #Reproduction.

The representation can be a #copy, or the re-#production of the object using the same #substance the object is made of (e.g. a *carbon copy* of a page or a copy of a living cell). In contrast, a #model (a map) is the reproduction of the object's form in a different substance.

Unlike real (artisanal) art, the reproduction (copy) of "digital art" is indistinguishable from the original. In addition, what is usually referred to as the "digital copy" of a physical work of art, is, in fact, a digital *model* of the real object it represents.

>Although the history of science and ideas is not my field, I could not imagine adopting Alfred North Whitehead's opinion that every science, in order to avoid stagnation, must forget its founders. To the contrary, it seems to me that the ignorance display ed by most scientists with regard to the history of their discipline, far from being a source of dynamism, acts as a brake on their creativity.

***On the Origins of Cognitive Science*** - *The Mechanization of the Mind*

by J-P Dupuy and translated by M. B. DeBevoise

*An examination of the fundamental role cybernetics played in the birth of cognitive science and the light this sheds on current controversies.*

https://mitpress.mit.edu/9780262512398/on-the-origins-of-cognitive-science/

A Springer Open access book from @decidim

**Decidim, a Technopolitical Network for Participatory Democracy**

*Philosophy, Practice and Autonomy of a Collective Platform in the Age of Digital Intelligence*

https://link.springer.com/book/10.1007/978-3-031-50784-7

The difference between a #Transformer and a #Transducer is that a *transformer* can re**form**ulate (modify the form) of the same substance, while a *transducer* can re**produce** the form observed in one kind of substance into the *same* form but in *another* type of substance. This kind of *reproduction* is usually called the #model.

*Terrence W. Deacon* writes beautifully about this conundrum:

https://royalsocietypublishing.org/doi/10.1098/rsta.2022.0282#d7508913e1

I have a somewhat different position on his second statement, however.

I think there **is** a self that determines **how** the system responds to an external perturbation.

Found it! 😎. It is called the
***Maximum Entropy Production Principle (#MEPP)***:

>The so-called maximum entropy production principle (MEPP) is known much less (even among specialists in physics of nonequilibrium processes). This antipode, as its name seemingly means, of Prigogine's principle has been overshadowed by its more famous twin. MEPP was independently proposed and used by several scientists throughout the 20th century when they dealt with general theoretical issues of thermodynamics and statistical physics or solved specific problems. By this principle, a nonequilibrium system develops so as to maximize its entropy production under present constraints.

https://www.sciencedirect.com/science/article/abs/pii/S0370157305004813

A system doesn't ***feed*** on #order (or #negentropy) from the environment it has to ***create*** it.

You can't get your desk organized by just acquiring some order from the environment. You have to do some #work and use some of your #free_energy. Schrödinger admits as much:

#Life as the ultimate form of #self_organization is usually thought of as ***resisting*** the *Second Law* of thermodynamics that says all #order eventually dissipates over time into a state of thermal equilibrium and enduring uniformity (disorder).

An alternative explanation says that organization (order) spontaneously emerges in dissipative structures ***because*** of the Second Law of Thermodynamics because ordered structures are much better at dissipating energy (thus more rapidly increasing the #entropy) than disordered ones.

The explanation (for which I now can't find the proper reference😟) exemplified this with whirlpools and how they spontaneously emerge because the water molecules in them don't bump into each other as much so the flow through the drain (transition to an equilibrium state) is faster when they are streamlined (organized) into a vortex.

#Trust is #Experience over #Time.

#AI and #Trust

>I trusted a lot today. I trusted my phone to wake me on time. I trusted Uber to arrange a taxi for me, and the driver to get me to the airport safely. I trusted thousands of other drivers on the road not to ram my car on the way. At the airport, I trusted ticket agents and maintenance engineers and everyone else who keeps airlines operating. And the pilot of the plane I flew in. And thousands of other people at the airport and on the plane, any of which could have attacked me. And all the people that prepared and served my breakfast, and the entire food supply chain—any of them could have poisoned me. When I landed here, I trusted thousands more people: at the airport, on the road, in this building, in this room. And that was all before 10:30 this morning.

https://www.schneier.com/blog/archives/2023/12/ai-and-trust.html

1️⃣ Kihbernetic #System with
2️⃣ fundamental #Processes: a recursive #Autopoietic self-production for growth and learning, and a linear #Allopoietic production of "other things", such as behavior and waste, distributed in
3️⃣ Control #Levels, of #Regulation, immersed in, and dealing with things in the system's environment, #Control for managing the workload of different regulators, and #Guidance to provide long-term goals and preserve the identity of the system, all using
4️⃣ #Variables: sensory #Input of data and other resources, motor #Output of behavior, #Information as the difference that will make a difference in the subsequent (updated) #Knowledge state, all interconnecting
5️⃣ #Functions: the #Control-ed #Reaction to external stimuli, the #Perception of sensory states, the #Prediction of the expected outcome of past behavior, and the repeated #Integration of new information into an updated knowledge state.

>"#N_Wiener’s preoccupation with mathematics, echoed in #WR_Ashby’s commitment to mechanical models and #Hv_Foerster’s conception of formal descriptions, largely excluded social phenomena in which cybernetics was practiced."

#K_Krippendorff's last paper

https://constructivist.info/19/1/082.krippendorff

A 3D #space of a natural #system can be visualized as created from the interaction of 2D #planes made of #matter and of #energy that modulate (change the form of or constrain) each other, leaving a 1D #information #sequence as a record of how their interaction unfolds in #time.

All #learning must be open-ended. The learning agent (the #observer) must have the #autonomy to set its own learning goals as well as plan and execute a #sequence of #exploration activities to achieve these goals.

One can never learn *all existing data* but rather refine their understanding of the data that is available to them. As true for human intelligence, you can either have "deep and narrow" specialized #AI agents or "average and broad" #AGI. You can't have both in the same entity. Time and #memory "limitation" are the main inspirations for #diversity and #cooperation between learning agents.

People should have figured it out by now that the #distribution of processing power, not the #centralization in gargantuan data and control centers is the right thing to do.

Stop working on LLMs (Large Language Models) and start working on PCAs (Personal Customizable Assistants).

From: https://arxiv.org/pdf/2311.00344.pdf

The current craze over *social media ruining democracy* and *AI posing an existential threat to humanity* stems from the fact that most people don't understand that the only thing #technology is able to do is *amplify* their own capacity to do good or bad.
The Internet and AI are communication and intelligence #amplifiers, the same way motors and servo mechanisms are amplifiers of our muscle power.