ᛕᎥᕼᗷᗴᖇᑎᗴ丅Ꭵᑕᔕ @Kihbernetics@qoto.org

@tg9541 @psybertron

Semantics, information, meaning, systems, models, representations, purpose ... those are all categories we "invented" to explain what we ***think*** to other thinkers.

The primary concern in Cybernetics and automation always was (and still is) #control of things within its environment, with representation, modeling, or #explanation used only to the extent that serves this primary function.

Now, an agent doesn't need to "understand" the "semantics" of what they are doing. Agents like living cells, for example, just have to respond correctly to the syntax of the genetic message, like any other *mechanism*, to jointly produce a more complex organism agent able to "understand" and communicate what's going on and not necessarily for control purposes.

@tg9541

>Kennedy was assassinated in 1963, but in his first State of the Union the following January, Johnson urged passage of the pending Kennedy automation commission bill. Congress obliged, and on Aug. 19, 1964, LBJ signed the legislation that formally created the National Commission on Technology, Automation, and Economic Progress, noting, ***“If we have the brainpower to invent these machines, we have the brainpower to make certain that they are a boon, not a bane, to humanity.”***

😀

https://www.washingtonpost.com/history/2023/10/29/automation-technology-fear-artificial-intelligence/

@janhoglund

Nothing is perfect. The #system (and consequently the #model built upon it) is always a selected subset of all the #variables available for the #control of the #machine.

#WR_Ashby in "Design for a Brain" (chapter 2/5) explains in more detail the meaning of the word "system":

>Because any real 'machine' has an infinity of variables, from which different observers (with different aims) may reasonably make an infinity of different selections, there must first be given an observer (or experimenter); a system is then defined as any set of variables that he selects from those available on the real ‘machine’. It is thus a list, nominated by the observer, and is quite different in nature from the real ‘machine’. Throughout the book, ‘the system’ will always refer to this abstraction, not to the real material ‘machine’.

As you can never control **all** the variables of any given "machine", there is always the possibility that the variables that you don't control will generate some unforeseen consequences.

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.

#Consciousness, like #awareness is not a *thing*. It is a #state or property of the part of an entity's #cognition (which *is* a thing) that the entity may *be* conscious or aware of ... or *not*.

Furthermore, consciousness is a #binary proposition. One can be either conscious of something or not. You can't be a *little bit conscious* the same way you can't be a *little bit alive*.

@psybertron @yoginho

There is no doubt that physics was working well before we introduced measurement, math, and computation.

I think it was Kauffman who said that the reason why mathematics works so well with physics is because it was **invented** to explain physical facts. I was looking for the exact quote but found this instead:

https://kauffman2013.wordpress.com/

I read a sample of Robert M. Sapolsky's new book *Determined: A Science of Life without Free Will* on Amazon, and I really don't see why some people find it "revolutionary". I find it full of half-baked contradictory claims that don't hold water even under quick superficial scrutiny like this.

Brains don't generate behaviors. They #produce motor responses to sensory stimuli that an outside observer then interprets as the behavior of the observed individual in their immediate environment. The observer can also stick electrodes in the brain of the individual and then correlate the observed behavior with the measurements performed on some of the neurons and then conclude that those firings have caused the behavior. However, even if it was possible to replicate the exact sequence of the observed firings of all the neurons, the observed behavior would be different if the "response" of the environment was also not exactly the same as during the measurement.

Determinism alone doesn't "cause" anything even if there are no such things as "causeless causes". The current #state of the system is obviously determined by its previous state and the current sensory inputs, so there are at least two separate "determinisms" in play here all the time, and, as an individual existing in its particular environment, I have at least **some** #control over the unfolding of both, my biology (eating, drinking coffee), and my environment (writing this nonsense)😉.

@sozialwelten

Sorry. I'm re-drafting the post because the link does not work for some reason it replaces the two dashes between "On" and "the" with one long dash. I'll try to post this as plain text maybe it works.

It works😀 :

"http://www.polanyisociety.org/MP-On--the-Modern-Mind-1965-ocr.pdf"

I wish people who are coming up each day with a new "breakthrough" theory using physics and/or quantum mechanics to explain everything from complexity and life to consciousness and free will, would read first what #M_Polanyi has said about it.
This is from:
http://www.polanyisociety.org/MP-On--the-Modern-Mind-1965-ocr.pdf

@AndrewMurphie@indieweb.social

I see quite a few theories emerging lately that make no distinction between #structure and #system and this is just one of them.

Structures behave deterministically under the influence of natural #laws and are thus predictable, inherently purposeless, and controllable.

Systems, on the other side, besides being made of structures that must abide by those same natural laws, are also governed by arbitrary #rules that define their #purpose, either designed or evolved within a larger environment.

Dynamical systems (with memory) have in addition the ability to learn and modify those rules. How this happens can be influenced but not fully predicted or controlled by an external observer, especially for living systems.

It is this ability to resist outside control that I consider "*free will*".

@AndrewMurphie@indieweb.social

Each one of us is undoubtedly the product of our genes and shaped by the history of all the interactions we had in life, but this sounds a little bit over the top, doesn't it?

>Then look at the forces that brought them to the professor’s office, feeling empowered to challenge a point. They’re more likely to have had parents who themselves were college educated, more likely to hail from an individualistic culture rather than a collective one. All of those influences subtly nudge behavior in predictable ways.

Students with uneducated parents coming from a "collectivist culture" are less likely to challenge authority? I beg to differ.

Also, "*more likely*" and "*trying not to be a jerk*" are not quite deterministic statements, and all the processing and choices I make unconsciously are made by no one else but me and free of any external influence.

This is so wrong I wouldn't know where to start.

>Hurricanes are ‘selected’ based on their ability to perform functions dictated by the environment, the researchers found.

Gimme a break!🤨

#M_Polany in "Life's Irreducible Structure" (1968) points out that using deterministic #machines to explain "the physics of #life" is backward thinking, because machines are devised and built by humans to resemble organisms and to serve the purpose of their design, and can therefore only be a #biological, not a #physical analogy.

>The organism is shown to be, like a machine, a system which works according to two different principles: its structure serves as a boundary condition harnessing the physical-chemical processes by which its organs perform their functions. Thus, this system may be called ***a system under dual control*** (*emphasis mine*). Morphogenesis, the process by which the #structure of living beings develops, can then be likened to the shaping of a machine which will act as a boundary for the laws of inanimate nature.
...
In the machine, our principal interest lay in the effects of the boundary conditions, while in an experimental setting, we are interested in the natural processes controlled by the boundaries."

Or in other words, we are interested either in the *control* #rules of the machine or the physical #laws of *causality* that make the machine work.

Wiener was wrong. There is ***no*** #communication ***in*** either the animal or in the machine, only #control by the application of #constraints to their inner flow of matter and energy.

Communication is established ***between*** animals and/or machines, and, as Shannon correctly recognized, requires an independent communication #channel susceptible to the environmental disturbance called #noise.

In order to be able to communicate animals and machines must share a common #language or cipher #rules used to code their respective messages. Communication is always one-way and does not require feedback. The sender has no control over the message after it is sent through the channel.

A special case of communication is #observation where the communication is established between the observer system and phenomena in its environment not necessarily produced by other systems "languaging".