ᛕᎥᕼᗷᗴᖇᑎᗴ丅Ꭵᑕᔕ @Kihbernetics@qoto.org

Unless I see evidence that someone else already introduced it in similar terms, I will claim here that I've come up with (yet another😀) theory of consciousness I will aptly name a "Kihbernetic Theory of #Consciousness" or "#KTC".

According to this theory #regulation in a dynamical system is always #unconscious (innate or learned, like driving a bike), #guidance is always #conscious (i.e. it assumes there is #intention, teleology, conscious seeking for answers), and #control can be either conscious or unconscious.

For example, one can be focused on (have conscious control over) a conversation while unconsciously controlling a vehicle they are driving, and then momentarily switch their #attention to some unexpected situation on the road that the regulators were unable to resolve by themselves.

Reading about different theories of #consciousness while trying to understand why it is such a "hard problem" and just had an idea. I'm sure someone has already thought of it, but here it is just in case:

Both #unconscious and #conscious neural activity are carried on by the same neural network mechanisms. The only difference between the two is that unconscious activities happen in #parallel, like a wave, while all conscious activity is performed in a #sequence.

We can experience multiple things and are able to perform multiple **unconscious** activities at the same time, but we can focus our conscious #attention only on *one thing at a time*. This is why we are flipping between two different views of the Necker cube and we can't *see* both versions at the same time.

Both conscious and unconscious activity affects the current #state of the neural network (our thoughts), but only conscious thoughts can be memorized and later recalled because they are "recorded" as sequences of events (stories).

This is totally different from computer #memory which mainly stores and retrieves separate, out-of-context data points.

Introducing the *qualitative* category of #Wisdom in the triad made of *quantifiable* #Data, #Information, and #Knowledge items adds nothing to the better understanding of the matter.

Saying someone or something is "wise" is just a subjective judgment made by an external #observer about another (#observed) system's behavior *appropriateness* to the given situation in the environment without knowing anything about the observed system's internal state, goals, or motives.

In addition, a really "wise" entity would never identify itself as such.😀

>"The mathematics of quantum mechanics works incredibly well as a predictor of what this data should be. It will not give you certainty, but it will give you reliable probabilistic predictions."

It is definitely **not** a *mystery*. #Quantum #Constructivism is just like every other #Science, which will also *not give you certainty, but it will give you reliable probabilistic predictions.*

https://bigthink.com/13-8/quantum-mystery-interaction/

The #control functions in a dynamical system such as a living organism are distributed on three levels:
1️⃣ The automated and predominantly *unconscious* #regulatory functions are responsible for any *immediate* response and maintaining the system's *homeostasis* in the face of external disturbances.
2️⃣ The working parameters for these "regulators" are changed based on actions planned, directed, and modulated by the *conscious* #control functions seeking to optimize the use of the regulators and fulfill "high-level" goals, aspirations, and other *needs* that originate on
3️⃣ The "highest"#governance control level which maintains *long-term* drives that the system may be either aware (conscious) of (voluntary), or deeply ingrained in some unconscious habits, or innate.

It is evident from this short presentation that #consciousness resides primarily on the *middle* control level that has the ability to make *predictions* of future events and compare such expectations with the *perception* of reality as provided by the regulators. All in order to extract the *difference* between the two, or the #information that will be subsequently *integrated* into the #knowledge structure of the system to improve control.

Many people think that "history doesn't repeat itself" so they dislike #models because "they are based on the #past and thus not useful for identifying all the #complexity associated with the #changes that will happen in the #future."

This is most likely because they think models are for producing #forecasts, while the best use of models is, instead, to plan future #experiments.

#Predictions are often made as statements about what **will** occur in the future, while they should be only statements about #expectations of what **may** most probably happen in the (most immediate) future.

Predictions based on historical data define the boundary of the narrow conical "#possibility_space", the "volume" of which rapidly increases with longer prediction times.

idem ...

>The concept of #language was modeled more and more after those emerging from interactions with computers, the "computer languages." It is clear that the syntax of these languages must be obeyed meticulously, otherwise ''garbage in - garbage out."
>Unfortunately, under the leadership of one of the foremost linguists in America, Noam Chomsky, the logico-mathematical principle of fulfilling rigorous #syntactic requirements in so-called "well-formed formulae" was transplanted into the domain of natural languages and became a criterion for "linguistic competence." This aspect of language ignores the essential role as a means of #communication and perceives language as an end in itself. It is in this castrated form that one believes language is "linear," that questions have unique answers, that the linguistic problem is to generate "well-formed sentences," and other misconceptions that have their roots in perceiving language as a monologue.

#HvFoerster on the origins of #computational_neuroscience

>For reasons that still baffle me, it was the pragmatic American engineers and scientists, not the romantic Europeans, who began to toss anthropomorphic sand into the gear box of evolving notions and ideas. To name two such cases, the computer people began to talk about a machine's storage system as if it were a computer's #memory, and the communication engineers began to talk about signals as if they were #information.

>Perhaps these were the precursors for the second derailment which, ironically, was the inverse of the first. lt worked as follows. The first phase was #anthropomorphization: mental functions projected into machines. However, we knew how these machines worked because we built them and wrote the programs. Consequently, an appropriate "#mechanomorphization," the concepts dealing with computer hard- and software were projected back into the workings of the brain and, presto!, we knew how the #mind worked.

*Heinz Von Foerster
*To know and to let know - an applied theory of knowledge*
Canadian Library Journal, Vol. 39, No. 5, October l982.*

Some pretty obvious and standard things are described here as novelties:

https://www.linkedin.com/pulse/re-wilding-leadership-seven-threads-rich-watkins?trk=news-guest_share-article

Basically:

1️⃣ #Leaders exist because they have #Followers,
2️⃣ Leaders are here to provide #Guidance within the #Regulation and #Control "hierarchy"
3️⃣ All #Measurement is personal and beneficial only to the measurer
4️⃣ The "hated" #Matrix organizations are connecting silos
5️⃣ Removing what is #NOT determines what IS #Possibile (the cone of possibilities)
6️⃣ Groups of people will form #Living systems that cannot be engineered but can only be maintained as a "garden"
7️⃣ #Negative feedback is the only useful #feedback. A "pat on the back" never helped anyone. 😀

Also, this is all set backward:

> How can we ensure there are useful leadership Artefacts (tools, processes) and leadership Heuristics (rules of thumb, ways of doing things) - as well as Skills, Experiences and (of course) Natural talent.

I understand that as a consultant you have the "urge" to sell something tangible (a product) but you always have to start with the #People and their experience, skills, and natural talent, then identify the #Processes, what they do, and how are they connected (collaborate). Selecting the #Products (tools, SW, forms, space, facilities) that will support that is the last and the least important thing.

Btw, a process is not an #artifact (product). Only the "rule book" that describes the process is, and there is a huge difference between the two.

Another very interesting passage showing a deep understanding and appreciation of Pattee's work:

>This is how the two processes that necessitate symbolic description connect in Pattee’s theory: **the biological function of #measurement is to #control**. Living organisms are able to form many kinds of such measurement–control networks. The outcome of the measurement process may feed directly into the control network (as in tropisms). But, according to Pattee, for control to be displaced in space and time (e.g., delayed with respect to measurement), a symbolic coding must exist. **The two processes of measurement and control fulfill the difficult ‘‘cementing’’ role between the #symbolic and the #dynamic, the discrete and the continuous, the static and the time-dependent**. Even though the measurement process may be a dynamical one, its function, according to Pattee, cannot usefully be described by the same dynamics it is measuring. It is only in this sense that dynamics and symbols (the informational record of a measurement) are irreconcilable’’ or complementary

Not all #control in real #life requires an immediate response of the dynamical #system to what's happening in its environment.

>Constraining the behavior of a system in a functional way, i.e., control, can be exerted here and now—by the specific parameters of environments. Such is the case of tropisms: a plant turns in the direction of a light. However, in cases in which control is displaced in time, the functional ‘‘freezing’’ of some degrees of freedom has to be written somehow and somewhere (i.e., some form of memory must occur), and—if one wants to have a physical description of this memory process—according to Pattee, one has to employ an alternative sort of description in the form of time-independent constraints. This description is "symbolic’’ in the sense of consisting of timeless structures, having external significance, that—themselves—form a system, being non-arbitrarily linked together by certain rules. According to Pattee, the two kinds of description (symbolic code and physical laws) are incommensurate. Neither is reducible to the other.

J. Rączaszek-Leonardi building on #HH_Pattee's work on Reconciling #symbolic and #dynamic aspects of #language

https://www.academia.edu/899225/Reconciling_symbolic_and_dynamic_aspects_of_language_Toward_a_dynamic_psycholinguistics

A #hierarchy is an #emergent property of an otherwise "flat" #network composed of randomly connected elements.

>"The craze with all things #quantum is not just because of its inherent weirdness. It’s motivated by a #reductionist impulse that has been animating science from Robert Hooke in the 17th century to Stephen Hawking in the 21st."

https://iai.tv/articles/reality-is-not-revealed-by-quantum-mechanics-auid-2512

Read the pdf here if interested in this kind of stuff:

https://stream.syscoi.com/2021/08/10/disorder-order-discovery-or-invention-von-foerster-1984/

#H_v_Foerster defines #complexity as
>"the number of #cycles it takes to compute the arrangement from the description".

When the description is much shorter than the arrangement it describes, we have #order, and when the length of the description is the same as that of the arrangement we have #disorder.

>"If the length of the description approximates the length of the arrangement, it is clear that *we do not understand this arrangement*."

😀

I see more and more individuals doing "organizational change in complex systems" frowning on the mention of "best practices", documentation, and planning, because:

> "in an increasingly interconnected world where technology, information, and customer expectations evolve at an accelerating rate, insights from past performance quickly become irrelevant in many scenarios"

https://medium.com/topology-insight/best-practices-are-useless-in-complex-systems-f7797a12071

All such "modern approaches" to dealing with *complex systems* forget that the *insight from past performances* is the **only** thing we can actually rely on while preparing for the uncertain future.

They also forget that organizations normally work, not in any one of the *clear, complicated, complex, and chaotic domains* at any point in time, but they are rather *in and out of all of those situations all the time*, and different parts of the same organization can also be in different situations at the same time.

Best practices are also not "silver bullets" as they would like you to believe. Best practices are the default (only possible) response the system can produce to par the current situation because it depends primarily on the #knowledge_state the system is currently in.

Having *diverse perspectives*, allowing time for *experimentation*, and maintaining short and direct *learning loops* are not some new and "improved" methods the organization should start adopting when things get complicated or complex, but should be rather part of the (documented and planned) very ***best practices*** an organization adopts as the *normal way of doing business*.

>"It’s not just Love Island: “fake British accent” videos have over 188,000 views on TikTok, where young people say they use the voice whenever they feel uncomfortable."

Maybe a way of unconsciously adopting a "Keep Calm and Carry On" perspective in unexpected circumstances?

https://getpocket.com/explore/item/why-are-so-many-young-americans-adopting-fake-british-accents

>"If time didn’t have a direction, it seems to me that would make time into just another spatial dimension, and if all we’ve got are spatial dimensions, then it seems to me nothing’s happening in the universe."

https://getpocket.com/explore/item/a-defense-of-the-reality-of-time

The use of the terms #transformer and #transducer seems somehow different in #AI than in other #engineering disciplines.

In engineering a "transformation" means altering the #form of the same #substance and "transduction" is used when the form is "produced" in another (different) substance.

For example, a #transformer will change (reduce or increase) the voltage "pressure" of an AC current source while a #transducer such as a microphone will change an **acoustic** pressure (wave) to an **electric** signal.

https://www.assemblyai.com/blog/an-overview-of-transducer-models-for-asr/

#Hallucination is defined as "an #experience involving the apparent #perception of something not present". Consequently, it requires a #sensory apparatus.

Because an #LLM does not have the ability to experience its surroundings except through user-provided prompts, an erroneous statement generated by the model should be called a (computational) #mistake, not a hallucination.

It cannot be a #lie because there is no #intention involved in the generation of the statement.