Re: representation and consciousness

Thank you for the insights
it would be good to get CG activities designed around these points


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On Sat, Jul 17, 2021 at 3:21 AM ProjectParadigm-ICT-Program <
metadataportals@yahoo.com> wrote:

> The way out of the "mess" of representation is to look at what linguists
> and philosophers say about natural language representation and "formal"
> representation.
>
> Six things here are key, (1) observation and coupled with it sense
> perception, (2) neural processing of perceived data, (3) encoding for
> storage,(4)  retrieval of stored information for recognition, (5)
> adaptation of stored information and (6) cognition.
>
> Neuroscience, in particular neural circuits and systems, cognitive and
> behavioral neuroscience and computational neuroscience have made great
> strides in the study of the biological underpinnings of cognition and
> related processes.
>
> The emerging picture is of a highly complex functionality where the brain
> can create structures of up to 11 dimensions for storage (Source: Blue
> Brain project). At the cellular level quantum effects can come into play,
> and for short term memory, long term memory and memory search, biological
> processes involving genes activated tor trigger release of biochemical
> compounds, even triggered snapping of DNA residing in the nuclei or other
> parts of brain cells at precise breakpoints, all create a very complex
> system of interacting foci in the brain each contributing to network
> activity that can lead to recognition/comparison with stored data,
> (adapted) storage, cognitive processes leading to action etc.
>
> Our (western) concepts of knowledge representation are based on formal
> mathematical systems and logical systems. Godel, Turing, Church and Chaitin
> have pointed out the limitations of mathematics, logic, information science
> and computability and according paradigms for knowledge representation.
>
> The dichotomy of mathematical abstractions (which may represent abstracted
> internalized perceived real world objects and their properties), and real
> world sense perceived objects is subject to quantum effects and a fiercely
> debated field of philosophical inquiry.
>
> It should be clear that knowledge representation based on purely
> mathematical and logical formal systems will not do.
>
> Graph theory, knowledge graphs, category theory and the theory of complex
> adaptive systems are useful tools in describing some aspects of the
> complexity of processes, where the emphasis is less on the objects and
> their properties and more on the interrelated processes.
>
> I recommend we take the point of view of seeing learning (to adapt) as the
> key ingredient. Sentience, sapience and consciousness, and perception and
> cognition are currently not formally describable.
>
> The "learning" viewpoint makes the most sense, both biologically but also
> in the artificial intelligence domain. If we can somehow add free will,
> i.e. (the axiom of) choice, causal reasoning to the now existing mix, we
> may be able to advance the field of artificial intelligence.
>
> There are however three major hurdles to  overcome, (1) to create
> explainability, (2) bias, (3) and ethical issues.
> '
>
> Milton Ponson
> GSM: +297 747 8280
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
> Project Paradigm: Bringing the ICT tools for sustainable development to
> all stakeholders worldwide through collaborative research on applied
> mathematics, advanced modeling, software and standards development
>
>
> On Wednesday, July 14, 2021, 11:04:57 PM ADT, Paola Di Maio <
> paola.dimaio@gmail.com> wrote:
>
>
> This is an interesting talk relevant to this  CG as  cognitionm AI KR and
> Neuroscience are converging
> https://www.youtube.com/watch?v=OAmB5SOS2LQ
>
> Neural representation is a key neuroscientific concept meant to bridge
> brain and mind, or brain and behavior. But what is meant exactly by a
> “neural representation”? Conventionally, a neural representation is a
> correspondence between something in the brain and something in the world, a
> “code”. The encoding view of representations faces two critical issues,
> empirical and theoretical. Empirically, I will show that neural codes do
> not have the properties required to naturalize mental representations.
> Theoretically, it raises the problem of “system-detectable error”
> (Bickhard): if the brain sits at the receiving end of the code, then how
> can it know if the representation is wrong? As John Eccles has concluded,
> the logical implication is dualism – there must be a “decoder” that
> translates brain properties to world properties. Consequently, a number of
> authors have argued that representations are not only homuncular but also
> unnecessary: adapted behavior results not from calculations on an internal
> copy of the world, but from coupling between body and world – “the world is
> its own best model” (Brooks). Anti-representationalism introduces crucial
> concepts missing from the conventional view (embodiment, autonomy,
> dynamicism) but it struggles to explain some aspects of anticipation and
> abstraction. I argue that the problem with representation is to think of it
> as a “thing” that can be manipulated and observed (like a painting), which
> collides with the dynamical nature of brain activity. I suggest to shift
> the focus from the encoding properties of brain states, a dualistic
> concept, to the representational properties of brain (and body) processes,
> such as anticipation and abstraction.
>
>