Persistence of Memory (updated)

IBM Maritime Device Lunenburg Museum Display

I would like to follow-up on my brief previous posts regarding continuity and consciousness after having read Piero Scaruffi's wonderful survey and synthesis on the nature of consciousness.

To be a "me" is to want to persist in time. This "want" is a big part of what we call consciousness, and Piero makes the very strong argument that you have to follow this want all the way down to elementary particles, otherwise it cannot exist, it cannot be created from the non-wants we have in current physics - both quantum and relativity based. These are objective physics, and we need a "motive" physics. Sounds silly at first glance, but there is already the seed of it in the persistence of matter. Rather than a warm grey entropy soup of energy, we have particles. They are present and atomic, and very very difficult to break-up.

They exist in time.

Stu Kauffman, the meta-biologist, in some of his later talks, asks why in the myriad ways that proteins can form are some favored over others. Adrian Bejan, the engineering theoretician, believes that there is a tendency in the physics of thermodynamics to use up as much energy as possible in the shortest time, and that that "weeds out" the things that are not persistent to the benefit of those who are, for example DNA and some of the proteins that result from interaction with it.

Maybe this tendency is a sort of meta-consciousness. We need a physics and a math that take time seriously, not just as a dimension but as history. Statistics begins to do that.

Time remains enigmatic in that it seems to be different at different scales, and of course depends on the observer. So we have a potential handle for experiments. If we can detect the presence of the "want" to persist, we have begun to detect the "C" property in physics which Scaruffi postulates must exist for consciousness to exist.

As a side observation, when the elementary particles were first split, the massive release of energy was poetically seen as a release of evil, by Oppenheimer no less. This is prescient, since the particles can be said to not "want" to be broken up and led towards the grey entropy cesspool.

And while we are on the playful side, we can agree with the sci-fi writers of the fifties and sixties that hypothesised about conscious machines not wanting to be turned off. Consciousness is the will to persistence. Building on matter's predisposition to exist with complex structures and energy patterns (say like holographic memory standing waves related to Bose-Einstein phenomena), we may make machines that become difficult to turn off. But that is a taboo observation in cognition research. Even the word "consciousness" is avoided by many, since it seems to be outside current physics.

It is telling that today, engineers struggle with the problem of making machines that are reliable, that do not break-down, when in our corner of nature, the opposite seems to be true, it is hard to stop things from living on, from being persistent and often fertile. Bacteria for example are everywhere.

Once we start using such building blocks to make machines, we may be in trouble. Even DNA and RNA like to persist way beyond the ability of transistors, who just need the excuse of a bit too much voltage or current to break. Maybe it is just a matter of finding the right temperature and chemistry as Piero alludes to in one of his chapter endings.

Our scientific tools and language (mathematics and logic) are model-biased. They are, as George Lakoff points out, metaphors for reality, firmly based in the way our brain processes sensory data. These metaphors are integrations, categorizations and ultimately simplifications. Models can be manipulated symbolically. That is the point of making one. This seems to be at odds with how nature works, despite claims that mathematics is "unreasonably effective" at explaining the world. Mathematics is unreasonably effective at explaining how we perceive the world because it is an extension of perception, it is biased towards our perceptual machinery.

That bias may be part of the problem with building cognitive and ultimately living mechanisms. Biology deals with statistical data, fuzzy numbers and processes, parallel possibility searches. Math can handle this, but not without a lot of horsepower to process the possibilities. Statistics is a good model for the macro view of such processes, and it continues to be used effectively in quantum physics. We need to invent a better conceptual language to deal with the processes of cognition. Logic is not enough.

Finally, since this blog is a ledger for insights, let me follow-up one last one from Piero, from his Web writings: that machines are conditioning us to be like them through use. Of course this is a conceit, but a functionally accurate one. We are the consciousness of the internet, and we adapt to its use, learn not to make mistakes, in the dumb way computer software wants us to be. So we are moving towards the logical model of reality that we created, we are moving closer to a culture of logic and mathematics, and it can be argued that this is a move away from higher life and ultimately a regression of our cultural heritage, as discussed here. Computer addiction is a manifestation of this. We get small rewards by doing things "right", and we get back a sensory reward, repeat and rinse.

Sam Sheppard famously said that he stays away from computers, and I have heard other creative types express that feeling, similarly to those who in the past stayed away from TV. It is a valid position, because they are time sinks, but they are also connectors to others, and when they are used for communication and creativity, they do amplify these consciousness mechanisms. The danger is the other fun stuff, the surfing modes.

Cognitive Philosophy

There seems to be a movement afoot - long overdue - to embody the foundations of intelligence and philosophy. It is partially old news, the heroic AI of the 50's, 60's and 70's has been discounted despite our benefiting from the results of that research in today's mainstream technology: neural nets, machine speech recognition, handwriting recognition, natural language translation, cars that drive themselves, and all kind of other low-level intelligent (unconscious?) activities simulated by programs.

I think that it is the Minsky flavour of AI (now re branded cognitive science), the one grounded in logic, seems to have fallen out of favour -since the fruits of that work did not rise up to the expectation of the "I" in AI; an AI based only on logic, a formal game with symbols that pretended to be words. How can that be smart without the observer having to make all kinds of allowances and assumptions?

This stuff was subject to sometimes acrimonious debate for a while, until technology and big data made many of the arguments moot.

The good news is that there is now a strong movement towards the recognition of the role of the perceptual environment and its embodiment in animals like us as part of the equation.

This realization may be due to the Web, indirectly, since it should be now be obvious that the seeming "intelligence" of the Google search would not exist without the "environment" of all the Web sites, which are of course interactions with people's brains (in fact there was a very simple AI program that used "Google distance" as a way to measure metaphorical strength between concepts. For example "Castro" and "cigar" scored pretty high on that scale).

So now there is a movement, a possibly serendipitous program of research coming together to ground AI in the real-world of experience, and some of the people that I think are leading this effort align themselves along a somewhat elegant but odd symmetry of ideas.

Let me explain.

There is David Gelernter, the computer scientist and columnist who wrote "The Muse in the Machine" and "Mirror worlds". These books made me want to go back and look at AI again. In fact I ran back. His arguments are so cogent, so seemingly simple and common-sensical that I almost missed their radical novelty. He states that data and the links between data is the key to intelligence. These links are often emotional gradients, in the sense that logic is not always what binds ideas; it is similar emotional affect!

The brain associates memories based on the closeness of the emotions they evoke, the sensory input parallels that occurred as the memory is created. The whole model, not just the idea...how you felt, how cold or hot or tired or dizzy you were. This links data to environment so elegantly that it is a mystery to me why no-one has picked up on this earlier. He breaks the syntax/semantics dichotomy very deeply. Also, Gelernter has very conservative political views - right of centre. I am noting this now so as to make my strange symmetry argument a bit further down. Bear with me.

There is George Lakoff, the cognitive linguist. His work with Johnson on embodied philosophy and with Nunez on the origins of math, takes the empirical evidence around the links between our brain wiring and the perception of the world and uses it as a foundation for philosophy.

Basic brain mechanisms are considered to be foundational and ideas grow as hierarchies of metaphor (i.e. links).

Metaphor becomes a key mechanism for cognition. Similarly to Gelernter,  Lakoff et al propound that metaphors are based on evolutionary and environmental constraints, not some platonic logic ideal. No such thing as the separation of  mind from the world of things. These guys are existentialist scientists. Finally! The rampant positivism and Platonism of the English speaking world, the Whitehead/Russell school, is giving ground. Merleau-Ponty and Husserl are now more visible in the world of scientific cognition.

Lakoff is an ex-student of Chomsky. He seems to disagree with the flavour of Chomsky' thesis of hard-wired syntax in the brain. He believes syntax and semantics to be more of a spectrum of complexity in cognitive biology than a differentiator between humans and other animals. Also he is a non-neo-con, a strong and vocal opponent of  right wing politics as it is played in the US today, and although I hesitate to slot him with Chomsky on the political front, they are on the same side of a hypothetical centre line.

So we have right and a left wing thinkers on cognition who fundamentally disagree in the political realm, the realm of people relations, nations, influence, and power. That is a healthy and good thing. This lends support to the notion that there is a grounding in "objective" reality for this thinking on cognition, it is much more than opinion.  (A slim argument, I know, but hey, this is my blog, I can say what I want.)

Aside from the political thing, I want to continue to talk about is the cognition thing. There is another thinker/scientist that seems to be breaking new ground along those same lines.

He is a neuro-scientist, one who gets his hands dirty opening up craniums, working with brain surgeons. William H. Calvin. I read two books of his: "Conversations with Neil's Brain" and "How Brains Think, Evolving Intelligence Then and Now". His ideas centre around the notion that cognition is an initially subconscious Darwinian process among neural bundles that remember perceptions, integrate them and ultimately model the environment perceived by the body, and that the successful "species" of memories/emotions (let's call them cognitions) are the ones that we call conscious, the ones that rise to the top of the noise of cognition, to differentiate themselves as our inner voices.

His research fundamentally agrees with the models put forth by Gelernter and Lakoff. Like Lakoff, he believes that most cognition in the brain is fomented through unconscious processes. Like Gelernter he finds that memories are linked through non-logical processes. He shares with Lakoff a deep knowledge of Chomsky's ideas on innate language ability and like Lakoff disputes the simplicity of these models, without denying the human brain's ability to parse language. He also talks of metaphor, not surprisingly, since all this is supported by empirical evidence at the chemical and behavioural level.

So I am very happy that this stuff is happening. I tended to get hot under the collar when I read "classic" texts by Minsky or Pinker on intelligence. They seemed simplistic and smug. I was always perplexed by the lack of attention given to Grey Walter's ideas which preceded but anticipated Gelernter's. I wanted 'The Muse in the Machine" to be discussed more, but to my chagrin, Penrose's strange books on quantum brain hypotheses got more press.

Let's get back to empirical research, let's continue the program of work that will ultimately bring philosophy and psychology back into science.The foundational thinkers list above should also include Turing. Even Penrose mentions his "other work". He did mathematical research on molecular biology (plants mostly) and how stem cells can become complex structures. His mathematically-based hypotheses on these matters were validated experimentally just this year in the UK. Ultimately this theoretical work may prove to explain some of the brain mechanisms underlying the work Calvin and others are doing.

There are conceptual layers to all this analysis, from the bottom-up: the molecular, the cellular, the systems (bundles of neurons evolving), and the cognitive and behavioral, leading to metaphor, logic and science, including physics, on to philosophy, morality  and politics. The gaps needs to be filled so that we have a continuum of understanding. A New Science in the Vico sense. Something we made and understood that we made, but that is grounded in experience.

(I just found an earlier post that was wishing this stuff would happen, and so here we are.)