Cognition All the Way Down
aeon.co
aeon.co
So, it could be viewed as cognition all the way down and up. At least as a tool of analysis.
It feels like a way of thinking that elevates analogy between domains up to the level of partial knowledge. And I understand it as being more about generalized properties of networks -- seeing networks that "rhyme", even in totally different domains and strata.
Operating within these frameworks feels like looking at one of those 3D Magic Eye images. "Oh, if I cross my eyes a bit, I can see that death is simply a repeatedly discovered pattern that emerged in virtually all living networks, and death is just a process of collapsing/compressing a complex network agent into a lower dimensional representation that will be referential to other agents. And so how does this repeatedly successful pattern bear on how I should build a government? Or my organization? etc etc"
EDIT: I also find myself curious whether this truth is why we have this predisposition to see beauty in allegory and metaphor and poetics. Maybe our deep history and evolution knows that these things constitute a fuzzy sort of real knowledge. Maybe our biology knows better than us that networks share structure at various levels, and connecting them through linguistic bridges has always served us and made our collective will more powerful.
The only thing that's encoded in DNA is how to make proteins. Everything else is emergent from the interactions of those proteins and "encoded" only in evolutionary history of how those interactions work when they do so in a repeatable fashion. DNA is not a "blueprint" for making a body or a mind... it is much more like the "seed" pattern for a run of Conway's Game of Life, except with a bit of indeterminism for environmental influences thrown in. There are things about the phenotype you can predict from the DNA because you've got past examples, but a small change in initial conditions or the environment during development can also throw you way off... you have to run the whole process (i.e. grow a complete animal) to ever be sure what the phenotype looks like or behaves like.
Wikipedia on the human genome [1]:
> Protein-coding sequences account for only a very small fraction of the genome (approximately 1.5%), and the rest is associated with non-coding RNA genes, regulatory DNA sequences, LINEs, SINEs, introns, and sequences for which as yet no function has been determined.
Wikipedia cites [2].
[1] https://en.m.wikipedia.org/wiki/Human_genome
[2] https://www.nature.com/articles/35057062
Edit: Formatting
The point remains that the products of DNA self-assemble, in the correct environment, into the pattern that determines the organism. Eliminate that environment, and it is just a stew of RNA and proteins.
There should be an upper bound to the complexity of their communication because of game theory. Tit-for-tat only supports an error rate of up to 9 percent, so at the upper bound cells will need to differentiate.
This is a lot of domain knowledge to accelerate the computation by, provided the theory is correct.
That doesn't seem plausible to me. DNA, just like a compiled program, is a set of instructions for a specific computer. I don't believe you can extract the meaning of a program without understanding the computer that is supposed to run it (except perhaps by statistical analysis of its results when being run, which is generally how we are studying it today).
Now, if we did have a deep understanding of cellular machinery, of the way cells organize into organs and organisms, and of the functionality of each of these organs, including the brain, and the way they collaborate to produce cognition, THEN we could perhaps decompile the DNA into a high-level algorithm, where we could say something like 'these are instructions for programming a stem cell to specialize into a cell which feeds cells that react when this chemical is encountered in concentrations greater than X over a time period of Y'. But this is likely the opposite approach to what you were asking - you would need to have an almost complete understanding of the biochemistry of the entire body, and of the way it gives rise to intelligence, at which point the DNA itself may not be so important anymore in the hunt for AGI.
This made me think of what forces of life are maybe engaging in within this universe: We can't know the structure of the machine running this simulation, but if we probe the results of the running simulation enough, we can understand everything of the system running it.
In the Einstein sense, maybe that's how we know God? :)
Note that he proposes both a problem and a solution, which are two separate entities. There may exist other solutions to cognition of incompleteness.
I think that if the problem of and solution to incompleteness in cognition did not exist then we would experience these computational inconsistencies similar to migraine blind spots. However we don't, and we perceive the error in computation as a single entity and not as two boundaries.
However, they haven't yet convinced their approach is useful. I note that their approach can't (yet?) begin to answer their own worm question (which head will the worm have?) either, and their analogies to software and hardware seem simplistic.
As an article this is worthwhile, and their proposal may well turn out to be a useful research direction, but it's not there yet. Hopefully there'll be a part 2.
P.S. There's no need to convince us that multicell organisms are compatible with PD as the article tries to do - so what if they weren't?
Unsure how Aeon is doing this; some sort of URL trickery?
> You think we shouldn’t anthropomorphise people?
The mechanistic/behaviorist way of looking at the world is fundamental to science as a discipline, and I suspect this originated from the crisis of religion - the split between matter and spirit, in terms of concepts. Consciousness and cognition have an uncomfortable resemblance to what we used to call "spirit".
It reminds me of the "uncanny valley", how some machines are starting to behave awfully close to living creatures; and machine learning ("artificial intelligence") producing results that seem as if there's an awareness, a mind of its own.
We know that they are just mechanisms, all matter and no spirit, but our guts sense a kinship - we have an emotional reaction to life or things that act like they're alive, like they're thinking. We look at an ant, moving around in the world, sensing and feeling, looking back at us with its eyes - and most of us would "anthropomorphise" it, to relate to it as "one of us". Our subjective experience tells us that we're not just objects, but something more, special, magical even.
But, having rid of magic, science must understand and explain convincingly the mystery of life and mind, the very strange material existence of ourselves.
Looking at how slime moulds crawl through mazes to find food, I get an uncanny feeling that it's alive and has a primitive mind. Or those sped-up films of plants reaching out their vines and tendrils, holding onto things and climbing toward the light - it has something in common with us at a fundamental level.
Science offers explanations for these phenomena, yes - but it seems there are still missing pieces, concepts, models, to tell the full story. Self-organization of matter, swarm behaviors, distributed intelligence, information and computation..
A mind without an observer would indeed be uncanny valley stuff. I always ask people who claim consciousness does not exist if they are indeed undead, or merely confused by the terminology.