Anton Zheltoukhov

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A Thousand Narratives. Theory of Memetic Evolution. Part 2/20
A new way of doing the same thing

"Is an ant colony an organism, or is an organism a colony?" 
- Mark A. Changizi

As of now, there are two kinds of evolution: genetic evolution and memetic evolution. The first one is your usual evolution concerned with "change in the heritable characteristics of biological populations over successive generations", responsible for all the biological diversity that we know, and happening on the scale of at least hundreds of years. Memetic evolution, strictly speaking, is just a particularly powerful set of adaptations that appeared in primates (and unique only to them), that enabled the accumulation of adaptations during a lifetime, responsible for the cultural progress of humanity, and happening on the scale from minutes to years depending on definition.

The meme as a concept was coined by biologist Richard Dawkins in his 1976 book "The Selfish Gene"[1] and refers to units of cultural information that are transmitted from person to person through imitation or other forms of cultural transmission. Like genes in biological evolution, memes can undergo processes of variation, selection, and transmission that can lead to their spread or decline within a population.

Memetic evolution became possible after the introduction of several key mechanisms: the obvious suspects such as language and social learning; their dependencies like signaling (prelinguistic communication), {niche construction, extended phenotype}[2], scaffolded upbringing, theory of mind; and development of necessary neural substrates enabling all these mechanisms (whatever they are)

The main benefit that the development of meme evolution has brought up is the drastic increase in problem solving capacity (both on the level of population and, more importantly for this post on an individual level)

While general dynamics remained the same (organisms being innovation aggregators) the details have changed:

  • Selective pressure also had changed, now being pointed at storing knowledge and social interactions. This might be viewed as the last big impact of genetic evolution - the creation of the adaptation loop driving memetic evolution. Which resulted in humans having bigger brains more suitable for both.
  • From that moment onward species switched (arguably fully) towards the accumulation of innovations through memes instead of genes. Individuals that were for some reason deprived of access to the meme pool effectively got thrown back to primates in terms of environmental success.
  1. ^

    Richard Dawkins. The Selfish gene. https://www.goodreads.com/book/show/61535.The_Selfish_Gene?from_search=true&from_srp=true&qid=oWwQlQJHhQ&rank=1

  2. ^

    Richard Dawkins. The extended phenotype. https://www.goodreads.com/book/show/61538.The_Extended_Phenotype?from_search=true&from_srp=true&qid=Ko5sX4zBtL&rank=1

A Thousand Narratives. Theory of Memetic Evolution. Part 1/20. Intro

The ultimate goal of this line of research is to gain a better understanding of how human value system operates. The problem I see regarding current approaches to studying values is that we cannot study {values/desires/preferences} in isolation from the rest of cognitive mechanisms, cause according to latest theories values are just a part of a broader system governing behaviour in general. With that you have to have a decent model of human behaviour first to then be able to explain value dynamics.

To get a good theory of the mind you have to meet multiple requirements:

  1. A good theory of the mind must span at least four different timescales: (genetic evolution) for the billion years in which our brains have evolved; (memetic evolution) for the centuries of cultural accumulation of ideas through history; (personal) for the individual development during lifetime; and (neuronal) milliseconds during which cognitive inference happens.
  2. A good theory must explain behaviour of the system on each of Marr’s three levels of analysis[1]: (1) the computational problem the system is solving; (2) the algorithm the system uses to solve that problem; and (3) how that algorithm is implemented in the “physical hardware” of the system. And, the part I think Marr is missing, the third level also has to include explanation of how the learning environment affects agent.
  3. A good theory must at least make an attempt at answering the main questions: how is the generality of intelligence achieved?; what is the neural substrate of memory?; etc.

To meet these requirements I’ve combined insights from several fields: Developmental Psychology, Neuroscience, Ethology and Computation models of mind. The result is the Narrative Theory. The research is still far from completion but there are already interesting insights to be shared.

At this moment NT is similar to Shard Theory in many ways, but it also differs from it in many others: (1) NT is trying to integrate “more distant” but still crucial perspectives (like ethology and linguistics). (2) It is concerned with the flow of development of human behaviour as a whole instead of focusing of values. And (3) NT is only concerned with human intelligence, for now ignoring the topic of artificial agents entirely.

It’s pretty audacious to say that one can make progress on something as big as computational theory of human behaviour but there are two things giving me hope of succeeding: (1) It’s been quite a while since the last wave of overarching psychological theories. (2) The last decades were sort of a divergent period of scientific inquiry (when it comes to mind studies), efforts mostly have been focused on puzzling out the smaller pieces of The Problem and there have been no serious attempts at updating previous theories with newly found evidence (or even integrating those theories between each other). These together promise that there is now a room for improvements to be made.

Note on vocabulary. Each mentioned theory has it’s own unique language. This may present a problem for unprepared readers. While I will unpack and rephrase convoluted terms when possible, not everything can be stripped away.

This post is structured as follows: (the first section) is a list of constraints discovered by various mind related fields that are crucial for building an overarching theory mind; (the second section) presents the first claims of Narrative Theory built according with known constraints; and (the third section) covers implications of the theory, problems and future work directions.

  1. ^

    David Marr.  Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. https://academic.oup.com/mit-press-scholarship-online/book/13528

For me, it's all about getting more posts on that topic. A post could be bad in terms of text quality. It could be "false" or badly reasoned. But if I consider the topic underrated I will upvote it.