Here is Richard Dawkins promoting part one of his autobiography at Google:
Ray Kurzweil is the host. Questions begin 18 minutes in.
Memes only get a brief mention at the very end of the video. They don't get very much space in the book either.
Dawkins gives his take on the evolution of cooperation near to the end in response to a question. Kin selection and reciprocity get mentioned. Group selection does not.
Another recent video has Dawkins being interviewed by Michael Shermer. Again the evolution of cooperation is a significant theme.
In universal Darwinism, many optimization processes in nature are seen as being Darwinian.
There are many examples of such optimization processes outside biology. Lightning finds the shortest path
between storm clouds and the ground. Cracks seek out the path of least resistance. Water on mountains
finds the steepest downhill path. Water on flat ground finds the path that maximally erodes the surface it flows over.
If you look at optimization techniques used in computer science, they include "genetic algorithms" and "memetic algorithms" - which are inspired by biology. However, there are also "gradient descent" and "simulated annealing" - which are named after relatively simple physical processes. These non-biological optimization techniques are simple and primitive - compared to biologically-inspired techniques - but they are still capable of performing useful work.
Physicists with knowledge of non-equilibrium thermodynamics typically use "maximum entropy thermodynamics" and the maximum entropy principle to explain these effects. The question physicists will probably have - when contemplating universal Darwinism - will be: what does it offer that maximum entropy ideas do not?
It is an excellent question, but one with some good answers, I think:
Universal Darwinism explains some cases where maximum entropy thermodynamics struggles. Increasing entropy isn't the only possible fitness function that can be applied to populations - and adaptations can locally favour other optimization targets in relevant selective environments. These are cases which universal Darwinism can handle but where maximum entropy thermodynamics doesn't typically help very much.
Lastly, maximum entropy thermodynamics and universal Darwinism are quite different-looking theories with different histories. Darwinism is better developed in many respects. It has better models of lock ins, sub-optimality, combining existing solutions and other phenomena. Physics can benefit from Darwinism's maturity.
Other types of optimization in physics
Another example of optimization in physics involves the opposite of hill-climbing: gradient descent. This can be demonstrated with a single ball bearing moving on a landscape - with little sign of a population, of copying, or of selective elimination.
Physics also features the principle of least action - which is probably its best-known optimization process. This works on the same principle as Galton's board (see right).
Putting a ball bearing into Galton's board computes the maximum value of the normal function - using gravity. The more iterative choices the ball faces, the better the board performs its optimizing task. The principle of least action is a broadly similar kind of optimization process. Galton's board illustrates iterated choices - but not terribly much reproduction. The balls and the gravitons involved are both produced at one location - and are clones of each other - but this copying seems rather remote from the optimization process itself.
An example of the principle of least action involves refraction of light. This case represents a challenge for population-level descriptions of optimization processes in physics. However, if considering a photon as a single point particle, refraction makes little sense. Only when a light wave is modeled as a spread-out, distributed phenomenon, can refraction can be understood.
The principle of least action hardly seems Darwinian at all. It can be modeled in simple physical systems devoid of much in the way of populations or copying. However, the search for shared principles that underlie the cases of optimization in physics may yet turn out to be a fruitful one.
The existence in mechanics of two actions and two corresponding variational principles which determine the true trajectories, with a Legendre transformation between them, is analogous to the situation in thermodynamics (Gray et al. 2004). There, as established by Gibbs, one introduces two free energies related by a Legendre transformation, i.e. the Helmholtz and Gibbs free energies, with each free energy satisfying a variational principle which determines the thermal equilibrium state of the system.
These other cases of optimization in physics raise the issue of what counts as optimization and what doesn't. Practically any physical system could be described as optimizing the function of behaving as it does - though such explanations may violate Occam's razor. The lightning strike in this post's illustration certainly looks as though it is performing search for high ground using a branching tree. However, we really need criteria relating to what qualifies and what doesn't.
If cultural evolution's effects are sufficiently strong, phenotypic effects due to nuclear DNA might be swamped by the effects of cultural variation. Perhaps egalitarian memes might act to eliminate variation at the level of DNA. Or maybecultural tags and tribal identifiers evolve quickly and generate so much phenotypic variation that the effects of nuclear DNA are swamped. In either case, population bottlenecks at the level of DNA might not matter much.
On balance, it seems unlikely that cultural variation makes the effect of recent population bottleneck on the variation in human DNA irrelevant. A good rule of thumb is that around half the variation in a typical trait is down to DNA. Cultural variation is important, but not so important that DNA doesn't matter.
A memetic hazard is defined as information with three main attributes. The first attribute is that it spreads from person to person, whether through personal contact or some form of recording. The second attribute is that this information causes some form of distress, whether as benign as mental stress to the individual or as dangerous as societal dysfunction. The third attribute is that it must cause preoccupation–that is to say, it maintains sufficient presence in the host’s mind that either a significant portion of his attention remains focused on it, or it plays a significant part in his decision-making process.
I might be inclined to play down the significance of the last attribute. One important way of measuring memetic hazards is by their severity. Some memetic hazards waste a small quantity of time. Others take over people's lives and ruin them.
Propaganda represents a memetic hazard on a national scale.
Memetic hazards are a type of information hazard. Want to be specific? Use the term 'memetic hazard'. Want a more general term that also covers individual learning? Use the term 'information hazard'.
Memetic hazards are not necessarily harmful to all. Some will have strong memetic immune systems. Some may actively benefit in some way from propagating them.
William Croft on Language Evolution, Language Change vs. Language Evolution Studies, Linguemes - Units of Language Evolution, Modeling Language Evolution with Linguemes, Mathematical Modeling of Language Evolution, Reticulation and Language Evolution Trees.
Linguemes are memes made of words or sentences. I'm not sure they need their own whole word. It probably brings more harm - in dividing linguists from the rest of the memetics literature - than it offers in benefits. However, I don't know this with much certainty.
The Applied Evolutionary Epistemology Lab has a YouTube channel is here.
Daniel Dor on Language Evolution, Development vs. Evolution, Evo-Devo and Phenotypic Plasticity in Language Evolution, Language as Collective Innovation and the Book "Social Origins of Language".
The Applied Evolutionary Epistemology Lab has a YouTube channel is here.
Monica Tamariz on Language Evolution, Cultural Levels, How Cultural Evolution models differ from Biological ones, and Simulating the Cultural Transmission of Language.
The Applied Evolutionary Epistemology Lab has a YouTube channel is here.
The material about mammalian imprinting mechanisms imprinting individuals on their cultures seems both insightful and probably correct.
Applying the term "cultural survival vehicle" exclusively to human tribes seems very wrong to me, though. Surely a physical bible is at least equally deserving of such a title.
Epigenetics is a hot topic these days - at least according to Google Trends.
We seem practically bound to have epimemetics in one form or another. However, it seems destined to be a controversial topic. I'll say briefly here what I think it should mean:
Firstly, I'm pretty happy with Waddington's use of the term "Epigenetics" to refer to influences on development not coded for in nuclear genes. I'm not happy with the subsequent hijacking of the term to refer to non-nuclear cellular inheritance. Since genetics is - or should be - the study of heredity, the we can't call the study of non-nuclear inheritance "epigenetics" - that would be an oxymoron. I explain this in more detail here. We just don't need to use a major genetics term to refer to "the study of mitotically and/or meiotically heritable changes in gene function that cannot be explained by changes in DNA sequence". The whole idea is a scientific farce.
That brings us to epimemetics. Using the term in Waddington's manner suggest that epimemetics is the study of epimemesis - or information acquired during ontomemy.
Just as brains acquiring information from their environment during development is epigenesis, so, computers acquiring information from their environment during development is epimemesis.
A complication with the concept of epigenesis is whether "epigenetic" information can consist of other genes. Epimemetics faces a similar issue: whether epimemetically-acquired information can consist of other memes. I favour an affirmative response - but currently I'm happy to leave the resolution of these controversies to future researchers.
Machine intelligence research experienced a "winter" - followed by something of a a modern renaissance.
The "winter" was characterized by reduced funding and interest in the topic. The term was coined by analogy to a nuclear winter.
I think meme researchers have experienced some winters of their own. Probably the main winter was from around 1900 to 1970 - when interest in the topic began to increase in a number of areas.
There was a large and obvious meme renaissiance in 2011. Around the same time, cultural evolution became much more popular, with many more researchers and papers appearing. However, memetics itself has been slow to experience the knock-on benefits of this. Indeed, compared to the situation at the turn of the century, interest in memetics seems to be at a low ebb.
Essentially, I blame academia for this situation. Academia is sensitive about the issues surrounding social Darwinism. A "tread softy" approach appears to have been taken. Notoriously, academia is little concerned with finding the truth, but rather is about with credentialing experts and forging affiliations. The meme pioneers included a lapsed parapsychologist and a self-help-guru and poker player - and were a raggedy bunch. For whatever reason, the outcome has been a disaster. Most researchers within academia seem ignorant or confused about memetics - and are often ignorant or confused about the whole idea of cultural evolution too. It's an ongoing disaster for scholarship in the area.
Before the development of culture, ideas were mortal - and died with their human hosts.
Cultural transmission lead to potentially-immortal ideas - with a correspondingly greater scope for cumulative adaptive evolution.
Cultural transmission also produced much larger idea pools - with more variation within each pool.
Before culture, ideas could only recombine with other ideas inside the same head. With culture, ideas could recombine with ideas from other individuals. The larger idea pools provided much greater scope for ideas to recombine. For the first time, ideas from men could recombine with ideas from women. Ideas from experienced individuals could combine with ideas from inexperienced ones.
The enlarged idea pool became a meme pool. With greater diversity and more scope for outcrossing this resulted in an enlarged human brain (with more space for memes) and the invention of science, technology and the internet. The memes then set about constructing a diverse range of new bodies and minds for themselves.
Richard Dawkins has said that stars might "go information" - rather than "go supernova". The existing cultural explosion might well continue to build until this happens.
Matthew Zimmerman is someone who has a reasonable understanding of cultural evolution. Matt's publications include a paper on the topic of this video: Cooperation, Evolution of - Matthew Zimmerman, Richard McElreath, Peter J Richerson. I commented on the paper here.
This one is a brief and concentrated video introduction to memes and Blackmore's "temes" - in three minutes. The supplied title is: "Can Meme Haz Science?!"
Here's Jonathan Zittrain on internet memes at ROFLCon III. The blurb for this one reads:
Jonathan Zittrain delivers the keynote address to ROFLCon III at MIT, May 4, 2012. In this talk he considers how memes arise, why some work and others don't, and what values they represent.
Lewontin's pioneering 1970 article "The Units of Selection" was an important milestone for universal Darwinism, and helped to promote the science of cultural evolution. Lewontin wrote:
Darwin's scheme embodies three principles (Lewontin 1):
Different individuals in a population have different morphologies, physiologies, and behaviors (phenotypic variation).
Different phenotypes have different rates of survival and reproduction in different environments (differential fitness).
There is a correlation between parents and offspring in the contribution of each to future generations (fitness is heritable).
These three principles embody the principle of evolution by natural selection. While they hold, a population will undergo evolutionary change. It is important to note a certain generality in the principles. No particular mechanism of inheritance is specified, but only a correlation in fitness between parent and offspring. The population would evolve whether the correlation between parent and offspring arose from Mendelian, cytoplasmic, or cultural inheritance.
Lewontin's principles boil down to variation, selection and heredity.
Lewontin offers a description of evolution by natural selection. However, other types of evolution don't require fitness to be heritable - namely genetic drift. In some respects, it would be better to have a characterization of evolution, rather than just one mechanism of evolution.
Note that Lewontin's principles don't guarantee that adaptations will accumulate. The conditions required for cumulative adaptive evolution are much more demanding. Lewontin's principles cover devolution and the loss of adaptations as much as adaptive evolution.
Lastly, Lewontin's principles tend to lead to a kind-of distorted neo-Darwinian perspective. They are a bit vague about what counts as a "parent" and what counts as an "offspring" - but they clearly include splitting, but make no reference to "joining". Merging is very important in evolution - and should be classified as a form of evolutionary change. Merging includes symbiosis and sex. The most common forms of merging involve parasitism by viruses - which are ubiquitous.
Merging has been systematically neglected by evolutionary theorists in the past. It still needs more emphasis.
It reports on the successes of meme therapy targeting violence. It also discusses the difficulties in getting people to accept an epidemiological approach to violence. Of course, violence as a mind virus is pretty much part of memetics 101.
When I was a child I learned in science class that distinguishing living systems from flames and crystals using a definition was hard, and that the best approach was to use a 'MR GRENS' definition - an acronym which defined life as involving: Movement, Respiration, Growth, Reproduction, Excretion, Nutrition, and Sensation. As a fairly intelligent child, this definition was not very satisfying.
Later in life I learned about evolutionary theory. It became clear that life was what evolved. I found this idea had been codified by J. Maynard Smith and Eors Szathmary - in "The Origins of Life", p.3:
What is life? [...]
An alternative is to define as living any population of entities possessing those properties that are needed if the population is to evolve by natural selection.
Still later I learned about Universal Darwinism, and the project of Darwinizing physics. The principles of Darwinian evolution were not confined to biology. They applied to inorganic systems - propagating cracks, electrical discharges, turbulence, drainage systems, etc.
At this point it became clear that the Maynard Smith / Szathmary conception of living systems had some issues. Either practically everything was alive, or this definition of life was in need of a rethink.
The latter option seems much more attractive than attempting to change the meaning of a common concept.
I think the concept of systems that exhibit cumulative adaptive evolution is more appropriate as a definition of life. Evolution by natural selection just isn't enough to pin the concept on life-as-we-know-it.
One problem with this idea is that it arguably includes structures such as drainage basins - which evolve adaptively over extended periods. For would classify drainage basins as being "alive". This definition may not be perfect - but it seems like a step forwards. At least cumulative adaptive evolution excludes many cases of degenerative Darwinism.
Positional inheritance and velocity inheritance offer high fidelity transmission of information when physical objects split - allowing for adaptations to arise in physical systems. Copying with variation and selection in physics is a relatively simple and obvious application of Darwinism.
Darwinian physics is currently mostly an unknown topic in the mainstream. There's someQuantum Darwinism out there - but it is hard for most people to assess the worth of this material. Darwinian models apply well to fairly simple Newtonian systems. These models are more comprehensible and should be easier for most people to understand and accept.
Darwinian physics lacks some of the complications that cause social scientists to get into muddles about memes. For instance, simple physical systems have pretty undirected variation - allowing the standard neo-Darwinian assumption that mutations are random with respect to fitness to be applied - without much loss of modeling realism. The simple physical systems used as examples in Darwinian physics are easier to understand than the complex structures involved in human cultural evolution.
Darwinian physics has been worked on. Bickhard and Campbell's 2003 paper covers the topic - listing crystal growth, convection cells and catalysis as targets of explanation. D. B. Kelley's book on Universal Darwinism also covers it. However, for whatever reason, the subject area has not yet become mainstream knowledge.
Physicists are reasonable people. It seems reasonable to expect that they will regard the project of Darwinizing physics with less hostility than social scientists regard the project of Darwinizing culture.
Another reason to put energy into Darwinian physics is that physics has historically been a "high-status" science. If physicists come to accept that Universal Darwinism applies to basic inorganic physical systems, that will be a big and important feather in the cap of Darwinism.
Social science is still the area of greatest social and political importance for evolutionary theory. It's the area where there's the greatest need for correct, Darwinian science. It's the area where backwards, pre-Darwinian science is doing the most damage. It's an area where religious attempts to distort science get a lot of funding. However, Darwinian physics can contribute to this project indirectly - by helping to apply increased pressure to the social scientists on multiple fronts.
In my 2011 book on memetics, in the chapter on Universal Darwinism, I proposed that there were numerous advantages in classifying evolutionary events into the categories "production" and "elimination" instead of "selection" and "drift". The concepts are especially appropriate when teaching evolutionary theory.
My proposed division broadly matches the "creation" / "destruction" dichotomy - though we can't easily use those terms, because they are not always technically correct.
Hodgson and Knudsen's proposal is in chapter 1 - which is available online here. They call the intersection of selection and elimination "subset selection" and the intersection of selection and production "sucessor selection".
My proposal is better, though. Hodgson and Knudsen subdivide selection, but they don't seem to notice that precisely the same division can naturally be extended to subdivide drift as well.
Apparently, one of the things anthropologists dislike about memes is the way they subdivide culture.
Here is Maurice Bloch in 1995:
In sum, the culture of an individual, or of a group is not a collection of bits, traits or memes, acquired from here and there, any more than a squirrel is a collection of hazelnuts.
My usual (patronizing) reply is that it's a basic scientific modeling technique to split thing up into pieces and analyze the pieces. It's called "reductionism" - and it is one of the most successful tools in the scientific toolkit.
Nonetheless, some anthropologists apparently think that memeticists focus too much on the bits of culture, and not enough on how the bits interact.
My way of framing this criticism (within the terminology of memetics) is that they are saying that memeticists focus too much on the memes, and not enough on meme contexts. By "meme context" I mean: everything else in the universe, apart from the meme in question.
However, I think that phrasing the criticism this way illustrates that there's a grain of truth to the accusation - and also suggests why meme contexts might be being somewhat neglected: they are large, complex and difficult to analyze.
I previously nominated
positional
inheritance as the most common kind of inheritance.
The second-most common kind is probably velocity inheritance. The term
"Velocity inheritance" refers to the way in which entities that split tend to inherit their parent's velocity. The offspring pieces tend to inherit the velocity of their parents.
Turbulence illustrates velocity inheritance fairly clearly. Or think of the way the targets break up in clay pigeon shooting.
Velocity inheritance is quite a lot like positional inheritance - but there are some differences:
Positional inheritance is always high-fidelity. However, the fidelity of velocity inheritance breaks down considerably when the particles involved become very small. In particular if the offspring particles are neutrinos or photons, velocity inheritance is not very high fidelity. You can also see poor velocity inheritance if you smash small objects into much larger ones at enormous speeds.
Some may find that velocity inheritance is easier to understand than positional inheritance. Velocity is more obviously a property of objects that is copied when they divide. Others find it more confusing - and get caught up in (irrelevant) concerns about relativity and frames of reference.
Other "simple" properties are inherited too when entities split - mass, angular momentum, charge, etc. The inheritance is not not always which such high fidelity as is seen in position or velocity inheritance.
Notoriously, evolutionary theory applies to populations. For evolution to operate, you need to have a population of variants for natural selection to choose between.
That evolutionary theory doesn't apply to individuals is enshrined in definitions of evolution, and is in textbooks (for example, Mark Ridley's "Evolution" textbook).
Note that biological evolution refers to populations and not to individuals. In other words, populations evolve but individuals do not. This is a very important point. It distinguishes biological evolution from other forms of evolution in science (e.g., stellar evolution).
Here's Graham Bell (1997):
Individuals do not evolve; they develop, reproduce, and die. The characteristics of organisms, however, may change through time.
However, in universal Darwinism, individuals do evolve. Their brains evolve via learning. Their bodies evolve during development. Most Darwinian individuals are, in fact, populations on closer examination. Animals are populations of cells. Cells are populations of bacteria. Bacteria are populations of molecules. Molecules are populations of atoms - and so on. Many of those populations clearly evolve over time - event by completely standard evolutionary theory.
What are the neo-Darwinians thinking about? It isn't clear - but I think they are maybe trying to divide the evolutionary process up - so it only applies to one population (or level) at a time.
This seems silly. You can't have a system evolving from one perspective and not evolving from another one. Herbert Spencer's concept of a single unified evolutionary process is far superior. Here's Herbert Spencer (1862):
there are not several kinds of Evolution having certain traits in common, but one Evolution going on everywhere after the same manner.
Long ago, the idea that individuals were themselves composed of populations was not understood. It took a while to understand that these populations evolved by Darwinian mechanisms in a non-trivial way over individual lifespans. However, now this is understood. The idea that individuals do not evolve is outdated dogma. Dogma often takes a while to die - and this is a case in point.
Hi. I'm Tim Tyler, and this is a video about incorporating observers and observations into Darwinism.
Universal Darwinism generalizes many of the principles of evolutionary theory, giving it a broader range of applicability and extending it to cover the inanimate world. One such principle is natural selection. Universal selection applies broadly to the natural world, harvesting asteroids and atoms - as well as ants and aardvarks.
A closely-related concept that can be similarly generalized is "survival of the fittest". Richard Dawkins, writing on page 12 of "The Selfish Gene", wrote:
Darwin's survival of the fittest is really a specific case of a more general law of survival of the stable. The universe is populated by stable things.
This proposed law of "survival of the stable" has subsequently not received proper attention. However it too is a specific case of a more general law, which might be referred to as: "observation of the observable".
Dealing with observability implicitly includes all cases of survival - since, in order to be observed, entities must have survived. However it expands the scope of original idea in two ways - to include:
Potential observables being hidden, and...
Observers failing to observe fully;
With this modification, Darwinism can be accurately applied to entities which are merely hidden - instead of ones that have failed to survive. This allows evolutionary theory to be applied to cases such as the Tall poppy syndrome - where entites are selected on the basis of their visibility - rather than because their competitors failed to survive.
Survival - from "survival of the fittest" is an important determinant of what we observe, but it is not the only factor involved.
The new principle also incorporates selection effects acting on observers and their perceptual apparatus into evolutionary theory. Such effects have classically been studied in the context of "the anthropic principle". However, the term "anthropic" was always unfortunate - since it implies the effect only applies to humans - whereas, in fact, any observer will do: animals and machines can act as observers too. Universal Darwinism brings observation effects under the umbrella of evolutionary theory. It includes cases where observers are sleepy, deluded, lacking awareness, or have perceptual limits.
Darwinism is the most appropriate framework for modeling the effect of selection on observations and observers. The expansion of Darwinism to deal with "observation of the observable" is long overdue. Previous iterations of the theory have made no mention of observations or observers, but this development puts them back into Darwinism at its heart. To fully explain scientific observations, we have no choice but to use the more general and broadly-applicable principle.