Friday, 18 July 2014

Lessons in memetic hitchhiking from "Weird Al" Yanovic

Take a quick lesson in memetic hitchhiking with the latest videos from "Weird Al" Yanovic.

Al neatly illustrates the art of spreading his content by linking it to popular trending content.

Another way of looking at this sort of thing is in terms of retromemes.

Of course both retromemes and memetic hitchhiking are fine examples of memetic recombination.

Al's content also illustrates memetic engineering.

In the first three videos Al parodies popular songs. In First World Problems, he hitch-hikes on a well-known internet meme.

"Weird Al" gave a talk at Google recently - where he explains his approach and marketing strategy.

Critics of memetics sometimes claim that we don't have a predictive science of cultural fitness. Some folk may be ignorant about which cultural items spread, but some other people clearly can tell what will spread - and some have based their careers on it. This criticism is bunk.

Monday, 14 July 2014

The 2014 meme explosion

In my 2011: year of the meme article I charted the beginnings of the internet meme explosion.

In 2014, it looks as though it might be happening again. Check out this graph of "memes" seaches:

That's a pretty spectacular 2014 "meme" spike! Looking at the meme news it looks as though it may have something to do with the memes that are hitch-hiking on the world cup. However, memes do seem to be on the rise again - and perhaps it will go on to rival the enormous 2011 meme explosion.

Sunday, 13 July 2014

Tim Tyler: Universal Darwinism

Transcript:

Hi. I'm Tim Tyler and this is a video about Universal Darwinism and the modern evolution revolution.

The term "Universal Darwinism" is the most popular name for the ongoing revolution concerning the expansion of Darwinian evolution's domain. Most scientists understand that Darwin's pioneering work applies to the evolution of animals, plants, fungi and microorganisms. However, in the twentieth century Darwinian evolution has also been applied to other areas including physics, chemistry, computer science and social science.

This expansion of Darwinism's domain of application is one of the most dramatic revolutions evolutionary theory has seen to date.

Not only do DNA-based creatures evolve in a Darwinian manner, but so do economies, lightning strikes, technologies, crystals, religions and propagating cracks. The basic elements of Darwinism - copying with variation and selection - are ubiquitous in nature - even outside evolutionary theory's traditional domain of biology.

Whenever you see a tree-shaped structure in nature, the chances are high that it's either a family tree or a bunch of family trees that have grown together. The same is true for structures that don't look like family trees - until you plot their history over time. For example a landslide doesn't closely resemble a family tree - but if you look at its history over time, almost all the rocks involved have one or more rocks which they inherited velocity from - whose influence caused them to gain speed and participate in the landslide.

The term "Darwinism" itself is somewhat vague. This can be confusing to some - which sometimes leads to controversy over what Darwin actually believed and what set of evolutionary processes deserves to be described as being "Darwinian" - as opposed to, say "Lamarckian". However, such discussions aren't central to the current revolution - the whole idea can be explained using specific core ideas from Darwinism instead - such as selection, adaptation and cumulative adaptive evolution. Science is about the ideas, more than it is about the people who came up with them - but there is a strong tradition of giving credit to originators and Darwin's name is used mainly to give credit where credit is due.

As a brief history, the term "Universal Darwinism" comes from Richard Dawkins in 1983 - who used it to mean something different. The term was given its current meaning by Henry Plotkin in 1984 - and the idea then popularized by Susan Blackmore, Daniel Dennett, David Hull, Geoffrey Hodgson, Gary Cziko and many others. Many of these folk were also pioneers of memetics and cultural evolution.

Another related term which refers to the same phenomenon is "generalized Darwinism". There's also a related concept called "universal selection" - which is best seen as being part of Universal Darwinism.

Universal Darwinism has faced criticism - mainly from social scientists and philosophers, who are uncomfortable with Darwinian expansionism for various reasons. One idea from critics is that unconstrained mutation can explain anything and so predicts nothing. However, Darwinism's traditional way around this is to constrain mutations to those that are naturalistically plausible and don't involve miracles. Another claim is that generalizing the idea of evolution so that it covers all change trivializes the idea of evolution. However, not many enthusiasts for Universal Darwinism actually endorse this idea. Macroscopic reversible systems such as a Newton's cradle have little to do with Darwinism. There are plenty of aspects of physics that aren't explained by conventional Darwinism. The easiest way to avoid this criticism is not to generalize Darwinism to cover all change in the first place. Most of the critics are wrong. In many cases, their motives are obvious - they are trying to defend traditional social science turf from being biologicized. This is generally a futile and counter-productive endeavour.

It is instructive to compare this current revolution with previous ones in evolutionary theory. It is smaller than the one that started in 1859 - but arguably bigger than most we have seen since then. The competitors include the revolutions associated with Mendel, Watson and Crick, and the discovery of the significance of symbiosis. Universal Darwinism seems to represent a more painful paradigm shift than any of the other revolutions that evolutionary theory has seen in the last a hundred and fifty years.

Another issue is how far through the revolution we are. Most energy expended on Darwinian evangelism seems to be devoted to those who don't understand Darwinism at all. In other words, it is devoted to the first wave of Darwinism. Later waves seem to receive relatively little attention. From this perspective, the Darwinian revolution looks as though it is less than half way through. However, hopefully science should go a bit faster when it is running on internet time. Technology improves connectivity, and links humanity together into a massive global brain. This tends towards a situation where once a few humans understand something, their knowledge becomes within easy reach of everyone - over the internet. Plus automation and outsourcing can help to take care of much of the more tedious work. So: probably the rest of the Darwinian revolution will take place in more of a rush than we have seen over the last 150 years. However there is obviously still a long way to go.

Being in the midst of an enormous scientific revolution makes for exciting times for those involved. Because of the lack of scientific manpower that has been devoted to the topic, low-hanging fruit abound - and it is relatively easy for budding scientists to make big discoveries and go down in history. Evolutionary theory has substantial social and political significance - so this is also a area of science where people can make a big difference with relatively little effort. Lastly, this is also an area of science that is being monetized. In particular, empirical discoveries related to applied memetics and memetic engineering are prone to being rapidly turned into cash by marketers and advertisers and progress in memetic algorithms looks set to play an important role in the development of machine intelligence.

These are exciting times for Darwinism. However this evolution revolution is currently not known about by many. If you have made it to the end of this video, you probably know more about this topic than most biologists do. However, the truth will out, and it now seems inevitable that Universal Darwinism will have its day.

Enjoy.

Saturday, 12 July 2014

Memes are not cultural traits

Memeophobe Peter Turchin took some steps towards publicly explaining his opposition to memes recently. What follows is my attempt to untangle Peter's meme muddle:

Peter wrote:

A cultural trait is similar to a meme, a word coined by Richard Dawkins, which is typically explained as “an idea, behavior, or style that spreads from person to person within a culture.” Dawkins proposed that memes are cultural equivalents of genes—self-replicating units of cultural transmission. Cultural traits, however, are a more general category than memes, because they also include quantitative traits that cannot be easily represented as discrete alternatives (for example, an inclination to trust strangers, which I will discuss in tomorrow’s blog).
Here is my reply:

Traits are different from genes, just as cultural traits should be considered to be different from memes. However, practically nobody argues that traits are more general than genes – and then concludes genes aren’t useful. That argument would be nonsensical: genes are heritable information, traits are the results of their expression. Similarly, cultural traits and memes are best treated as different names for different things: memes are the heritable cultural information, and cultural traits are the result of their expression.

A closer synonym for meme within academia is “cultural variant”. However the term “meme” is better, shorter and massively more popular. It won, long, long ago.

Why speak of "memes" rather than just discussing "cultural traits"? Because these are different things! Traits are on the phenotype side, while memes are in the genotype side. Or - using more words - memes are heritable cultural information while cultural traits are their expression in some environmental context.

No one argues against genes on the grounds that traits are more general than genes. Well, apart from Charles Goodnight, maybe. The reason is that doing so would be ridiculous. So: why argue against memes on the grounds that cultural traits are more general than memes?

I think the answer is that because often in science the more general theory is to be preferred - if it is equal in other respects. However, when comparing trait-oriented theories with gene-oriented theories, there can be no pretense of equality in other areas. Traits are the product of developmental processes and environmental interactions. Those are enormous complexities. One of the useful things that was discovered during the gene revolution was all the mileage that it is still possible to get if you strip away all that complexity and just focus on the heritable information - i.e. the genes.

As a brief summary, genes (i.e. heritable traits) are what persists in evolution, while other aspects of the phenotype are lost in each generation, don't persist, have less influence and can often be usefully ignored.

One of the big ideas of memetics, is that we can use the exact same approach in cultural evolution - and get most of the same benefits. That's not to say that ontogeny isn't interesting, or that students of cultural evolution can totally ignore developmental processes - just that memes (i.e. bits of heritable cultural information) are a tremendously useful and helpful abstraction in understanding the cultural evolutionary process.

Just as genes are a tremendously useful and helpful abstraction in understanding the organic evolutionary process.

I think that Peter Turchin is just confused about memes. He hasn't found a sympathetic interpretation of them - and so doesn't know what he is talking about. However, why go on in public about something you don't properly understand? In my experience, one sometimes-legitimate reason is to give others the opportunity to straighten you out. Time will tell if this process helps in Peter's case.

[Note: if anyone reads my quoted comment above and thinks that "cultural variant" and "cultural trait" sound like the same thing, please look up how the term "cultural variant" is used by its proponents in academia. It is actually used by them to refer to heritable information - and not to the corresponding traits.]

Were memes a slap in the face to anthropologists?

Gene Anderson came out with a funny comment about memes recently:

PLEASE PLEASE avoid “memes.” The meme is not only unscientific, but anti-scientific–Dawkins’ slap in the face to the thousands of anthropologists, linguists and psychologists who have worked on these issues for 200 years and come up with very good understandings of how culture is transmitted. Memes not only do not exist, nothing like them exists, and the word is really seriously distracting attention from the actual data and theory on this.

Were memes really a "slap in the face" to anthropologists? I think one has to agree that they were. Let me explain:

In 1976, anthropology had resisted Darwinism successfully for over 100 years. Cultural anthropology had transformed itself from a science into one of the "humanities". Theories were seen as playing the role of: preconceived notions that might bias your perceptions and distort your observations of other cultures. The focus was on recording the data, without preconceptions. Where had this data-driven approach got them? Anthropologists had simply not "come up with very good understandings of how culture is transmitted". They had persistently failed to grasp one of the key organizing principles of their own discipline: namely Darwinian evolution. Basically their theoretical enterprise had failed to find this important organizing principle. At that stage, a slap in the face from a scientist was entirely appropriate medicine. WAKE UP! SMELL THE DARWINISM!

Some might point to Donald Campbell as an anthropologist who understood Darwinism before 1976. That's fair enough - but Campbell was one person, who came along late in the day, and helped started the process of cleaning up the mess left by all the other anthropologists. In no way was he representative of anthropology, or cultural anthropology in that era.

Indeed, to a large extent, this situation persists to this day. Understanding of evolutionary theory among anthropologists - and among social scientists in general - it still awful. Never mind that it's an important part of the theoretical foundation of these topics. These days a few of these folk are busy educating themselves about the topic. However, for goodness sake, don't try to defend the multiple generations of anthropologists who kept their subject mired in pre-Darwinian darkness for so long. Those folk didn't know the extent of their own ignorance - or the damage they were causing.

Yes, Dawkins gave a "slap in the face" to anthropologists. What else are you supposed to do with a bunch of scientists that persistently refuse to understand the basics of Darwinism? Also: the slap wasn't enough of a wake-up call. Most anthropologists persisted in their pre-Darwinian dream for multiple more decades. For example, look at the contributions of anthropologists to Darwinizing Culture. They are simply embarrassing. The pre-Darwinian era in anthropology should be a source of embarrassment and shame to all those involved. Those were stupid, poorly-educated humans. Now we know better. Or at least, we should do.

Update 2014-07-13:

See also this comment from Gene:

Memes and culture traits: There is an absolutely enormous amount of work on this. Nothing remotely like a “meme” exists. Cultural knowledge is not packaged in neat little clumps, does not spread like genes or bugs or viruses from person to person, and does not have a life or identity of its own.

Gene is obviously totally confused about memes. However, I've dutifully added a link to his comment on my meme-denialism page.

Thursday, 10 July 2014

Tim Tyler: Memetic algorithms

Transcript:

Hi. I'm Tim Tyler and this is a video about memetic algorithms.

While social scientists have mostly ignored or misunderstood memetics, the topic has received much warmer welcome from computer scientists. Where social scientists lamented their complex, integrated cultures being atomized into isolated memes, the computer scientists shrugged and went on to use the idea to solve their engineering problems.

Computer scientists had previously employed genetic algorithms as a means of finding solutions to their problems. These involve virtual creatures who are rewarded for producing better solutions to whatever optimization problem their creators are trying to solve. The virtual creatures are iteratively modified using mutation operators, and are maintained in a breeding pool - allowing for recombination to take place.

Cultural evolution appears to have dramatically increased the rate of development of human civilization. If culture evolves faster than DNA does, perhaps we can improve the power of our computer optimization strategies by drawing of some aspects of cultural evolution. This led to the idea of memetic algorithms.

Memetic algorithms are similar to genetic algorithms - but in addition to mutation, recombination and selection, they make use of individual learning, social learning and teaching. Where genetic algorithms were inspired by organic evolution, memetic algorithms draw inspiration from cultural evolution.

Evolution took billions of years to produce creatures sophisticated enough to produce an open-ended type of cultural evolution based on behavioural imitation. This appears to have been because observing the actions of another and then recreating them is not a trivial task. Detailed imitation of behaviour is technically quite a difficult reverse-engineering task, which requires complex cognition to perform.

However, fortunately, we do not have to wait until we have human-level machine intelligence before machines can make use of social learning techniques. We can engineer virtual environments in which even the relatively dumb artificial agents that we can build today can enjoy the benefits of cultural transmission.

Rather than passing on cultural information by a clumsy process based on behavioural imitation, memetic algorithms can work with creatures which have been designed for direct thought transfer. Agents can can record their sense data and replay them for the benefit of other agents. Behaviours can be encoded in a portable format and ported directly between agents. Memories can be directly downloaded from one agent and uploaded into another. Cultural transmission is pretty easy for machines - it doesn't require advanced intelligence.

Memetic algorithms may include a genetic component - and thus may exhibit meme-gene coevolution. Not DNA genes - of course - but rather the same kinds of genes that are used with genetic algorithms. In cases where both memes and genes are involved, there is a tradeoff between the resources expended on each type of evolution.

So far memetic algorithms have become quite a popular technique, with many books and papers on the topic and a string of international conferences dealing with the subject.

Memetic algorithms lie directly on the path which leads towards machine intelligence. Cultural evolution in humans illustrates the process machines will need to master to continue their growth. Machines are masters of mind-to-mind thought transfer, which makes it easy for them to engage in social learning. If you have a partly-intelligent machine, one obvious thing you can do to boost its power is to network it together with other similar machines - and let them cooperate with each other. The dense environment provided inside modern data centers provides an ideal environment for machines to engage in social activity with each other.

Overall, it seems highly likely that memetic algorithms will play a key role in the development of machine intelligence. Memetic algorithms will thus probably prove to be the most important application of memetics - in the long term.

Enjoy,

Sunday, 6 July 2014

Tim Tyler: Eusociality: the symbiont hypothesis

Transcript:

Hi. I'm Tim Tyler, and this is a video about the origin of eusociality - and the role that symbiology might play in that. Most modern ideas about of the origin of eusociality are fairly simple. They invoke kin selection. The ecological advantages of forming large cooperative groups are obvious - and those groups that have managed it dominate the planet - but it isn't easy for evolution to get individual creatures to cooperate in large groups. Kin selection helps to explains how such cooperative groups can be stable. Almost all cases of close group living involve close relatives. The conventional wisdom is that kin selection did it.

Some have invoked group selection as an alternative idea about the origin of eusociality. However, this explanation has turned out to be a dud - in the sense that it doesn't really add anything to the kin selection explanation - because modern forms of group selection and kin selection have turned out to make equivalent predictions.

There are other forces that promote cooperation and group living. Byproduct mutualism is the idea that individuals enjoy straightforward fitness benefits to living in groups - for example, by sharing defense, foraging and lookout duties with others.

This video is about another explanation how eusociality can be stable - one involving symbiosis. The idea is that living in close groups promotes the spread of symbionts between group members. In turn, the symbionts manipulate their hosts into close living arrangements in order to allow the symbionts to reproduce. These two effects create a synergetic spiral that leads towards ultrasociality and eusociality.

This is not a new explanation for eusociality. Indeed it was the most widely accepted explanation for the origin of eusociality in termites before kin selection came on the scene. In this context, it is known as "the symbiont hypothesis". Termites depend on interactions with other colony members to obtain gut bacteria which are essential of their survival. It was thought that this regular need for bacteria from other colony members forced the termites into living a social life.

Multiple symbonts may be involved in creating pro-social forces. Both mutualists and parasites may be present. Each additional symbiont increases the ecological forces that pull the hosts together.

I the symbiont hypothesis is an unfairly neglected explanation for the origin of eusociality. It is interesting to me partly because of its relevance to human culture. There, it suggests that memes manipulate humans into coming into close contact - in order to facilitate their transmission between humans. In turn, humans living in close proximity to each other makes them more vulnerable to horizontal transmission of pathogens and symbionts - including more memes. This leads to a spiral of increased sociality - and to more and more memetic transmission.

Eusocial species are well known for their mutualisms. Termites have their cultivated fungi. Mole rats have their gut bacteria. Bees have their flowering plants while ants have their domatia. The idea of social groups being drawn together by a web of ecological interactions between multiple symbionts makes a lot of sense.

The symbiont explanation differs significantly from the conventional kin selection one. Under kin selection the genes of organisms involved benefit from the cooperation. Under the symbiology explanation, benefit to the host genes is not necessary - the hosts could be being manipulated into engaging in social behaviour - for the benefit of mutualist and parasitic symbionts. You could still classify this as kin selection - kin selection between the symbionts involved and their own offspring, but that's a bit different from the orthodox idea that kin selection between host genes is responsible.

While the conventional kin selection explanation is obviously an important factor, I think that more attention should be given to the symbiont hypothesis of the evolution of eusociality. We need to quantify the effect to see how important it is - relative to kin selection at the level of host genes. The effect seems to be especially clearly applicable to humans - where the cooperating humans involved are often not themselves closely related.

Enjoy,

Tim Tyler: Memetic engineering

Hi. I'm Tim Tyler and this is a video about memetic engineering.

The term "memetic engineering" refers to the deliberative creation of memes using techniques from engineering.

The term is derived from "genetic engineering" - which involves the engineering of genes and genomes.

In the modern world, many memes and memeplexes are engineered - rather than being the product of the deliberate breeding or unconscious selection of memes.

Engineered memes are used in marketing, advertising, entertainment, politics, warfare, religion and education - among other fields.

To give an example, Gangnam Style is a memetically engineered music video. It has over 2 billion views - a testimony to the success of its creators.

Techniques for memetic engineering broadly mirror those used in genetic engineering. Transplanting and recombining existing memes is a common source of new variants. Intelligent design is used to create memes to specifications. Deliberate selection is used to filter the results of these techniques.

With DNA-based creatures, classifying organisms into those that have been engineered and those that have not is a relatively straightforward task. However, with memes, it isn't always easy to distinguish between engineering and selective breeding. The problem is that with DNA, only engineered genes pass through the human mind. By contrast, practically all memes pass through the human mind - and so there is much more scope for changes that might be classified as being engineering to take place.

Like most powerful technologies, memetic engineering is a positive force which also has significant negative potential. Social engineers could use memetic engineering to create a benevolent utopia. However, today, memetically engineered pathogens currently cause a significant quantity of damage. In particular the obesity epidemic, addictive drugs, pornography, movies and computer games represent widespread memetically-engineered plagues.

In some areas, indoctrination targeted at children uses memetically-engineered propaganda to turn kids into soldiers. In other cases, memetic engineering is used to recruit new cult members. Memes can have a dark side - and engineered memes are not excluded from this.

While genetically engineered pathogens are rare and cause relatively little damage, memetically engineered pathogens are common, often largely unregulated, and cause damage in a massive scale. While there are some attempts to restrict more addictive drugs, nicotine, alcohol and caffeine are widely available, many millions are addicted. These are cultural products whose spread is promoted by advertising campaigns which are engineered by large corporations.

Engineered products are sometimes regarded as being inferior to ones that are produced more naturally. This phenomenon does not just involve Luddites: many people often prefer wood to plastic and cotton to polyester. Most of those who would choose ice cream over a banana, recognise that the more natural product is more likely to be better for them.

Broadly in line with this widespread suspicion of artificial products, genetic engineering has acquired a dubious reputation. People campaign against the production and sale of genetically engineered goods. Engineered foods have been dubbed 'frankenfoods' by their detractors. With memetic engineering things are a bit different. In practice, few object to the use of engineered memes simply on the grounds that they are engineered - since so many memes are engineered. However some of the drawbacks associated with engineered products do also apply to memes too.

For example, Esperanto is a memetically engineered language. It was designed - rather than evolving over a long period of time. It has a very regular grammar and has been designed to be easy to learn. However it is widely recognized that Esperanto sucks. Part of the reason is that it didn't evolve over thousands of years - and so is poorly adapted to the human mind. This situation with memetic engineering thus mirrors some of the objections that are associated with genetic engineering.

Despite these kinds of problem, memetic engineering seems to have a bright future. Engineered memes are ubiquitous and dominate the planet. In addition to undirected mutations and selection, they can take advantage of the full toolkit of intelligent design - including interpolation, extrapolation, and evaluation under simulation. As a result they tend to evolve faster and adapt more adeptly.

Despite a three billion year head start, DNA genes are already lagging behind memes in some areas. A more eager embrace of engineering has contributed to the success of memes in the ecosystem. Engineering DNA is challenging - whereas for memes, the human mind is their native environment, and so engineering comes to them more naturally. Unless DNA genes similarly embrace engineering techniques, they risk being rapidly left behind in the dust.

Enjoy,

References

Friday, 4 July 2014

Wanted: human trait inheritance breakdown

Those tracking the inheritance of traits have tended historically to consider what proportion of the variance in a trait is explained by "genetic" factors - with the rest being explained by "the environment" - and chance fluctuations.

The figure differs according to what trait is being investigated, but an average figure of around 50% is often a reasonable guess for the proportion of the variance in a trait is explained by human DNA genes.

The concept of "heritability" is used to describe this.

However, a basic question in cultural evolution is what proportion of the variance in traits is explained by cultural inheritance. Alas, this question seems to have rarely been addressed.

Ideally, we would like a breakdown for a wide range of traits: human DNA genes, DNA genes of parasites and symbionts, cultural transmission, other environmental factors and chance.

Part of the problem is the very idea of "heritability" itself. The concept shoehorns the factors involved in development into 'genes' and 'the environment'. However, in the context of cultural evolution, this dichotomy is basically a naive and unhelpful classification scheme. It's the kind of classification that someone totally ignorant of cultural and environmental inheritance might come up with.

It would be better to split trait variances into inherited and non-inherited components - and then sub-classify the inherited components according to how the inheritance takes place - via host genes, symbiont genes, cultural transmission or environmental inheritance.

It's especially important to know what factors can influence a trait if you want to influence that trait. We do know some things about this topic - but mostly the basic science in this area appears to have been neglected.

One of the reasons why I want to know is because I want to quantify how significant cultural inheritance is - compared to DNA genes and to other forms of environmental inheritance.

Friday, 27 June 2014

Tim Tyler: Darwinian physics

Transcript:

Hi. I'm Tim Tyler and this is a video about Darwinian physics.

In the 1980s there was a movement to incorporate elements from physics into evolutionary theory. It was claimed that not all of the complex-looking patterns of organisms were there in order to benefit the genes of their owners. Instead, some of them were the product of self-organizing systems. Reaction-diffusion patterns were invoked to explain zebra stripes and cheetah spots - challenging the idea that these were adaptations whose purpose was to improve camouflage. Cellular automata were found that reproduced the decorative patterns found on some seashells. The branching tree-like pattern that is found everywhere in biology was likened to dendritic frost patterns, electrical discharges and propagating cracks. The search was on for the new rules that governed these self-organizing systems.

Now, we have found many of these rules. A big and important one has turned out to be: Darwinian evolution via natural selection. So, now the time is ripe for Darwinism to claw back some of the explanatory territory that was lost to complexity theory - and it is time for it to perform some invasions of its own - into realms that have been traditionally occupied by physics and chemistry.

Darwinism is based on processes involving copying with variation and selection. It was once widely thought that copying of the required kind was unique to biological systems - and that before the origin of life copying fidelity was too poor to support any kind of Darwinian evolution - with any copying processes producing instead an error catastrophe and a mutational meltdown. This argument was made by A. G. Cairns-Smith in 1982 - for example. However, this idea has turned out to be dramatically wrong. It turns out that the high-fidelity copying suitable for supporting cumulative adaptive evolution is ubiquitous in simple physical systems.

Lightning strikes are one of the easiest examples of Darwinian physics to visualize. Lightning makes a branching tree. This is a family tree - with regions nearer to the trunk being the ancestors of regions nearer to the tips. If you ask what information is transmitted from parent to child in this case, the answer is that the offspring inherit their parent's position. They inherit this extremely precisely - down to the nearest millimeter.

Position isn't the only thing that is inherited in this way, other attributes - such as velocity and chemical composition - are inherited too, although this inheritance is often less precise.

Examples of Darwinism in simple physical systems are ubiquitous. Most tree-shaped structures are the product of copying with variation and selection. This includes many crystals, fractal drainage basins, propagating cracks and electrical discharges. Re-radiation of photons after hitting dust particles is one of the most common events in the universe and it follows the classical Darwinian algorithm - producing a family tree of photons with the older photons with higher energies being ancestral to their more numerous, but less energetic offspring.

Many other cases do not so obviously exhibit a simple tree. For example, raindrops divide, but they also join creating a network - rather than a classical phylogenetic tree. Of course there are also broadly similar examples of joining in classical evolutionary biology: gametes fuse together, parasites inject DNA into hosts, bacteria assimilate other bacteria and lineages join forces in symbosis. Evolution involves joins and mergers as well as splitting and subdivision.

In other cases, the phylogenetic tree is only visible if you take a historical perspective. For example, every asteroid has an associated ancestral tree of other asteroids, moons, planets and stars that it was formed from. However, you don't see the tree by looking at the asteroid. Only if you look back in time does the family tree become visible.

It's well known that organisms can be modeled as optimizing a fitness function. The same thing applies to lightning - it too is optimizing a function. It acts as a crack in space the seeks out the path of least resistance in its search for the ground. The fact that organic evolution acts as an optimization process is widely exploited by genetic algorithms. There, humans allocate a fitness function and let simulated evolution do their optimization work for them. Optimization features maximands - and these give evolution an apparent teleological character. Biologists can ask what wings are "for" - and then give a reasonable-sounding functional answer. Darwinian physics brings the concept of adaptation to the evolution of inorganic systems - and it becomes reasonable to ask what their features are "for".

Ultimately, both living organisms and lightning strikes can be modeled in the same optimization framework using the same maximand - by treating them both as maximizing entropy.

Entropy maximization is a formulation of optimization processes from within physics which some physicists are already familiar with. Some might ask what the advantages are of taking a Darwinian perspective over one based on entropy maximization. This is a complex question which risks going beyond the scope of this video, but briefly, entropy maximization and Darwinian evolution are largely equivalent ideas which make most of the same predictions - since nature's maximand is closely correlated with entropy production. These are mostly two different ways of looking at the same phenomenon. However, it is possible to select locally for other things apart from entropy maximization - including entropy minimization. Path dependency within a Darwinian framework provides a context which helps to explain these apparent deviations from maximum entropy production.

Lastly, Darwinism neatly explains observation selection effects. While these have long been considered to be part of physics, they are obviously a case of selection acting on observations. We can reformulate the concept of survival of the fittest as observation of the observable. This more general concept acts as a grand unified theory of selection - which neatly covers both Darwinian evolution in biology and observer selection effects in physics and many other areas of science.

Over the last two centuries, Darwinism has had a revolutionary impact on biology, leaving most of the theories that preceded it in the dust. Physics and chemistry are relatively new and unexplored frontiers for Darwinian explanations - but it seems clear that incorporating Darwinism into physics will involve some rewriting of textbooks, and a fair number of psychological paradigm shifts, as scientists gradually awaken to the idea.

Historically, Darwinism has had a hard time penetrating areas that go beyond inheritance of nucleic acids. For example, cultural evolution is still a topic mired in confusion and controversy. However, physicists are supposed to be intelligent people. Hopefully they will prove to be more open to Darwin's ideas than many social scientists have been - and less inclined to treat the Darwin enthusiasts as hostile invaders.

Enjoy,

References