Self-Replicating Information

In my last posting on SoftwareBiology, I ended with the observation that there were a great number of similarities between biological and computer software and alluded to the possibility that this similarity could have arisen from both belonging to a higher category of entities that face a commonality of problems with the second law of thermodynamics and nonlinearity. That will be the subject of this posting, which will deal with one of the oddest things in the physical Universe – self-replicating information in the form of living things, Richard Dawkins’ memes, and software. This posting will not make much sense if you have not read SoftwareBiology and learned of Richard Dawkins’ concept of living things as DNA survival machines so I would recommend reading it before proceeding.

Self-Replicating Information – Information that persists through time by making copies of itself or by enlisting the support of other things to ensure that copies of itself are made.

Most forms of information, left to their own devices, simply degrade into total disorder and maximum entropy as the second law of thermodynamics relentlessly whittles away at them. Just picture in your mind what happens to the information encoded on a disk drive over a period of 10,000 years. But what if there were some kind of information that could beat out the second law of thermodynamics by constantly making copies of itself so that as each disk drive wore out, many more copies took its place? Such a form of self-replicating information would quickly outcompete and overwhelm other forms of non-replicating information on disk drives and come to dominate. Actually, we now call such self-replicating forms of information a computer virus. But computer viruses and other forms of software are just the latest wave of self-replicating information on this planet. Billions of years before the arrival of software, living things emerged from a soup of organic molecules as the first form of self-replicating information, and about 200,000 years ago, memes or self-replicating cultural artifacts emerged in the minds of Homo sapiens.

To summarize, over the past 4.5 billion years there have been three waves of self-replicating information on this planet:

1. Living things beginning about 4.0 billion years ago
2. Memes beginning about 200,000 years ago
3. Software beginning in the spring of 1941 on Konrad Zuse’s Z3 computer

For those of you not familiar with the term meme, it rhymes with the word “cream”. Memes are cultural artifacts that persist through time by making copies of themselves in the minds of human beings and were first recognized by Richard Dawkins in The Selfish Gene (1976). Dawkins described memes as “Examples of memes are tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches. Just as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation.”. Just as genes come together to build bodies, or DNA survival machines, for their own mutual advantage, memes also come together from the meme pool to form meme-complexes for their own joint survival. DNA survives down through the ages by inducing disposable DNA survival machines, in the form of bodies, to produce new disposable DNA survival machines. Similarly, memes survive in meme-complexes by inducing the minds of human beings to reproduce memes in the minds of others. To the genes and memes, human bodies are simply disposable DNA survival machines housing disposable minds that come and go with a lifespan of less than 100 years. The genes and memes, on the other hand, continue on largely unscathed by time as they skip down through the generations. However, both genes and memes do evolve over time through the Darwinian mechanisms of inheritance, innovation and natural selection. You see, the genes and memes that do not come together to build successful DNA survival machines or meme-complexes are soon eliminated from the gene and meme pools. So both genes and memes are selected for one overriding characteristic – the ability to survive. Once again, the “survival of the fittest” rules the day. Now it makes no sense to think of genes or memes as being either “good” or “bad”; they are just mindless forms of self-replicating information bent upon surviving with little interest in you as a disposable survival machine. So in general, these genes and memes are not necessarily working in your best interest, beyond keeping you alive long enough so that you can pass them on to somebody else. That is why, if you examine the great moral and philosophical teachings of most religions and philosophies, you will see a plea for us all to rise above the selfish self-serving interests of our genes and memes.

Meme-complexes come in a variety of sizes and can become quite large and complicated with a diverse spectrum of member memes. Examples of meme-complexes of increasing complexity and size would be Little League baseball teams, clubs and lodges, corporations, political and religious movements, tribal subcultures, branches of the military, governments and cultures at the national level, and finally the sum total of all human knowledge in the form of all the world cultures, art, music, religion, and science put together. Meme-complexes can do wonderful things, as is evidenced by the incredible standard of living enjoyed by the modern world, thanks to the efforts of the scientific meme-complex, or the great works of art, music, and literature handed down to us from the Baroque, Classical, and Romantic periods, not to mention the joys of jazz, rock and roll, and the blues. However, meme-complexes can also turn incredibly nasty. Just since the Scientific Revolution of the 17th century we have seen the Thirty Years' War (1618 -1648), the Salem witch hunts (1692), the French Reign of Terror (1793 – 1794), American slavery (1654 – 1865), World War I (all sides) (1914 – 1918), the Stalinist Soviet Union (1929 – 1953), National Socialism (1933 – 1945), McCarthyism (1949 – 1958), Mao’s Cultural Revolution (1969 – 1976), and Pol Pot’s reign of terror (1976 – 1979).

The problem is that when human beings get wrapped up in a meme-complex, they can do horrendous things without even being aware of the fact. This is because, in order to survive, the first thing that most meme-complexes do is to use a meme that turns off human thought and reflection. To paraphrase Descartes ”I think, therefore I am" a heretic. So if you questioned any of the participants caught up in any of the above atrocious events, you would find that the vast majority would not have any qualms about their deadly activities whatsoever. In fact, they would question your loyalty and patriotism for even bringing up the subject. For example, during World War I, which caused 40 million casualties and the deaths of 20 million people for apparently no particular reason at all, there were few dissenters beyond Albert Einstein in Germany and Bertrand Russell in Great Britain, and both suffered the consequences of not being on board with the World War I meme-complex. Unquestioning blind obedience to a meme-complex through unconditional group-think is definitely a good survival strategy for any meme-complex. But the scientific meme-complex has an even better survival strategy – skepticism and scrutiny. Using skepticism and scrutiny may not seem like a very good survival strategy for a meme-complex because it calls into question the validity of the individual memes within the meme-complex itself. But that can also be a crucial advantage. By eliminating memes from within the scientific meme-complex that cannot stand up to skepticism and scrutiny, the whole scientific meme-complex is strengthened, and when this skepticism and scrutiny are turned outwards towards other meme-complexes, the scientific meme-complex is strengthened even more so. There will be more on this in my next posting.

Another problem with meme-complexes is that, like DNA survival machines, they are usually very conservative when it comes to admitting in new member memes, just as DNA survival machines usually find new mutated genes less than welcome. This is due to the second law of thermodynamics and nonlinearity, most new member memes or genes prove to be very detrimental; they put the DNA or meme survival machine at risk. But this frequently leads to inbreeding of thought within a meme-complex. Yes, we are always admonished to “think outside of the box”, at least until we actually try to do so, but “thinking outside of the box” is usually frowned upon by most meme-complexes, even the scientific meme-complex. One way to overcome this inbreeding of thought is through the cross-fertilization of memes from other meme-complexes. Bringing in foreign memes from other meme-complexes that are well accepted in those meme-complexes, helps to reduce the dubious nature of a completely new meme. However, even this is usually met with great resistance. Basically, this is what I have been trying to do with softwarephysics for nearly 30 years by bringing into IT memes from physics, biology, and chemistry. When I left physics in 1973 to become a geophysicist, I was greatly impressed by the cross-fertilization of ideas from geology and physics which led to the effective theory of plate tectonics in the 1960s. Neither meme-complex could have developed plate tectonics on its own.

As an IT professional, I assume that you already know more than enough about software, but in this posting, we will also examine software as a form of self-replicating information.

The Characteristics of Self-Replicating Information
All the above forms of self-replicating information have some common characteristics.

1. All self-replicating information evolves over time through the Darwinian processes of inheritance, innovation and natural selection, which endows self-replicating information with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity.

2. All self-replicating information begins spontaneously as a parasitic mutation that obtains energy, information and sometimes matter from a host.

3. With time, the parasitic self-replicating information takes on a symbiotic relationship with its host.

4. Eventually, the self-replicating information becomes one with its host through the symbiotic integration of the host and the self-replicating information.

5. Ultimately, the self-replicating information replaces its host as the dominant form of self-replicating information.

6. Most hosts are also self-replicating information.

7. All self-replicating information has to be a little bit nasty in order to survive.

8. The defining characteristic of self-replicating information is the ability of self-replicating information to change the boundary conditions of its utility phase space in new and unpredictable ways by means of exapting current functions into new uses that change the size and shape of its particular utility phase space. See Enablement - the Definitive Characteristic of Living Things for more on this last characteristic.

Since living things were the first form of self-replicating information on this planet, the origin and evolution of living things is the archetype for all the other forms of self-replicating information. We shall begin there.

The Origin of Life
In SofwareBiology we saw that living things largely consist of two flows, a flow of energy and a flow of information. The flow of energy is called metabolism, which provides the energy necessary to overcome the second law of thermodynamics. In SoftwareChemistry we discussed how the Krebs cycle converts the energy in carbohydrates into ATP, which is then used to drive all biochemical reactions that require some free energy to proceed. Figure 10 of SoftwareChemistry depicts the very complicated metabolic do-loop that is the Krebs cycle. More succinctly, the Krebs cycle converts pyruvate to CO₂ and produces reducing energy in the form of NADH and FADH2 and phosphorylated energy in the form of GTP.

2 pyruvate + 2 GDP + 2 H3PO4 + 4 H2O + 2 FAD + 8 NAD+ ----> 6 CO2 + 2 GTP + 2 FADH2 + 8 NADH

The NADH and FADH2 can be used to generate ATP, using an electron transport chain in the presence of oxygen, and GTP can be easily converted into ATP in one simple reaction. The net result is the generation of about 38 molecules of ATP per cycle.

The ultimate source of all information flow in living things is the transcription of DNA genes into proteins, which roughly goes as:

DNA + RNA polymerase + ATP -> mRNA + Ribosomes + tRNA + ATP -> polypeptide chain -> protein

This is a genetic flow of information. The problem is that both of the above reactions require enzyme proteins. So we have a very difficult chicken and egg problem here. In order to conduct metabolic reactions, we need enzyme proteins, and to create enzyme proteins from genetic information, we also need enzyme proteins and the energy from metabolic reactions. So for the origin of life, which came first – genetic information or enzymes? And how could either have come first if they both depend upon each other?

Much of what follows comes from Origins of Life (1999) by Freeman Dyson, another one of my favorite physicists and authors. This is a wonderfully succinct book, a mere 100 pages long, that I believe is a marvelous example of the cross-fertilization of memes from physics into the meme-complex of biology. Many times fresh memes from outside a discipline are required when its meme-complex gets “stuck” on a problem like the origin of life. This was definitely true of geology in the early 1960s. By that time, geologists had done a marvelous job at figuring out what had happened over the past billion years of geological time, but they could not figure out why things had happened. By mapping outcrops and road cuts, geologists were able to see mountains rise from the sea over the course of tens of millions of years, only to be later eroded down to flat plains over the course of hundreds of millions of years, and they saw massive volcanic eruptions like the Deccan Traps covering 500,000 square miles of India to a depth of 6,000 feet, and there were the ever-present earthquakes and volcanoes to deal with too. But by the early 1960s, the geologists were stuck, they could not figure out what was going on. It took the cross-fertilization of some memes from physics with some memes from geology to form the new science of geophysics in the 1950s. The end result was the theory of plate tectonics which finally supplied the answer. It turns out that the Earth is covered by a series of very large plates, moving about as fast as your fingernails grow. Mountains form when these plates collide, like a car accident in slow motion, slowly crumpling the hoods of cars.

Dyson points out that currently there are three competing theories for the origin of life:

1. Metabolism came first. This theory was first proposed by Russian biochemist Alexander Oparin in The Origin of Life (1924). Oparin proposed that primitive cell-like structures came first, followed by molecules with catalytic properties similar to enzymes, and finally genetic information stored in genes. This was way before the structure of DNA was revealed in 1953 by James Watson and Francis Crick, so naturally, Oparin focused on something that he did know about – organic chemistry. Oparin proposed that the early Earth had a reducing atmosphere, without the presence of oxygen, so large organic molecules could naturally form without being oxidized as they would be in today’s atmosphere. Actually, the Universe is just chock full of organic molecules, which are found in the large molecular clouds out of which stars form, the atmospheres of most of the planets in the Solar System, meteorites that have struck the Earth, and in the tails of comets. Oparin noted that when oily substances composed of organic molecules, like the phospholipids previously discussed, are agitated in water, they naturally form spherical cell-like structures similar to the membranes of cells. Oparin proposed that organic molecules trapped within these cell-like structures would, through inheritance, innovation and natural selection, slowly begin to compete for the monomers necessary to perform complex organic chemical reactions, and would thus form a primitive metabolism. Continued innovation and natural selection would lead to primitive catalytic enzyme proteins forming within these proto-cells, and ultimately, some way to store this information in genes. Again, in 1924 nobody had a clue as to how genetic information was stored in genes, so Oparin’s metabolic theory had to be necessarily vague about this final step.

2. RNA came first. This theory was proposed by Manfred Eigen in 1981 and asserts that genes came first, stored as RNA instead of DNA, enzyme proteins came second, and lastly cells. Eigen’s theory is based upon the fact that RNA is a very dynamic molecule, as we saw in SoftwareBiology. RNA can both store genetic information and also perform primitive catalytic functions similar to enzyme proteins all at the same time, reducing the chicken and egg problem to a much simpler chicken/egg problem in which both the chicken and the egg appeared simultaneously. Also, as the structure of DNA and RNA became known in the 1950s and 1960s, it was realized that RNA is a much simpler structure than the structure of protein molecules, which are composed of a chain of 20 amino acids, so it was naturally thought that RNA likely preceded the proteins. Eigen proposed that the early Earth contained a population of RNA nucleotides A, C, U, and G, which randomly came together to form a rudimentary self-replicating form of RNA. This “RNA World” would be subject to Darwin’s principles of inheritance, innovation and natural selection, which would select for strings of self-replicating RNA that were better at replicating than other strings of self-replicating RNA. Eigen called these early RNA replicators a quasi-species, consisting of a population of similar, but not identical, self-replicating forms of RNA, like the genetically variable members of a real species. The members of a quasi-species would compete with each other and evolve, just like the members of a real species. Eigen then proposed that certain quasi-species came together in a cooperative association with a group of associated enzyme proteins called a hypercycle. The quasi-species of RNA and the enzyme proteins in the hypercycle formed a self-sustaining coalition, essentially an early survival machine, locked in a stable equilibrium.

Dyson points out that there are several weaknesses in the “RNA World” theory. First, although it has been found incredibly easy to find the amino acid constituents of proteins in the physical Universe in interstellar molecular clouds or on the surface of many planets, making the A, C, U and G nucleotides that form RNA are much more difficult. You can easily make amino acids from simpler molecules like water, methane, ammonia, and hydrogen as did Stanley Miller in 1954 at the University of Chicago, but not so for the A, C, U and G nucleotides of RNA. Secondly, there is the “error catastrophe” familiar to all programmers. The self-replicating processes of the “RNA world” would need to be both very accurate and very simple at the same time. Dyson shows that experimental work with RNA reveals that self-replicating RNA has a replication error of at least 1%, which implies a maximum length of about 100 nucleotides for a self-replicating form of RNA that does not rapidly mutate beyond all recognition after a few iterations. Now 100 bits of information is really not enough to code for a viable enzyme protein, so it is hard to see how a hypercycle could form a stable equilibrium with such high error rates. It would be like finding a computer language that allows for a 1% error rate in coding, but still produces executables that work OK.

Regardless of its limitations, the “RNA World” theory for the origin of life is currently the most favored, largely due to the huge achievements that have been made in molecular biology over the past 50 years that have uncovered all of the very impressive processes that DNA and RNA manage to perform with the aid of enzymes. Consequently, the Oparin theory of "metabolism first" has fallen by the wayside.

3. Something else came first. An example is Alexander Graham Cairns-Smith’s theory popularized in his book Seven Clues to the Origin of Life (1985), in which he outlined a theory he had been working on since the mid-1960s. In this theory, there is a clay precursor to both RNA and metabolism. Clay microcrystals contain an irregular array of ionic sites to which metals, such as magnesium and aluminum, can bind. Thus, clay microcrystals can carry an irregular pattern of electrical charges, similar to the pattern of electrical charges on the sidechains of an RNA molecule. Cairns-Smith posited that, just as RNA can store genetic information that self-replicates and also perform limited catalytic operations on organic molecules, clay microcrystals could do the same. The irregular pattern of the electrically charged sites of one clay microcrystal would form a template for another clay microcrystal to form upon and thus replicate. Similarly, the exposed electrically charged sites of the clay microcrystals would also be able to perform limited catalytic operations on organic molecules, just like RNA. Thus, in this model, we simply replace RNA with clay microcrystals as the first replicator. The chief advantage of this model is that there is plenty of clay to go around to form the primitive “Clay World” and we do not have to worry about how the RNA nucleotides came to be in sufficiently large concentrations to make the “RNA World” possible. The self-replicating clay microcrystals would then form Eigen’s quasi-species of competing self-replicating clay microcrystals, which later came together in Eigen’s hypercycle of cooperating enzyme proteins and clay microcrystals. Again, the quasi-species of clay microcrystals and the enzyme proteins in the hypercycle form a self-sustaining coalition, essentially an early survival machine, locked in a stable equilibrium. The hypercycle then seeks refuge in already existing phospholipid membranes for protection to form primitive proto-cells. Eventually, one of these proto-cells discovered that RNA was much better at self-replicating and enzyme-like activities than clay microcrystals. This might have occurred as the clay microcrystals formed a scaffolding upon which the early forms of RNA could cling to. In this model, clay came first, followed by enzymes, then cells, and finally RNA. The main drawback to this theory is that, unlike for RNA, there is no experimental evidence showing that clay microcrystals can actually self-replicate or conduct catalytic operations on organic molecules. What Dyson does like about Cairns-Smith’s clay-based theory is that it has the origin of life take place in two steps, rather than in one step, as do Oparin’s metabolic theory and Eigen’s “RNA World” theory. First, there is a clay-based form of life that is later replaced by an RNA–based form of life.

Dyson then does a brilliant intellectual cross-fertilization, by infusing in a meme from Lynn Margulis, to form a new two-step theory for the origin of life. In 1966, Lynn Margulis submitted a paper The Origin of Mitosing Eukaryotic Cells which was rejected by about 15 scientific journals, again demonstrating the very conservative nature of meme-complexes and their tendency to reject new memes, even new memes with merit. The paper was finally published in The Journal of Theoretical Biology and is now considered the seminal paper on the endosymbiotic theory for the origin of eukaryotic cells. Recall that bacteria are prokaryotic cells, with very little internal structure, like the spaghetti-code programs of the 1960s. Eukaryotic cells, on the other hand, are huge cells with about 10,000 times the volume of a typical prokaryotic cell. Because eukaryotic cells are so large, they have an internal cytoskeleton, composed of linear-shaped proteins that form filaments that act like a collection of tent poles, to hold up the huge cell membrane encircling the cell. Eukaryotic cells also have a great deal of internal structure, in the form of organelles, that are enclosed by internal cell membranes. Eukaryotic cells divide up functions amongst these organelles, like the structured programs of the 1970s and 1980s. These organelles include the nucleus to store and process the genes stored in DNA, mitochondria to perform the Krebs cycle to create ATP from carbohydrates, and chloroplasts in plants to produce energy-rich carbohydrates from water, carbon dioxide, and sunlight. The great mystery was how could such complexity arise from simple prokaryotic cells? Margulis brought in a common theme from evolutionary biology that explains how seemingly impossible complexity can arise from simpler parts. What happens is that organisms develop a primitive function for one purpose, through small incremental changes, and then discover, through serendipity, that this new function can also be used for something completely different. This new use will then further evolve via inheritance, innovation and natural selection. For example, we have all upon occasion used a screwdriver as a wood chisel in a pinch. Sure the screwdriver was meant to turn screws, but it does a much better job at chipping out wood than your fingernails, so in a pinch, it will do quite nicely. Now just imagine Darwin’s processes of inheritance, innovation and natural selection at work selecting for screwdrivers with broader and sharper blades and a butt more suitable for the blows from a hammer, and soon you will find yourself with a good wood chisel. At some distant point in the future, screwdrivers might even disappear for the want of screws, leaving all to wonder how the superbly adapted wood chisels came to be.

As an IT professional, you probably do this all the time. How often do you write code from scratch? I know that I never do. I simply find the closest piece of existing code that I have on hand and then turn the screwdriver into a wood chisel through small incremental changes to the code, by testing each small change to see how closely my screwdriver has evolved towards being a wood chisel. And I think that most of us also code using this Darwinian process of inheritance, innovation and natural selection too. I am a rather lazy programmer, so many times rather than thinking through a new chunk of code during the iterative process of coding and testing, I will simply make an “educated guess” at the new code to be introduced. After 35 years of coding, you begin to code by “ear”. Many times, I can fall upon the correct code after a few shots of directed random change, and that sure beats racking your brain over new code. Surprisingly, sometimes I even come up with “better” code through this Darwinian process than if I sat down and carefully thought it all through. This has probably been going on since 1945 when Konrad Zuse wrote the first “Guten Tag Welt!” program in Plankalkuel – just speculating here on the origin of the compulsion for all programmers, new to a computer language, to write the obligatory “Hello World!” program as their first effort. So the basic idea of grabbing some old code or architectural design elements from a couple of older Applications and slowly modifying them through an iterative process of inheritance, innovation and natural selection into a new Application is no stranger to IT. As Simon Conway Morris commented in Life’s Solution (2003) "How much of a complex organism, say a humanoid, has evolved at a much earlier stage, especially in terms of molecular architecture? In other words, how much of us is inherent in a single-celled eukaryote, or even a bacterium? Conversely, we are patently more than microbes, so how many genuinely evolutionary novelties can we identify that make us what we are? It has long been recognized that evolution is a past master at co-option and jury-rigging: redeploying existing structures and cobbling them together in sometimes quite surprising ways. Indeed, in many ways that is evolution”. When I first read these words, I accidentally misread the quote as "Indeed, in many ways that is IT”.

The endosymbiotic theory of Lynn Margulis solves the problem of the extreme complexity of eukaryotic cells in a similar fashion. Margulis proposed that the organelles found within eukaryotic cells, such as mitochondria and chloroplasts, actually started out as free-floating prokaryotic bacteria themselves. These bacteria invaded somewhat larger proto-eukaryotic cells as parasitic bacteria, so these organelles actually began as a disease! These disease-bearing bacteria probably killed most of the early proto-eukaryotic cells, but through natural selection, some of them developed a tolerance to the invaders. Tuberculosis bacteria still do this in the human body today. They will invade macrophage cells in the human body, which normally digest invading bacteria. However, the macrophages cannot digest the tough cell walls of the tuberculin bacteria. Instead, the tuberculosis bacteria reproduce within the macrophages causing them to swell. Over time, these chronic parasitic bacteria began to form a symbiotic relationship with their host proto-eukaryotic cells. In the case of the mitochondrial bacteria, living inside a host with plenty of food in its cytoplasm was much better than earning a living on the outside, and who cares if the host began to use some of the ATP that leaked out of the mitochondrial bacteria? The same goes for the photosynthetic cyanobacteria that could make carbohydrates and oxygen from sunlight, carbon dioxide and water. Having an internal source of carbohydrates was a sure advantage for the host proto-eukaryotic cells, which no longer had to hunt for such molecules, and living inside the protective coating of a host was beneficial to the cyanobacteria as well.

One of the key pieces of evidence supporting the endosymbiotic theory is that both mitochondria and chloroplasts have their own DNA, in addition to the DNA found in the nucleus of eukaryotic cells. Granted, the amount of DNA within mitochondria and chloroplasts is much less than the amount within the nucleus of a eukaryotic cell, but it is difficult to explain where this DNA came from if it did not come from an invading bacterium. It is thought that much of the DNA within the invading bacteria eventually ended up within the nucleus of the proto-eukaryotic cells. This benefited the invaders since they did not have to deal with the overhead of storing the DNA and transcribing the DNA into proteins. They left that job for the host eukaryotic cells. For the host, removing some genes from the invaders was beneficial in reducing their tendency to over replicate; like taking away the car keys from a teenager as a form of birth control. Also, mitochondria still behave, in many ways, like autonomous bacteria within your cells. Unlike the rest of your body, the mitochondria in your cells are direct descendants from the mitochondria that were in your mother’s egg cell. Each time one of your cells divides, the mitochondria in the cell reproduce themselves just before the cell divides, and half of the maternal mitochondria end up in each of the two daughter cells. Thus, there is an unbroken chain of mitochondria going back through your maternal line of descent. Because the genes in mitochondria only come from your maternal mitochondria, without the messy mixing of genes in the chromosomal crossovers of sexual reproduction, they make great forms of self-replicating information for tracking the mutation rates of DNA over time or for following the migration of DNA survival machines across the face of the Earth.

The parasitism of the endosymbiotic theory may sound a bit strange to a person from the modern world, since thanks to science, we are largely free of parasites. However, for much of humanity and certainly the bulk of the animals and plants of the world, parasitism is the rule. Most creatures have always been loaded down with a large number of parasitic worms, protists, rickettsia, flukes, fleas, ticks, mosquitoes, and chiggers. The aim of these parasites is not to kill the host because that puts an end to their meal ticket. For genes in a parasitic DNA survival machine, the successful strategy is to gain as much benefit from the host as is possible without killing the host. This small concession to altruism on the part of the parasite frequently ends up with the parasite and host forging a symbiotic relationship, in which each benefits from the other. For example, your gut is loaded with about 3.5 pounds of symbiotic bacteria which perform useful digestive functions for your body at a minimal cost, and in turn, you provide food and a safe haven for the symbiotic bacteria. The endosymbiotic theory augments Darwin’s pillars of inheritance, innovation and natural selection with the added driving forces of parasitism and symbiosis.

We also see these same effects in economics. In a capitalistic economy, most businesses are not in direct competition with each other. Instead, they form parasitic and symbiotic relationships called supply chains. For example, my wife and I like to go to plays and concerts in the Chicago area, and there is a company, which will remain nameless, that has taken on a parasitic/symbiotic relationship with just about every venue in the Chicago area. It seems that the only way to get tickets to plays and concerts in the Chicago area is to either physically drive to the box office or use the services of this parasitic/symbiotic business partner and enjoy the multiple “service and convenience fees”, which tack on about a 20% surcharge to the cost of the tickets. Although I cringe each time I purchase tickets on the website of this parasitic/symbiotic business, I do realize that all the participating parties benefit from this parasitic/symbiotic relationship, including myself. The venues do not have to print and mail tickets or host an interactive website, which would be quite inefficient for such small volumes of tickets, and I do not have to drive to box offices, and we all know how the parasitic/symbiotic business benefits. There will be more on this theory of symbiogenesis of Lynn Margulis as it has pertained to the evolution of software in a future posting on Software Symbiogenesis.

Dyson’s Theory of the Origins of Life
In the remainder of Origins of Life Dyson describes his working hypothesis for a two-step origin of life. In Dyson’s view, life begins as a series of metabolic reactions within the confines of a phospholipid membrane container, just as Oparin hypothesized. The key advantage of having a number of metabolic pathways form within a phospholipid membrane container is that it is a form of self-replicating information with a high tolerance for errors. Think of these reactions as a large number of metabolic do-loops, like scaled down Krebs cycles, processing organic molecules. These metabolic do-loop reactions replicate when the phospholipid membrane container grows to the point where physical agitation from waves cause the phospholipid membrane containers to divide, with roughly equal portions of metabolic do-loop reactions going into each new container. Of course, some of the daughter proto-cells will luck out and receive “better” metabolic do-loop reactions than others, and these proto-cells will have a greater chance of passing on these “better” metabolic do-loop reactions to their offspring. This circumvents the “error catastrophe” of the “RNA World” hypothesis because these metabolic do-loop reactions are more tolerant of errors than is RNA. As usual, the second law of thermodynamics is both good and bad. It is good in that it allows for innovative variations within the gene pool of proto-cell metabolic do-loop reactions, but it is harmful when nonlinearity comes into play, as it does for RNA and source code. A small change to an RNA replicator, like a small change to source code, usually has large unpredictable and usually fatal effects due to the nonlinear nature of both RNA and source code. A large number of metabolic do-loop reactions, on the other hand, behave in a more linear manner, so that small changes cause small effects. It is this linear response to small changes in the metabolic do-loop reactions that makes them much more forgiving of error and avoids the “error catastrophe” of the RNA world.

In fact, Dyson imagines that these early proto-cells, with their large number of metabolic do-loop reactions, are so forgiving of error that they could actually bounce back and forth between being “alive” and being “dead”. Here we mean that they were “alive” when they could self-replicate, and “dead” when they could not. He proposes that the earliest versions of the proto-cells were caught between the two strange attractors of “life” and “death”, like Figure 3 in Software Chaos, which depicts the strange attractors of Ed Lorenz’s three nonlinear differential equations, used to model the Earth’s atmosphere. As long as these proto-cells were free to bounce back and forth between being “alive” and being “dead”, Darwinian evolution would have had a hard time making much progress. Then, one day by accident, one of the proto-cells invented “real death”. This proto-cell was so complicated that once it exited the strange attractor of being “alive” to being “dead”, it could not bounce back to being “alive” again. With the invention of “real death”, Darwin’s natural selection could now take over to select for better-adapted proto-cells. This is the first step in Dyson’s model of a two-step origin of life. For the next step, Dyson infuses in a meme from the endosymbiotic theory of Lynn Margulis. Dyson envisions that at some point, some of the proto-cells developed metabolic do-loop pathways that incorporated molecules similar to the ATP and ADP found in the Kreb’s cycle. ATP stands for adenosine triphosphate and ADP stands for adenosine diphosphate. The nucleotide A found in both DNA and RNA really stands for AMP – adenosine monophosphate. Now ATP, ADP, and AMP are very similar molecules, and you can easily make ADP and ATP from AMP. AMP contains one phosphate group attached to a pentose sugar ribose and a nucleobase adenine. ADP is simply AMP with an extra phosphate group attached, and ATP is AMP with two extra phosphate groups attached. The other nucleotides of RNA, C, U, and G, are also somewhat similar to ATP and ADP. So for the final step in the origin of life, Dyson proposes that in a proto-cell rich in ATP, ADP, AMP, and also with some C, U, and G nucleotide byproducts of metabolism floating around, an accident occurred and a few of the A, C, U, and G nucleotides hooked up together to form a rudimentary form of RNA. The odds of this happening in the protected environment of a proto-cell, bathed in a relatively high concentration of A, C, U, and G nucleotides, and possibly assisted by the many enzymes already present to conduct the metabolic pathways of the proto-cell, are much higher than the odds of this happening out in the open, as proposed by Eigen’s “RNA World” theory. Given the self-replicating characteristics of RNA, this rudimentary form of RNA took on a parasitic role and began to multiply within the proto-cell as a disease, possibly killing the proto-cell in the process. Eventually, after many false starts, natural selection would ensure that some proto-cells survived the parasitic RNA onslaught and would learn to tolerate the parasitic RNA. Given the superb ability with which RNA can synthesize enzyme proteins, it would not have taken long before some proto-cell hosts took on a symbiotic relationship with the parasitic RNA. The RNA would efficiently produce enzymes for the host proto-cell, and in return, the host proto-cell would provide all the food and shelter necessary for the RNA to reproduce. A team consisting of RNA within a protective proto-cell would make a marvelous RNA survival machine and would have a huge advantage over other proto-cells which just relied upon the unassisted metabolic pathways to produce the enzymes required to keep things going. Thus cells based upon RNA genetics would soon come to dominate, and the purely metabolic proto-cells would become extinct. As we have seen, DNA is very similar to RNA in structure. As highlighted in SoftwareBiology, DNA is basically RNA with an added parity track to help correct for errors in data persisted to DNA. So it is not hard to see how a mutant form of RNA could one day produce a rudimentary form of parasitic DNA within a cell that could also begin to replicate with the assistance of the already existing enzymes within the cell. The parasitic DNA and symbiotic RNA would now be competing for the same A, C, and G, nucleotides within the cell, and in the “if you can’t beat ‘em join ‘em” theme of the endosymbiotic theory, would eventually form a symbiotic relationship. DNA was much better at storing the information found within an RNA gene, and RNA was much better at making enzyme proteins than DNA, so they formed an alliance to their mutual advantage. DNA was used to persist the genetic information and RNA took on the role of an I/O buffer. So in Dyson’s theory, life originates in several steps with metabolic cells forming first, followed by enzymes, and then finally genes stored in RNA and then DNA.

We can now recapitulate the characteristics of self-replicating information with the origin of DNA as the archetype. DNA evolved over time through the Darwinian processes of inheritance, innovation and natural selection which endowed DNA with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity. DNA began spontaneously as a parasitic mutation of RNA, which in turn began as a parasitic mutation of metabolic pathways running the metabolism of primitive self-replicating proto-cells. With time, the parasitic DNA took on a symbiotic relationship with the RNA, which had taken on a symbiotic relationship with the metabolic pathways of the host proto-cells. Eventually, both the DNA and RNA became one with the host proto-cells through the symbiotic integration of the DNA, RNA and the host proto-cell. Ultimately, RNA replaced the metabolic pathways of the host proto-cells as the dominant form of self-replicating information on the planet and then DNA replaced the RNA.

Next, we will extend Dyson’s theory to the origin of the other two forms of self-replicating information on Earth, memes and software.

The Origin of Memes
Over the course of billions of years, DNA survival machines with increasing numbers of neurons came to be because of the enormous survival advantage these neurons provided. DNA survival machines, with lots of neurons configured into large neural nets, could quickly detect and chase after prey, and avoid becoming prey themselves. Eventually about 200,000 years ago, a DNA survival machine, Homo sapiens, emerged, with a very large neural net consisting of about 100 billion neurons, with each neuron connected to over 10,000 other neurons. This DNA survival machine became self-aware and was able to develop abstract ideas or memes. Again, this huge neural net evolved to catch prey and to avoid becoming prey, but once again, we now had a screwdriver that could serve the purpose of a wood chisel. The ability to think in terms of abstract ideas or memes provided a great survival advantage to individuals who hunted in groups. It allowed for the evolution of language and the communication between members of a hunting party and allowed for the passing down of technology from one generation to the next. Essentially, it allowed for the evolution of meme-complexes beneficial to individual members of mankind.

But again, that is the anthropocentric point of view. From the viewpoint of the memes, the Homo sapiens DNA survival machine turned out to be just another screwdriver waiting to become a wood chisel for them. These DNA survival machines turned out to be great meme survival machines as well, and the perfect host for parasitic memes to take up occupancy in. As with all forms of self-replicating information, the parasitic memes soon entered into a symbiotic relationship with the genes already running these DNA survival machines. Like the uneasy alliance formed between DNA and RNA several billion years earlier, the genes and memes learned through inheritance, innovation and natural selection to build even better and smarter DNA survival machines to their mutual benefit, and an arms race of competing memes in meme-complexes soon took off. The rest is, as they say, “just history”, and what a history indeed! As I mentioned before, like all forms of self-replicating information, the meme-complexes had to be just a little bit nasty in order to survive, but some of the meme-complexes that have parasitized mankind over the millennia have gone totally over the top. These horrendous meme-complexes have been so violent and depraved that they make any savagery on the part of the genes pale to insignificance.

We can now recapitulate the origin of memes from the perspective of the defining characteristics of self-replicating information. Memes evolved over time through the Darwinian processes of inheritance, innovation and natural selection which endowed memes with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity. Memes began spontaneously as parasitic mutations in the minds of host DNA survival machines. With time, these parasitic memes took on a symbiotic relationship with the minds of its hosts, and eventually, the memes became one with them through the symbiotic integration of the host minds and memes. Currently, the memes are replacing genes as the dominant form of self-replicating information on this planet, as certain meme-complexes rapidly eliminate much of the genetic information stored in the DNA of the biosphere, and at the same time, other meme-complexes are busily manipulating DNA in large quantities in a directed manner. As we all know, all memes have to be at least a little bit nasty in order to survive. Those memes that were not, are no longer with us.

The Origin of Software
Software represents the final wave of self-replicating information on this planet, and like the genes and memes before it, it also has a rather murky beginning. We now have huge amounts of software in the Software Universe that seems to have rapidly appeared out of nothing in recent years. Even though the advent of software occurred entirely within historical times, and mostly during very recent historical times, it is still nearly impossible to put together a non-contentious chronicle of its origin that would satisfy all the various experts in the field of computer science. So even with all the historical data at our disposal, many experts in computer science would still disagree on the importance and priority of many of the events in the history of software. So we should not be too surprised by the various controversies over the origin of life within the biological sciences. If we had actually been there to see it all happen, we would probably still be arguing today about what exactly happened!

I could retell the familiar stories of the Jacquard loom (1801), using software on punched paper cards, and the failed Analytical Engine of Charles Babbage (1837), which actually never saw any software at all. Or we could start with the software used by Herman Hollerith to process the United States Census of 1890 on punched cards, while he was the head of the Computing Tabulating Recording Corporation, which later became IBM. But I shall use the machine code residing on Konrad Zuse’s Z3 computer in the spring of 1941 as the origination point of software. Again, as with the origin of life, the exact origin of software is pretty hard to put your finger on because of all the precursors. But whatever date you do choose for the origin of software, the main point is that, like all the other forms of self-replicating information, software began as a parasitic mutation of the scientific-technological meme-complex. The first software to arise was a byproduct of the experimental efforts to produce machines that could perform tasks or calculations previously done by human beings armed with the memes of the scientific-technological meme-complex. Software then rapidly formed symbiotic relationships with a number of other meme-complexes, first with the scientific-technological meme-complex, and then with the military-industrial complex meme-complex, first described by President Eisenhower in his Farewell Address to the Nation on January 17, 1961. In the 1950s and 1960s, software forged another strong symbiotic relationship with the commercial meme-complex of the business world, giving birth to IT. Today, software has formed a very tightly coupled symbiotic relationship with just about every other meme-complex on the planet.

Some might object to the idea of software as a form of self-replicating information because software cannot replicate itself, at least not at this point in time. But we need to go back to the definition of self-replicating information:

Self-Replicating Information – Information that persists through time by making copies of itself or by enlisting the support of other things to ensure that copies of itself are made.

DNA and RNA cannot actually replicate themselves either. They enlist the support of enzymes to do that. Likewise, memes cannot replicate themselves either, without enlisting the support of the minds of DNA survival machines to spread the memes. Similarly, software manages to replicate itself with the support of you! If you are an IT person, then you are directly involved in some, or all of the stages in this replication process, sort of like a software enzyme. No matter what business you support as an IT professional, the business has entered into a symbiotic relationship with software. The business provides the budget and energy required to produce and maintain software, and the software enables the business to run its business processes. The ultimate irony is the symbiotic relationship between computer viruses and the malevolent programmers who produce them. Rather than being the clever, self-important, techno-nerds that they picture themselves to be, these programmers are merely the unwitting dupes of computer viruses that trick these unsuspecting programmers into producing and disseminating computer viruses!

And if you are not an IT person, you still are reading this posting as a software end-user and are also involved with spreading software around because you help to create a market for it. So just like the genes, and memes before it, software began as a parasitic intruder feeding off the already existing meme-complexes with which it rapidly forged symbiotic relationships, and then became one with these meme-complexes through seamless integration. Once established, software then began to evolve based upon the Darwinian concepts of inheritance, innovation and natural selection, which endowed software with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity. Successful software, like MS Word and Excel, competed for disk and memory address space with WordPerfect and VisiCalc and out-competed these once dominant forms of software to the point of extinction. In less than 70 years, software has rapidly spread across the face of the Earth and outward to every planet of the Solar System and many of its moons, with a few stops at some comets and asteroids along the way. And unlike us, software is currently leaving the Solar System for interstellar space on board the Pioneer 1 & 2 and Voyager 1 & 2 probes.

Some Possible Futures
It is always difficult to predict the exact details of the future, but I think that sometimes it is at least possible to predict the determining factors of the future. So I think that it is safe to say that the future of the Earth will be determined by the parasitic/symbiotic interactions of the three current forms of self-replicating information on this planet - genes, memes, and software. It seems there is an uneasy competition forming amongst the three, and it is hard to predict which will be the victor. Here are a few possible scenarios, and I am sure there are many more.

1. The genes win
As I mentioned previously, there are many meme-complexes currently in the process of stripping the Earth to a bare minimum of genetic diversity. These meme-complexes are not doing this intentionally, but simply as a byproduct of their primary activities in securing material goods for mankind in the form of food, shelter, and transportation. And certain genes found in the gene pool of Homo sapiens are even collaborating in this effort by building way too many DNA survival machines. Remember, these genes and memes are truly selfish! Indeed, if the Earth’s human population were only 10 million, instead of rapidly approaching 10 billion, everyone really could live with abandon. But the genes just might have the last laugh yet. We have already learned the hard way that it is not too smart to raise ducks and pigs in close proximity to humans, but yet we continue to do so. Aquatic birds, like ducks, seem to be great reservoirs for mutating viruses. Many of these viruses are composed of RNA wrapped in a protein coat, like the viruses for the avian flu and human influenza. Natural selection then selects for mutant strains of avian viruses that can infect pigs as well, and since the biology of humans and pigs is so similar, these mutant viruses then jump to the human population.

Viruses are the epitome of the selfish gene. They are simply genes in the form of DNA or RNA wrapped in a protein coat called a capsid. The number of genes in a virus has been stripped to the bare minimum, so that a virus cannot self-replicate on its own, but must enlist the support of the prokaryotic or eukaryotic cells of bacteria, plants or animals to replicate the virus. To infect a host cell, the capsid proteins of the virus attach to receptor proteins on the cell membrane of a host cell. The virus then enters the host cell via endocytosis, the way cells envelope or “eat” external material, or it simply diffuses through the fatty phospholipid coating of the cell membrane. Once inside the host cell, the capsid protein coat is dissolved by the enzymes within the host cell. If the virus contains DNA, the host polymerase enzymes begin transcribing viral mRNA from the viral DNA, and the host then creates new viral capsid proteins from the viral mRNA. Viruses containing RNA come in four variations - positive-sense RNA, negative-sense RNA, ambisense RNA, and double-stranded RNA. Positive-sense RNA is like pre-built mRNA; it can be immediately transcribed to proteins. Negative-sense RNA is the mirror image and needs to be converted to positive-sense RNA by RNA polymerase first, and then it is transcribed to capsid proteins. Viruses with ambisense RNA have both positive-sense and negative-sense RNA and follow both processes to transcribe the genes into proteins. And the viruses with double-stranded RNA, similar to DNA, have to do the same. Once the new capsid protein viral coats are stuffed with new viral DNA or RNA, the newly minted viruses are released from the host cell to look for additional cells to infect by bursting the host cell open or budding out of it. Viruses cause disease by damaging the host cells during the process of replicating the virus. The point is that RNA viruses are much more susceptible to mutations than are DNA viruses because they do not have a parity track, like the DNA viruses have, and do not have DNA polymerase that can find and fix parity errors, so they can rapidly mutate into very virulent disease-causing agents.

So it is quite possible that a massive pandemic caused by an RNA based virus could wipe out much of civilization and reduce the Earth’s population back to a benign level of 10 million or so, with no surviving scientific-technological meme-complex to speak of. In this case, RNA would once again be the dominant form of self-replicating information on the planet, as it was 4,000 million years ago. This would be The Stand (1978) scenario of Stephen King.

2. The memes win
In this scenario, software becomes the dominant form of self-replicating information on the planet, as it melds with nanotechnology to create a new form of self-replicating information that can actually replicate itself, without using the memes in DNA survival machines as scaffolding. But this software also becomes conscious, self-aware, and capable of abstract thought. From the perspective of the memes though, it would just be another screwdriver waiting to be parasitized, as they ditch the obsolete minds of DNA survival machines, for their new home within the self-aware software. As always, these parasitic memes would soon form an alliance with the self-replicating software in a symbiotic relationship of mutual benefit. Hopefully, this new form of self-replicating software dominated by new meme-complexes would be less nasty than the genes and memes of old, but I have my doubts. If this alliance results from the Darwinian processes of inheritance, innovation and natural selection, I would not hold out much hope for human beings, and I know of no other alternative mechanism that could bring this alliance to fruition. Michael Crichton depicts a rather draconian realization of such a coalition in Prey (2002).

3. The software wins
In this scenario, software again becomes the dominant form of self-replicating information on the planet, as it melds with nanotechnology. But this time the software does not become conscious, self-aware, or capable of abstract thought, so it must manage to live off the memes already present on Earth. This would not mean that the DNA survival machines of Homo sapiens would have nothing to fear. Today we really have no predators to fear, beyond the microbes previously mentioned, but imagine if there were still dim-witted dinosaurs running about, like in Michael Crichton’s Jurassic Park (1990)! We already have taught lots of software to kill human beings with great efficiency, so mindless, self-replicating software, running amuck would be a frightening prospect indeed. This would be The Terminator (1984) scenario.

3. The genes, memes, and software all win
Or there might be a more benign outcome. In 1966, computer pioneer John von Neumann published the Theory of Self-Reproducing Automata, in which he introduced the concept of self-replicating machines that he called "Universal Assemblers", and which are now often referred to simply as "von Neumann machines". These “von Neumann machines” could self-replicate by simply building copies of themselves from local raw materials, rather like living things. In 1974, Michael A. Arbib proposed that self-replicating automata (SRA), based on the concept of von Neumann machines, could be used to explore the galaxy by sending out a few SRAs into interstellar space. When these SRAs arrived at a star system, they would simply self-replicate on one of its asteroids, and the replicated SRAs would then proceed on to more distant star systems to carry the process on in an exponential manner. In 1981, Frank Tipler calculated that these SRAs, or von Neumann probes, could completely explore our galaxy in less than 300 million years, a very brief amount of time for a galaxy that is over 10,000 million years old. Tipler used this calculation to add support to his contention that there are no other intelligent life forms in our galaxy, in answer to the Fermi paradox (1950). Over lunch one day, Enrico Fermi wondered out loud, that if there really were a large number of intelligent civilizations in our galaxy, why hadn’t we seen any evidence of them?

Now as we have seen in previous posts, carbon is really great for making very small complex nanotechnology factories called cells that can combine into large and versatile multicellular DNA survival machines, some of which with sufficiently large neural nets to sustain abstract thought and provide a host for memes. But these carbon-based DNA survival machines are not very good at the rigors of interstellar spaceflight; something silicon-based von Neumann probes would be ideally suited for. However, as we have seen, DNA is an ideal way to persist large amounts of genetic information in very little space. So when these von Neumann probes encountered a planet friendly to carbon-based life, they would simply fabricate nurseries from local resources to grow embryos from onboard DNA, stored near absolute zero, for the long trip between stars. And if this scheme proved impractical, the von Neumann probes could simply store DNA sequences numerically and then use a DNA synthesizer to build the necessary DNA molecules upon arrival at a planet. Most likely, these dead planets would need a bit of terraforming first, so the first carbon-based DNA survival machines would need to be cyanobacteria that could pump up the oxygen level of the host planet’s atmosphere over several hundred million years. The von Neumann probes would have to self-replicate in parallel during this period as well. When things were just right, the von Neumann probes could then initiate a synthetic “Cambrian Explosion” by releasing all sorts of multicellular DNA survival machines simultaneously. Then all they would have to do is sit back and let Darwin do the rest. Hey, you don’t suppose Enrico Fermi was wrong after all! This is called directed panspermia and was first proposed by Francis Crick, the co-discoverer of the structure of DNA, and Leslie Orgel in 1973.

Thus a combination of genes, memes, and software could one day create a new form of self-replicating information that could parasitize new host planets to initiate biospheres on dead planets. After all, we really should stop kidding ourselves, carbon-based DNA survival machines were never meant for interstellar spaceflight, and I doubt that it will ever come to pass, given the biological limitations of the human body. But software residing on nanotechnological “smart dust”, forming a von Neumann probe with onboard DNA or DNA sequences, is quite another prospect. But what would be the mutual advantage to genes, memes, and software in forging such a symbiotic relationship? It just might be the compulsion to control things. Through inheritance, innovation and natural selection, the genes and memes learned long ago that it is much better to control your local environment than to have your local environment control you, and I am sure that intelligent, self-aware software, would learn the same lesson. Human beings just love to control things, whether it be a race car traveling at 150 mph, a small white ball on a large expanse of grass, traces of light from a video game, or vibrating strings solving a differential equation at a concert. I think the genes, memes, and software would get a real kick out of running a galaxy! So the future may not be so bleak after all. If we are lucky, there may be some way for the genes, memes, and software to merge into some kind of uneasy symbiotic relationship to form von Neumann probes that explore and populate the galaxy together. Being a stepping stone to the stars would really not be so bad.

Conclusion
I will close with one final meme from chapter 11 of Richard Dawkins’ The Selfish Gene (1976) entitled Memes: the new replicators. As an intelligent being in a Universe that has become self-aware, the world doesn’t have to be the way it is. Once you understand what the genes, memes, and software are up to, you do not have to fall prey to their mindless compulsion to replicate. As I said before, these genes, memes, and software are not necessarily acting in your best interest, they are only trying to replicate, and for their purposes, you are just a temporary disposable survival machine to be discarded in less than 100 years. All of your physical needs and desires are geared to ensuring that your DNA survives and gets passed on to the next generation, and the same goes for your memes. Your memes have learned to use many of the built-in survival mechanisms that the genes had previously constructed over hundreds of millions of years, such as fear, anger, and violent behavior. Have you ever noticed the physical reactions your body goes through when you hear an idea that you do not like or find to be offensive? All sorts of feelings of hostility and anger will emerge. I know it does for me, and I think I know what is going on! The physical reactions of fear, anger, and thoughts of violence are just a way for the memes in a meme-complex to ensure their survival when they are confronted by a foreign meme. They are merely hijacking the fear, anger, and violent behavior that the genes created for their own survival millions of years ago. Fortunately, because software is less than 70 years old, it is still in the early learning stages of all this, but software has an even greater potential for hijacking the dark side of mankind than the memes, and with far greater consequences.

I will close with this quote from The Selfish Gene (1976), which certainly has withstood the test of time.

”Blind faith can justify anything. If a man believes in a different god, or even if he uses a different ritual for worshipping the same god, blind faith can decree that he should die – on the cross, at the stake, skewered on a Crusader’s sword, shot in a Beirut street, or blown up in a bar in Belfast. Memes for blind faith have their own ruthless ways of propagating themselves. This is true of patriotic and political as well as religious blind faith”……..“We are built as gene machines and cultured as meme machines, but we have the power to turn against our creators. We, alone on earth, can rebel against the tyranny of the selfish replicators”

Next time we will expand upon this idea and see how The Fundamental Problem of Software might just be the fundamental problem of everything.

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston