“The Blind Watchmaker” argues that the biological complexity and apparent design in living organisms are not the result of chance or a conscious designer, but of cumulative selection.
This process, driven by natural selection, involves gradual, step-by-step transformations from simpler beginnings. Mutation provides the random variation, but natural selection is the non-random force that directs evolution.
The book also addresses rival theories (Lamarckism, mutationism, etc.) and explains why Darwinism, specifically the modern synthesis, is the most compelling explanation for life’s diversity and complexity.

To help me understand the key concepts in the book, I’ve created two interactive tools: a simulator comparing single-step vs. cumulative selection and a biomorphs generator inspired by Dawkins’ own program. These tools demonstrate how cumulative selection can produce complex designs from simple beginnings and allow you to experience artificial selection by breeding your own digital creatures across multiple generations.

Explaining the Very Improbable

The title is a reference to William Paley’s Natural Theology, which used the analogy of a watchmaker to argue for the existence of God. Dawkins uses this same analogy, but argues against it:

A true watchmaker has foresight: he designs his cogs and springs, and plans their interconnections, with a future purpose in his mind’s eye. Natural selection, the blind, unconscious, automatic process which Darwin discovered, and which we now know is the explanation for the existence and apparently purposeful form of all life, has no purpose in mind… If it can be said to play the role of watchmaker in nature, it is the blind watchmaker.

It seems like complex things have been designed. Some have, but not biological beings (this claim may become wrong in the near future).

A designer (watchmaker here) designs the parts and plans their interconnectedness ahead. But natural selection doesn’t do that. It’s blind - it has no foresight.

A good case can be made that Darwinism is true, not just on this planet but all over the universe wherever life may be found.

This is because good explanations have a reach (The Beginning of Infinity).

The answer we have arrived at is that complicated things have some quality, specifiable in advance, that is highly unlikely to have been acquired by random chance alone. In the case of living things, the quality that is specified in advance is, in some sense, ‘proficiency’; either proficiency in a particular ability such as flying, as an aero-engineer might admire it; or proficiency in something more general, such as the ability to stave off death, or the ability to propagate genes in reproduction.

Complex beings are often proficient in some specific way.
You won’t create this proficiency at random, as it’s very unlikely.

You don’t assemble an airplane by jumbling parts around.

More generally, if living things didn’t work actively to prevent it, they would eventually merge into their surroundings, and cease to exist as autonomous beings. That is what happens when they die.

We, as living beings, want be avoid merging with the environment. Our bodies actively try to mitigate cooling down to environmental temperatures. Or liquids leaving our bodies.

Complex systems can be understood by looking at its parts:

If there is a complex thing that we do not yet understand, we can come to understand it in terms of simpler parts that we do already understand.

When we try to understand something, or explain something, we often start at a rather high level, yet still with parts of the system. Then we can proceed down into subsystems and explain them in terms of their parts. Like, we often start by explaining computers as “it has a central processing unit, main memory…”, and we could go on. Then we could explain each part of a CPU in terms of its architecture.

Dawkins calls this hierarchical reductionism:

The hierarchical reductionist, on the other hand, explains a complex entity at any particular level in the hierarchy of organization, in terms of entities only one level down the hierarchy…

We explain complex things by explaining the levels below.
It’s important to realize that the kinds of explanations at the top level are different from the bottom.

Complex things don’t come into existence by chance.

Good Design

Natural selection is the blind watchmaker, blind because it does not see ahead, does not plan consequences, has no purpose in view. Yet the living results of natural selection overwhelmingly impress us with the appearance of design as if by a master watchmaker, impress us with the illusion of design and planning

It is spelled out here.

A living body or organ appears well-designed if it possesses traits that suggest intentional design for a specific purpose, even if that design isn’t perfect or the best possible:

We may say that a living body or organ is well designed if it has attributes that an intelligent and knowledgeable engineer might have built into it in order to achieve some sensible purpose, such as flying, swimming, seeing, eating, reproducing, or more generally promoting the survival and replication of the organism’s genes.

It is also important to remember:

Even if the foremost authority in the world can’t explain some remarkable biological phenomenon, this doesn’t mean that it is inexplicable. Plenty of mysteries have lasted for centuries and finally yielded to explanation

Personal Incredulity, also known as skill issues, hits hard.
Just because you don’t understand something doesn’t make it wrong. And it doesn’t mean humans (or you!) won’t ever be able to comprehend and understand it.

confusion of natural selection with ‘randomness’. Mutation is random; natural selection is the very opposite of random

Accumulating Small Change

One reason why most find evolution hard to understand is the timescales involved are so long that they can feel incomprehensible in relation to our lifetimes.

It’s easy to understand that change is possible from natural selection. Say, a small change possible in a 100 years. That’s easy to imagine.
Less so for the evolution of complex systems over millions of years.
But our difficulty understanding it doesn’t make it less true.

The core concept of the chapter is cumulative selection. Life evolved gradually, not through sudden leaps of chance. It’s a step-by-step process guided by non-random survival (natural selection):

Each successive change in the gradual evolutionary process was simple enough, relative to its predecessor, to have arisen by chance. But the whole sequence of cumulative steps constitutes anything but a chance process, when you consider the complexity of the final end-product relative to the original starting point. The cumulative process is directed by nonrandom survival.

There are two types of selection:

1. Single-step selection: Entities are sorted once, and that’s it. Like sieving pebbles. This alone can’t explain the complexity of life.
2. Cumulative selection: The results of one selection round become the starting point for the next. It’s like reproduction, with changes accumulating over generations. This is the key to understanding how complex life evolved.

Imagine having to type out a sentence with a random character generator.
If you had to restart every time, it would take.. a very, very long time. This is single-step selection.

But if you could generate a sentence, and have it use mechanisms of cumulative selection, it would be much faster!

The essential difference between single-step selection and cumulative selection is this. In single-step selection the entities selected or sorted, pebbles or whatever they are, are sorted once and for all. In cumulative selection, on the other hand, they ‘reproduce’; or in some other way the results of one sieving process are fed into a subsequent sieving, which is fed into …, and so on.

Dawkins provides a great example with randomly generating the sentence “METHINKS IT IS LIKE A WEASEL”. Doing so with single-step selection (restart every time) would take “a million million million million million years”. However, with cumulative selection, the computer “breeds” from its current best guess, making small changes (“mutations”) and selecting the closest match each time. This drastically reduces the time, down to seconds or minutes.

There is a big difference, then, between cumulative selection (in which each improvement, however slight, is used as a basis for future building), and single-step selection (in which each new ‘try’ is a fresh one). If evolutionary progress had had to rely on single-step selection, it would never have got anywhere

It is also important to realize that:

This belief, that Darwinian evolution is ‘random’, is not merely false. It is the exact opposite of the truth. Chance is a minor ingredient in the Darwinian recipe, but the most important ingredient is cumulative selection which is quintessentially nonrandom.

Darwinian evolution is not random. While mutation is random, the selection process is not.

The “METHINKS IT IS LIKE A WEASEL” model is useful, but it has limitations. Real evolution doesn’t have a long-term goal or “distant ideal target.” Selection is always short-term, focused on survival and reproductive success:

In real life, the criterion for selection is always short-term, either simple survival or, more generally, reproductive success… The ‘watchmaker’ that is cumulative natural selection is blind to the future and has no long-term goal.

In real life, the form of each individual animal is produced by embryonic development. Evolution occurs because, in successive generations, there are slight differences in embryonic development. These differences come about because of changes (mutations — this is the small random element in the process that I spoke of) in the genes controlling development

Evolution occurs because there are random mutations in successive generations

Dawkins goes on to describe a computational model using “biomorphs” – branching tree-like structures generated by a program. He represents “genes” as numbers that influence the drawing rules (angles, lengths, etc.). Evolution is simulated by:

1. Development: Genes translate into a biomorph’s shape.
2. Reproduction: Genes are passed on with small, random changes (mutations).
3. Selection: The user (or, ideally, a simulated environment) selects which biomorphs “survive” and reproduce.

The genes, as we shall see, are more like a recipe than like a blueprint; and a recipe, moreover, that is obeyed not by the developing embryo as a whole, but by each cell or each local cluster of dividing cells.

Each cell acts on its own. There’s no grand blueprint.
Genes, by influencing local events, has influence on the whole.

Recursive branching is also a good metaphor for the embryonic development of plants and animals generally… But all embryos grow by cell division. Cells always split into two daughter cells. And genes always exert their final effects on bodies by means of local influences on cells, and on the two-way branching patterns of cell division

The key is that development and reproduction are separate “modules,” preventing Lamarckism (the inheritance of acquired characteristics):

This is why, in the computer model, it is important that the two procedures called DEVELOPMENT and REPRODUCTION are written as two watertight compartments… DEVELOPMENT most emphatically does not pass gene values back to REPRODUCTION — that would be tantamount to ‘Lamarckism’ (see Chapter 11).

Natural selection doesn’t choose genes directly, but their phenotypic effects (the traits they produce):

In true natural selection, if a body has what it takes to survive, its genes automatically survive because they are inside it. So the genes that survive tend to be, automatically, those genes that confer on bodies the qualities that assist them to survive

Ultimately, it’s death (or failure to reproduce) that acts as the selecting agent:

In nature, the usual selecting agent is direct, stark and simple. It is the grim reaper.

Making Tracks Through Animal Space

Evolution proceeds through small, incremental steps. Each step must be beneficial, or at least not harmful, for it to be selected:

Five per cent vision is better than no vision at all. Five per cent hearing is better than no hearing at all. Five per cent flight efficiency is better than no flight at all… I have no trouble at all in accepting that these statements are true of eyes, ears including bat ears, wings, camouflaged and mimicking insects, snake jaws, stings, cuckoo habits and all the other examples trotted out in anti-evolution propaganda.

Darwin himself said:

If it could be demonstrated that any complex organ existed which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down.

Seems intuitively true. Good reflection by Darwin. Can’t think of any counterexamples we’ve found.

Convergent evolution provides strong evidence for natural selection. Similar traits or features can evolve independently in different lineages, because the same “design principle” is effective:

The basic rationale is that, if a design is good enough to evolve once, the same design principle is good enough to evolve twice, from different starting points, in different parts of the animal kingdom.

The Power and the Archives

Life is fundamentally about information:

What lies at the heart of every living thing is not a fire, not warm breath, not a ‘spark of life’. It is information, words, instructions. If you want a metaphor, don’t think of fires and sparks and breath. Think, instead, of a billion discrete, digital characters carved in tablets of crystal.

Dawkins emphasizes the digital nature of genetic information:

The information technology of the genes is digital.

Genetics works like a digital system where traits are passed down in separate, unblended units, as discovered by Gregor Mendel. This means we inherit specific traits directly from our parents without mixing them. For example, we inherit being male or female without a blend of both. While children might seem to blend traits from their parents, like height or skin color, this is just because they inherit a mix of many separate genetic units. These units themselves do not blend but stay distinct through generations.

DNA and RNA are the “storage medium” of this information. They are polymers, chains of smaller molecules called nucleotides. There are four types of nucleotides (A, T, C, G), creating a four-state system, analogous to the binary (1 and 0) system of computers:

There is very little difference, in principle, between a two-state binary information technology like ours, and a four-state information technology like that of the living cell.

DNA is like ROM (read-only memory). It’s “burned in” and doesn’t change during an individual’s lifetime (except for rare errors). It’s copied during cell division and passed on to offspring:

DNA is ROM. It can be read millions of times over, but only written to once — when it is first assembled at the birth of the cell in which it resides.

The structure of DNA is like computer memory. We all have the same “addresses”, but different “values” (gene variants):

All of us, all human beings, have the same set of DNA addresses, but not necessarily the same contents of those addresses. That is the main reason why we are all different from each other.

In sexually reproducing species, each sperm or egg gets a random half of the parent’s DNA. This creates unique combinations in offspring:

When a sperm, with its 23 chromosomes, is made from a body cell with its 46 chromosomes, it only gets one of the two copies of each addressed location. Which one it gets can be treated as random.

Evolution involves changes in the frequency of different gene variants within a population:

Evolutionary change in a species largely consists of changes in how many copies there are of each of the various possible contents at each addressed DNA location, as the generations pass.

DNA’s information can be copied or used for “action” (like executing program instructions). “Action” involves translating the DNA code into proteins, which then influence the organism’s development and characteristics. This is similar to how computer instructions can produce specific outputs (like a blip sound):

In the same way, patterns in the DNA four-letter code have effects, for instance on eye colour or behaviour, but these effects are not inherent in the DNA data patterns themselves. They have their effects only as a result of the way the rest of the embryo develops, which in turn is influenced by the effects of patterns in other parts of the DNA.

The translation process goes from DNA to RNA to protein (polypeptide). Proteins are chains of amino acids, and there are 20 different types. The sequence of amino acids determines the protein’s unique 3D shape, which in turn determines its function:

There is a sense, therefore, in which the three-dimensional coiled shape of a protein is determined by the one-dimensional sequence of code symbols in the DNA.

This translation uses the “genetic code,” a dictionary where each DNA/RNA triplet codes for a specific amino acid or a “stop reading” signal.

Proteins act as “machines” within cells, carrying out specific chemical reactions. Cells are like “gigantic chemical factories” with millions of these protein machines:

Every living cell, even a single bacterial cell, can be thought of as a gigantic chemical factory… It is the characteristic chemical products of such enzymes that give a cell its individual shape and behaviour.

DNA information is preserved and passed on. Living organisms exist for the benefit of DNA:

Living organisms exist for the benefit of DNA rather than the other way around.

It’s not easy to think this way. We think things revolve around us, our consciousness. But really, it’s our genes that matter - our reproductive systems. All they care about is reproduction. Our lives are just a means to that end. Odd to think about.

The key ingredient for life is self-replication (the ability to make copies). The first replicators were probably simpler than DNA:

The first replicators were probably cruder and simpler than DNA.

Replicators also need:

1. Occasional errors in copying (mutation).
2. The ability to influence their own replication probability (“replicator power”).

There are two other necessary ingredients, which will normally arise automatically from the first ingredient, self-replication itself. There must be occasional errors in the self-copying… And at least some of the replicators should exert power over their own future.

Origins and Miracles

Memes are the new replicators. They spread through culture:

The new replicators are not DNA and they are not clay crystals. They are patterns of information that can thrive only in brains or the artificially manufactured products of brains — books, computers, and so on.

We remix each others ideas.

Constructive Evolution

Natural selection is often seen as a purely negative force, but it can be constructive:

People sometimes think that natural selection is a purely negative force, capable of weeding out freaks and failures, but not capable of building up complexity, beauty and efficiency of design

Mutation adds; natural selection subtracts. Together, over long periods, they build complexity.

Two mechanisms are important here:

1. Coadapted genotypes: A gene’s effect depends on the existing biological context. Genes “cooperate” with other genes within the same species:

First, the idea of ‘coadapted genotypes’. A gene has the particular effect that it does only because there is an existing structure upon which to work.

2. Arms races: Genes in different species can influence each other, leading to escalating improvements in “weapons” and “defenses.”

Duplication within the species isn’t the only means by which the number of cooperating genes has increased in evolution. An even rarer, but still possibly very important occurrence, is the occasional incorporation of a gene from another species, even an extremely remote species.

The Red Queen Effect describes how evolutionary progress in equipment doesn’t necessarily lead to increased success. In an arms race, both sides improve, but their relative success may stay the same:

The principle of zero change in success rate, no matter how great the evolutionary progress in equipment, has been given the memorable name of the ‘Red Queen effect’ by the American biologist Leigh van Valen.

We also have two types of arms races:

1. Symmetrical: Same resources.
2. Asymmetrical: Conflicting

The arms race between cheetahs and gazelles, however, is asymmetric… Cheetahs are trying to eat gazelles. Gazelles are not trying to eat cheetahs, they are trying to avoid being eaten by cheetahs.

Explosions and Spirals

This chapter focuses on positive feedback (self-reinforcing processes) in evolution. Sexual selection is a prime example. Female preferences can drive the evolution of exaggerated traits, even if those traits are detrimental to survival (utilitarian selection):

Darwin, although he laid his main stress on survival and the struggle for existence, recognized that existence and survival were only means to an end. That end was reproduction.

The traits are often linked to genes that increase female preference for those traits, creating a runaway process.

Puncturing Punctuationism

Gradualists traditionally believe in slow, steady change. Punctualists emphasize long periods of stasis punctuated by rapid bursts of change.
The fossil record often shows “gaps,” which seem to support punctuated equilibrium. However, Dawkins argues that these gaps are often due to the incompleteness of the fossil record and the fact that evolutionary change often occurs in small, isolated populations:

From Darwin onwards evolutionists have realized that, if we arrange all our available fossils in chronological order, they do not form a smooth sequence of scarcely perceptible change… Darwin, and most others following him, have assumed that this is mainly because the fossil record is imperfect.

The “gaps” may also reflect migrational events, where a new species appears suddenly in a particular area, having evolved elsewhere:

The reason the ‘transition’ from ancestral species to descendant species appears to be abrupt and jerky is simply that, when we look at a series of fossils from any one place, we are probably not looking at an evolutionary event at all: we are looking at a migrational event, the arrival of a new species from another geographical area.

Dawkins clarifies that punctuated equilibrium is not the same as saltationism (evolution through large, sudden mutations). Saltationism is generally rejected because large mutations are usually harmful:

Macromutations — mutations of large effect — undoubtedly occur. What is at issue is not whether they occur but whether they play a role in evolution

Dawkins argues that punctuated equilibrium is compatible with mainstream neo-Darwinism. It’s simply a consequence of how speciation (the formation of new species) often occurs in geographically isolated populations:

The ‘gaps’, far from being annoying imperfections or awkward embarrassments, turn out to be exactly what we should positively expect, if we take seriously our orthodox neo-Darwinian theory of speciation.

The currently accepted theory of evolution is neo-Darwinism, or the Modern Synthesis. This theory combines Darwin’s ideas with genetics and other fields. It emphasizes gradual change through natural selection, but can accommodate faster rates of change under certain conditions. It addresses and incorporates earlier theories like Mendelian genetics, and expands upon them with new ideas.

Dawkins stresses that gradualism is essential to Darwin’s theory, because it explains how complex adaptations can arise without miracles:

In Darwin’s view, the whole point of the theory of evolution by natural selection was that it provided a non-miraculous account of the existence of complex adaptations.

The One True Tree of Life

The universality of the genetic code is strong evidence for common ancestry:

The genetic code is universal. I regard this as near-conclusive proof that all organisms are descended from a single common ancestor.

Doomed Rivals

Dawkins argues that Darwinism is the only known theory capable of explaining certain aspects of life, particularly adaptive complexity. He examines rival theories:

• Lamarckism: The inheritance of acquired characteristics. Dawkins refutes this on multiple grounds: it’s not supported by evidence, it’s incompatible with epigenetic development, and it can’t explain complex adaptations:

Our refutation of Lamarckism, then, is a bit devastating.

• Mutationism: The idea that evolution is driven primarily by the direction of mutations, not selection. Dawkins argues that while mutation is not entirely random in all respects, it’s random in the crucial sense that it’s not biased towards improvement:

There is randomness and randomness, and many people confuse different meanings of the word. There are, in truth, many respects in which mutation is not random. All I would insist on is that these respects do not include anything equivalent to anticipation of what would make life better for the animal.

• Neutralism: Claims that variation is not directed towards improvement and that evolution comes from selection.
• Creationism

The core argument is that cumulative selection, with its gradual, step-by-step process guided by non-random survival, is the only way to “tame chance” and explain the improbable complexity of life:

The essence of life is statistical improbability on a colossal scale. Whatever is the explanation for life, therefore, it cannot be chance… Cumulative selection, by slow and gradual degrees, is the explanation, the only workable explanation that has ever been proposed, for the existence of life’s complex design.

To ‘tame’ chance means to break down the very improbable into less improbable small components arranged in series.