'Bounce Back - How to Fail Fast and be Resilient at Work' is written by Business Psychologist Dr Susan Kahn, this book shows you how to embrace failure. Failing fast, failing well, and learning how to be agile and resilient at work is a vital part of being a successful and innovative leader. This book is packed with practical exercises, case studies and it shows you how to invest in your resilience in a deliberate way, and empower you to face risk head-on. From learning how to respond well to critical feedback, to understanding cultural attitudes to failure around the world, this book attempts to help you, to be stronger and resilient.



Key Learnings

Success paradoxically means embracing failure. Falling short is a great way of learning, and it builds resilience over time. Add psychological clarity, physical wellbeing, stoic philosophy and a clear sense of purpose into the equation to be set for success. 

Refrain negative situations
We often look at the world in black and white terms: some things are clearly 'good' while others are simply 'bad'. 'Turning the Obstacle Upside Down' is a good exercise in helping you notice this. The idea is to reframe difficult situations as a sources of insight and development. 


If you want to succeed, you should accept that you’re going to fail time and again.

Whatever the industry, professionals and organisations benefit when they learn from their failures. This is because, contrary to conventional wisdom, failure doesn’t make you less intelligent or able. In fact, the most accomplished and talented individuals and institutions routinely experience failure. They recognise that, as the psychologist Denis Waitley puts it, failure isn’t an “undertaker” – it’s a teacher.

Take it from basketball star Michael Jordan, one of the most successful players in the history of the sport. Looking back, Jordan sees his career as a series of failures. He missed over 9,000 shots, 26 of which were potential game-winners. He failed time and again. “That,” he said, “is why I succeed.” Then there’s JK Rowling, one of the world’s most respected authors. Before Harry Potter became the global sensation it is today, her books were rejected by dozens of publishing houses. Or take Netflix. The on-demand video streaming service was first pitched to Blockbuster in 2000 for a fraction of its current value. Blockbuster turned it down. 

These kinds of failures provide a valuable lesson on the importance of self-belief and determination. Just think of Thomas Edison, the inventor of the lightbulb. He famously regarded each failure as a step in the right direction. With all these failed attempts he had found 10,000 ways that wouldn’t work. But even though failure is so important, not everyone will respond to it in an encouraging and supportive way. Some stakeholders, like bosses or clients, will inevitably be upset. So it’s very important to develop a system that encourages risks and failures, but which also avoids a breakdown in relations. Call it fail fast.


“Fail fast” can teach both individuals and organisations to make the most of failure.

The concept of fail fast comes from systems design. There, it denotes a technology that immediately reports issues likely to cause serious problems further down the line. When this happens, operations are halted so that the flaw in the process can be addressed. The idea was later taken up by businesses to describe the way they stress-test products early on. This gets failure out of the way, and it can prevent years of wasted investment. This is something we can also implement in our own day-to-day work.

There’s only one surefire way to avoid failure: don’t try anything new – ever. But playing it safe is a recipe for stagnation. We thrive when we feel challenged and excited by what we’re doing. Conversely, we stop producing our best work when we get caught in a familiar routine. So why do so many of us fall into the trap of familiarity? Well, once we’ve developed our expertise and become highly competent by mastering challenges, we suddenly become risk-averse. Being an expert feels good, and we’re reluctant to leave that hard-won comfort zone. After all, when we embrace a new challenge, we have to accept that we’re not experts in this new area. This in turn reintroduces the scariest prospect of all – failure. 

This is where fail fast comes in. The idea is pretty simple: the sooner we try something new, the lower the stakes will be if we fail. This makes it easier to get the dreaded experiment out of the way and gain valuable new insights. It also means we’re less likely to fail the next time around. Implementing fail fast systems is increasingly important in today’s world. As Sunnie Giles argues in The New Science of Radical Innovation, the twenty-first century work environment is characterised by four factors: volatility, uncertainty, complexity, and ambiguity – or VUCA for short. In this climate, failure is certain. The organisations best placed to thrive don’t just tolerate this reality; they embrace it. In practice, this means that leaders encourage experimentation and set moderate challenges. These challenges encourage creative solutions while keeping the stakes tolerably low. But there is more to workplace resilience than failing fast. We also have to understand ourselves better. 



Your unconscious shapes your behaviour, and exploring your inner motivations can help you become more resilient.

It’s easy to assume that what we’re able to see is all there is to see. At work, for example, we might notice a manager ignoring a colleague’s contributions and inwardly condemn this disrespectful behaviour. What we can’t see, though, are the unconscious drivers of this behaviour. Maybe this manager is envious of the person proposing ideas. Or maybe he thinks that it’s his duty as a manager to have all the good ideas. Ultimately, it’s these unseen factors that explain how we act. 

Like icebergs, the greater part of who we are is below the surface. It is the hidden part of ourselves – the unconscious – that determines who we are. This idea goes back to the work of Sigmund Freud. According to Freud, our unconscious is a kind of repository of repressed childhood memories. And it shapes the way we behave. Let’s say we felt unsafe, envious, neglected, or abandoned in our early years. These feelings are likely to play an important role in how we view and act in the world as adults. Unconscious thoughts influence us in two ways. The first is called transference. Here, our response to individuals and events is shaped by past experiences. Say you find yourself blushing when the chair speaks to you at a board meeting. There’s a good chance that’s because his tone unconsciously reminded you of being humiliated by your teacher as a child.

Then there’s projection – attributing your own thoughts and feelings to someone else. This often happens when you feel those thoughts and feelings are wrong. You might feel hateful toward a colleague. This is an unacceptable thought, so you might make it palatable by deciding that they hate you. Essentially, you’ve projected your hatred onto the other person.

The best way to keep these kinds of unconscious thought patterns in check is to explore your inner motivations. Knowing who you are and why you respond to people and events in the way that you do will allow you to interact more productively and avoid unnecessary conflicts. This in turn will help you become more resilient. To do this, get into the habit of reflecting on workplace encounters that left you feeling wounded. Jot down everything that hurt you, and see if you can face the painful memory it brought back. Making unconscious thoughts conscious is the best way to break out of unhelpful behavioural patterns.


Sleep is the key to building physical resilience.

There are thousands of scientific reports demonstrating the health benefits of getting a good night’s sleep. Unfortunately, this is something fewer and fewer of us are doing. The World Health Organisation reports that a sleep-loss epidemic is sweeping through industrialised nations. This is a cognitive and emotional time bomb. Inadequate sleep wreaks havoc on our ability to concentrate, carry out complex tasks, and acquire new information.

Sleep loss also takes its toll on our resilience. Without the sustenance of sleep, we are both mentally and emotionally weaker. This makes us grumpy, irritable, and much likelier to lash out. Think of an infant crying its heart out. Their mother or father might explain that “they’re just tired.” As adults, we’re socially aware enough not to throw a tantrum in public. But we’re just as impacted by our lack of sleep as a bawling toddler.

World-renowned neuroscientist Matthew Walker’s 2017 book, Why We Sleep, talks about adopting a few simple tricks to getting enough sleep. If you’re getting less than seven hours of sleep a night, Walker argues, it’s time to start avoiding stimulants like caffeine and nicotine. These can take up to eight hours to work through your body, and they seriously undermine your ability to nod off. Alcohol should also be avoided. While a nightcap might make you feel relaxed, it robs you of deep sleep – the most restorative and restful part of the sleep cycle. This is also true of heavy meals eaten too close to bedtime. And remember, humans are creatures of habit, so it’s a good idea to go to bed at the same time every day. 


Resilience isn’t just about positivity – it’s also helpful to think about everything that could go wrong.

If you want to build your resilience, many argue, you need to embrace the power of positive thinking. This is a popular idea found in self-help books, therapies, and on social media. It says that if we’re positive enough, there’s nothing we can’t do, from losing weight to landing that dream job. There’s nothing wrong with a can-do attitude, of course – the reason these books and ideas are popular is because they do help lots of folks. But positive thinking isn’t the only approach. 

Sometimes, dwelling on negatives can be just as helpful. Granted, mulling over all the reasons you might fail doesn’t sound like a compelling strategy to build resilience. But here’s the thing: confronting the likelihood of falling short can be liberating.

This notion is at the heart of Stoicism, a philosophical creed that goes back to the ancient Greeks. This doctrine has two key components.

The first is death. Stoics, as followers of this school of thought are called, emphasise the briefness of life. This might sound depressing, but they believe this focus actually relieves us of a burden. They reason that once you concentrate your mind on the certainty of dying, it becomes easier to embrace life and not put off until tomorrow what you can do today. This also applies metaphorically. Think of what “death” might mean in your work. What is the worst possible outcome? The loss of employment, your reputation, clients, or money? If you knew that these things would eventually happen, how would that affect your choices today?

Then there’s the lesson of the influential Greek philosopher Epictetus, born in 341 BCE. As Epictetus saw it, few things cause more misery than change and disruption. This is because we fear the unknown and assume the worst.  So Epictetus argued that it’s best to only consider the changes that you’re presented with. If thinking through the worst possible outcomes is not really helping you plan for them but just making you anxious, change tack. Stop stressing about possibilities, gossip, or what could happen. Prepare for change once it becomes a reality. 

Together, these lessons strike a balance – anticipate the worst and plan for it, but really focus only on what’s actually happening, not on “what ifs.”


Purpose makes us resilient and gets us through periods of hardship. 

When we’re clear about why we’re doing what we’re doing, we are much more likely to be resilient. It is this sense of “why” that gets people through grueling seven-day weeks in the early stages of establishing their business, or keeps them on course during a marathon. In other words, the conviction that our tasks are meaningful gives us the courage to push through adversity.


Only you can define what kind of work is meaningful.

The Japanese have a special word for the sense of purpose that gets you out of bed in the morning: ikigai, meaning “a reason for being.” This is something you do not just for money but also because it matters. As the saying goes, “If you do something you love, you’ll never have to work another day in your life.” This is true enough, but first you have to find your purpose.

Committing to a working life of purpose takes courage. Doing what matters to you, after all, is deeply personal. It might lead you down a path that will surprise your family, friends, and peers. This can cause friction, but it’s worth doing all the same. We only get one chance at life. Doing what you care about is an opportunity that shouldn’t be passed up lightly. The question, then, is how to find out what a working life of meaning and purpose would look like for you. To help you do that, there are a couple exercises to try.

Your ikigai encompasses both your personal values and your professional abilities. To find work that allows you to combine these two things, you’ll need to ask yourself four questions.

  • First off, what do you love doing? 
  • Secondly, what are you good at? 
  • Thirdly, what does the world need? 
  • Lastly, what can you be paid for? 

Think of your answers as a Venn diagram; you’ll find your ikigai where all four circles overlap. 

You can also try a more creative approach. Imagine you are a manager at a firm that’s hiring, and you walk through the door. Try to describe yourself. What does your contribution to the company entail? Why does it matter? What are the top three points about your work that you’d emphasise? If this is still too vague, try condensing this description of why your work is important even further, into a 140-character tweet. 

Finally, there's another approach: think about what’s working well for you right now, and use that as a launching pad to think about your purpose. To do this, keep a journal for a week. Each night, right before bed, write down three good things about your day. Once you’ve jotted these down, think about why those things went well. Chances are, you already know what you find meaningful. This exercise will just help you bring that out into the open. 



 


The Selfish Gene by Richard Dawkins is considered one of the most influential books on evolutionary biology since Charles Darwin’s The Origin of Species. It was first published in 1976 however, the version I have is the 2009 reprinted version. This book is about evolution and is written by Richard Dawkins, the evolutionary biologist and author. The fundamental argument that The Selfish Gene makes is that the natural selection process in the evolution of living beings is not about making the species, community or group secure. It is about making the individual secure, and the individual is merely a vehicle for its genes. Altruistic behaviour happens only when individuals gang up for purely genetically selfish purposes that species and societies carry on, and perchance, thrive.

Darwin’s theory of evolution by natural selection was based on individual organisms. It is individuals that vary in phenotype, individuals that struggle to survive environmental pressures and compete over access to mates, and individuals that vary in fitness according to phenotype. Selfish gene theory, or the gene’s-eye view of evolution, however, offers a radically different picture of evolution by natural selection. Under this view of life, the fundamental unit of selection is the gene. Whereas individual organisms are temporary occurrences—present in one generation, gone in the next—genes are potentially immortal and their structure is passed on from generation to generation. As a consequence, the ultimate beneficiary of selection is the gene.




Key Learnings


The key message in this book is:
Evolution occurs through the action of natural selection on genes, not on individuals or species. Genes are selfish by definition in that genes that promote their own survival at the expense of other genes tend to be more successful. All animal behaviours can be traced to selfishness on the part of their genes.

The questions this book answered:
What are the processes by which evolution occurs, and how are genes central to this?

  • Evolution is driven by varying abilities and limited resources.
  • The basic unit of evolution is the gene, because it can exist as multiple copies and is therefore near-immortal.
  • Genes are selfish by definition: their survival success comes at the expense of other genes.
  • A gene’s phenotype – the way its code is manifested in its environment – determines its survival.
  • The survival success of a gene is dependent on its particular environment – both physical and genetic.

How does selfishness at the level of the gene influence behaviour at the level of the organism?

  • Organisms are machines built by groups of genes that cooperate only because they share a reproductive mechanism.
  • Genes program the brains they build with behavioural strategies that help their survival.
  • Competition between strategies results in a stable behavioural pattern in a population.
  • Mutually altruistic behaviours are often successful, because they benefit the host’s genes more than purely selfish behaviours do.

What application does this theory have for human behaviour and cultural development?

  • Human culture is also subject to evolution, and its basic unit is the meme.
  • Conscious human foresight can help us overcome the downsides of biological gene selfishness.


Evolution is driven by varying abilities and limited resources.

Over 3.5 billion years ago, in a primordial soup of molecules, the first, simplest form of life on earth came to be: a molecule able to copy itself, a Molecular replicators are made up of long chains of smaller building-block molecules in the same way that a word is made up of a string of letters. Replicators copy themselves by attracting other ‘letters’ and acting as a template for them to match up to. The first replicator automatically had a competitive advantage over all the other molecules in the primordial soup because they could not copy themselves, and hence the replicator became more numerous than any other type of molecule. However, mistakes in the copying process led to ‘daughter’ replicators that had a slightly different configuration than their ‘parent.’ These new configurations meant that some ‘daughters’ were able to copy themselves faster, or more accurately, giving them a competitive advantage over their ‘parent.’ 

More and more replicators were built from the finite supply of building-block molecules in the primordial soup, and these molecules were gradually used up. These two concepts – a population in which ability varies and an environment of limited resources – are the basic requirements for the process we know as evolution. As time went on, further mistakes in copying resulted in new advantageous characteristics, such as the capacity to break down other replicators and use their building blocks for replication: the first carnivores. Through the creation of new variations, and the survival of the replicators with the most useful advantages, more complex life forms emerged, eventually resulting in the variety of organisms we see today.


Evolution is driven by varying abilities and limited resources.

The basic unit of evolution is the gene, because it can exist as multiple copies and is therefore near-immortal. Evolution occurs through differential survival in a given population of entities with differing abilities, some survive and propagate while others die out. But contrary to what is often thought, the basic units that evolution acts on are not individual organisms but short snippets of DNA, the replicator molecule that is the basis of all life on Earth. The reason for this is that genes fulfil an important criterion that evades individual organisms: genes are not unique and can exist as copies in many different bodies. For example, all blue-eyed people have in their cells a copy of the gene for blue eyes. 

Most organisms, on the other hand, cannot replicate themselves as identical copies. This is because sexual reproduction does not produce copies but rather combines the parents’ genetic makeup to create new, unique individuals. The fact that genes exist as copies makes them near-immortal. While individual organisms tend to survive for no more than a few decades, genes can live for thousands or even millions of years. Consider that while your ancestors are long dead, you no doubt carry plenty of their genes in your cells and will in turn pass on at least some of them to your descendants.It is the genes’ multiplicity and potential for immortality that makes them candidates for evolution to act upon.


The basic unit of evolution is the gene, because it can exist as multiple copies and is therefore near-immortal.

Genes are selfish by definition: their survival success comes at the expense of other genes. A gene is ‘selfish’: it acts in a way that promotes its own survival at the expense of other competing entities. However, genes themselves have no conscious motives; it is simply their behaviour that we can describe as seemingly selfish. Similarly, while the process of evolution could appear to be motivated towards creating entities that are suited to particular environments, it is not consciously trying to achieve this. 

To understand why genes seem selfish, we must examine the physical environment they exist in: Genes come in packages called chromosomes, which are sheltered within the cells that make up an organism. Chromosomes come in pairs: humans have 23 pairs (46 chromosomes in total). Both chromosomes in a pair have the same organisational structure, so if an area on one chromosome houses the gene for eye colour, then the other chromosome will have a gene for eye colour in the same location. However, the versions of these genes may not be the same: one might be for blue eyes and the other for brown. Different versions of genes for the same characteristic are called alleles; for example, there are several alleles of the eye-colour gene. 

Because the different alleles try to occupy exactly the same spot on a chromosome, any survival advantage an allele gains is automatically selfish: it decreases the survival prospects of the other alleles.


A gene’s phenotype – the way its code is manifested in its environment – determines its survival. 

Physically, all genes are fairly similar: they are all snippets of DNA. Where they differ is the information they encode. DNA is basically a long molecular chain constructed of four types of molecules denoted by the letters A, T, C and G. Just as every word in the English language can be constructed from the 26 letters in the alphabet, these four basic building blocks can be combined into so many different and elaborate DNA sequences as to describe every feature of an organism. 

This code is translated into the instructions for how to build an organism’s body. Small differences in the code are expressed as characteristics like longer legs, a survival advantage for, for example, an antelope running away from a cheetah. The long-legged antelope escapes and lives to bear offspring with copies of the gene – the code – for longleggedness. Thus, the gene survives through its effect on the body of the antelope. This bodily manifestation of the gene is known as its phenotype. However, the effects of genes are not necessarily limited to the body they belong to. Virus genes don’t have their own bodies: their codes affect the cells of the body they infect; for example, they can cause the host body to sneeze, which helps the virus to spread and thus enables its genes to survive. 


The survival success of a gene is dependent on its particular environment – both physical and genetic.

Good camouflage for a tiger is very bad camouflage for a polar bear, because of the fundamentally different environments. A gene for tiger camouflage would have minimal chances of surviving in an icy environment. Genes are not just affected by their physical environment but also by the genes around them: all the variations (alleles) of a species’ genes in the same gene pool. This includes both the specialised genes that only certain species have, like genes for building wings or carnivorous teeth, and the shared genes that different species have in common.

The success or failure of a gene – no matter how useful – depends largely on what other genes share its gene pool. For example, if a gene for sharp carnivore teeth was introduced to the gene pool of a herbivorous species, it would most likely not be successful since the pool lacks other genes necessary for a carnivore to survive, such as a gene that allows the species to actually digest meat. On an individual level, sexual reproduction entails the constant mixing of genes, so every individual of a species ends up with a unique set of alleles. Some allele combinations prove more advantageous than others. Consider a bird species in which there is an allele that increases wingspan and another that lengthens tail feathers. An individual bird with both alleles will fly faster, while a bird with only one of these alleles may be unbalanced and fly more slowly. In this case, each allele is only successful in the presence of the other.


Organisms are machines built by groups of genes that cooperate only because they share a reproductive mechanism.

Organisms are machines built by groups of genes that cooperate only because they share a reproductive mechanism. A gene affects a characteristic of the organism it belongs to – e.g. its speed, strength or camouflage. When this effect is advantageous, the organism is more likely to produce offspring that carry copies of the gene, and thus the gene survives. However, one gene alone can’t build an organism. It requires tens of thousands of genes all working together to construct something as complex as a human body. But if genes are fundamentally selfish, then why would they cooperate in this manner? The answer is that the genes within a single organism share a reproductive mechanism and hence have a common goal: they are all trying to maximize the production and survival prospects of the organism’s eggs or sperm. By the same token, although a parasite like a tapeworm inhabits the host’s body, the tapeworm’s genes do not cooperate with the host genes, because they do not share a reproductive mechanism. 

The cooperation of genes manifests itself as a complete organism: the sum of their collected phenotypes. The genes basically build a machine – the organism – around themselves, and this machine produces offspring who carry copies of those same genes, thus helping them survive. While genes within an organism cooperate to ensure their survival, we should not expect individual organisms within a group to cooperate with each other, because their genes do not share a single common pathway of reproduction. Rather, under the direction of its genes, each individual should work towards the production and survival of its own eggs or sperm and should therefore act selfishly towards other individuals in its group. This, however, is not always the case, as we will see later on when examining the phenomenon of altruism.


Genes program the brains they build with behavioural strategies that help their survival.

It can take generations for one gene’s phenotype – for example, longer legs – to prove more successful than another. However, to survive, the bodies that genes build need to be able to react much faster to environmental stimuli – to eat, fight or flee in mere seconds. To facilitate this, genes build brains that allow organisms to respond to rapidly changing factors in their environment. We call these reactions “behaviour.” The natural environment can present an infinite number of different situations, so there is no way for an organism to have a prepared response to each one. Instead, behavioural responses are guided by ‘rules,’ which are encoded by the genes in a way that is analogous to how a computer is programmed. For example, two such rules could be for an organism to regard sweet-tasting things as rewarding and to repeat actions that lead to this reward. 

The problem with such rule-based programming is that it cannot always adapt to radical environmental changes. An attraction to sweet-tasting things was a survival aid for early hunter-gatherer humans but is a driver of the obesity epidemic in today’s calorie-loaded world. Intelligent organisms can minimize the negative impact of such outdated rules with two strategies: learning and simulation. Learning means trying an action to find out if it’s a good idea, and then remembering the outcome; simulation means modeling the outcome of an action before taking it, which not only saves effort but also helps avoid potentially dangerous actions. For example, an organism that knows beforehand that jumping off a cliff is a bad idea has a survival advantage over an organism that must try it to find out.


Competition between strategies results in a stable behavioural pattern in a population. 

Members of the same species are in direct competition with each other for resources, which can be expected to lead to confrontations between individuals. These confrontations can be dealt with via different behavioural strategies, ranging from fleeing to fighting to the death. Behavioural strategies, like any other characteristic of an organism, can be expected to vary, and some are going to be better for the survival of the organism – and its genes – than others. In the same way that the success of a gene is determined by its environment, the success of an organism’s behavioural strategy is determined by how all the other organisms around it behave. For example, take a population of birds with three behavioral approaches to confrontations:
  1. “Doves,” which flee if attacked;
  2. “Hawks,” which always attack and fight until severely wounded;
  3. “Retaliators,” which behave as Doves until attacked, after which they respond as Hawks.
In a population of Doves, an invading Hawk is very successful because no Dove stands up to it. Thus, Hawk genes increase in the population. However, when the population has become predominantly Hawks, the proportion of Doves begins to increase, because Hawks are more frequently injured in ferocious fighting with other Hawks, which are now abundant in the population. Neither the Hawk nor Dove is an evolutionarily stable strategy, because a population of either could be successfully invaded by the other. Retaliators, on the other hand, aren’t injured through unnecessary aggression, but they do defend themselves if necessary (unlike the Dove). Therefore, in a population of Retaliators, neither Hawks nor Doves would be successful; the Retaliator’s strategy is evolutionarily stable. Competition between strategies results in a stable behavioural pattern in a population.


The selfish survival drive of genes explains apparently altruistic behaviour like parental care.

As pointed out earlier, because genes control behaviour, and genes are selfish, then we can expect organisms within a group to behave selfishly toward each other. However, there are many examples of behaviours in nature that appear altruistic, not least of which are the many examples of extremely devoted parental care, such as a mother bird feigning a broken wing to lead a fox away from her young. Altruism here can be defined as behaving in a way that reduces one’s own chances of survival for another’s benefit. This apparent contradiction disappears when considered in the light of one of the basic characteristics of genes: they exist as multiple copies in multiple organisms. Thus, genes program behaviours that benefit their copies in other organisms, even at the expense of their own organism – but only if it produces a greater overall survival benefit to the gene. 

How does a gene ‘know’ that another organism is carrying copies of its genes? It doesn’t: genes aren’t conscious and don’t ‘know’ anything. But organisms that are kin do share copies of genes. Hence, genes that program organisms to aid their kin gain a survival advantage, and thus lead those behaviours to survive, too. Altruism is not necessarily reciprocated equally, though. Parents and children are equally closely related, but parents behave with greater altruism towards their children than vice versa. This is because in order for their genes to survive beyond one generation, the parents must ensure their children survive to reproductive age. For the children, on the other hand, the survival and well-being of their parents is far less relevant, hence the asymmetry in altruistic behaviour.


Mutually altruistic behaviours are often successful, because they benefit the host’s genes more than purely selfish behaviours do. 

When characterising interactions between organisms, a useful principle is the idea of the zero-sum or non-zero-sum ‘game.’ Basically, a zero-sum situation is one where one side wins and the other loses; for example, in the case of a cheetah chasing an antelope, either the antelope dies or the cheetah starves. In contrast, a non-zero-sum game is one where both ‘sides’ are playing against a ‘bank’ that holds the resources. One player winning does not mean the other has to lose. The players can stab each other in the back to gain a bigger share of the bank’s resources, but, depending on the rules, they can also cooperate to outwit it.

In nature, organisms generally compete for resources in their environments. Although there are many situations where the competition is a zero-sum game, such as in the case of the cheetah and the antelope, in other cases it can pay for the organisms to cooperate, either with members of their own species or even with other species. For example, ants “milk” insects called aphids for the sweet secretions they produce. The aphids might appear to be exploited in this arrangement, but in fact they gain significant protection from predation by having battle-ready ants around to protect them. Sometimes ants even raise and protect baby aphids inside anthills. Therefore, this cooperation benefits the survival of both ant genes and aphid genes. The end result – an increase in survival – satisfies a selfish motive, but the pathway to it is mutual altruism.


Human culture is also subject to evolution, and its basic unit is the meme.

One of the most distinctive traits of humans is culture: the aspects of our lives that are neither instinctive nor purely have to do with survival, for example, language, dress, diet, ceremonies, customs and art. Although basic human psychology and interests can probably be traced to the survival benefits of mutual altruism and aiding kin, these aren’t enough to explain the complexity and variety of culture. Instead, culture can be considered the equivalent of a gene pool, with the basic unit of cultural evolution being a meme instead of a gene. A meme is the smallest piece of culture with potential immortality, for example, a tune, an idea or a YouTube clip of a dancing cat. The methods of transmission are the methods of human communication: speech, writing, the Internet. Like genes, memes are in competition with one another. Some are in direct opposition – for example, evolutionary theory and creationism –, but all compete for human attention and memory. In the same way that genes cooperate to form complex organisms, memes also form complex entities: the Catholic Church is an aggregation of ideas, rituals, clothing and architecture around the central meme of an omnipotent God. Separating culture from biology helps explain some of humanity’s more peculiar expressions, such as celibacy, which goes counter to biological imperatives. If culture is its own evolutionary system with its own replicators, then those replicators need only survive within that system. They aren’t necessarily influenced by factors outside of the meme pool, such as biological survival. As with their gene equivalents, the success of memes is determined by their environment. Human culture is also subject to evolution, and its basic unit is the meme.


Conscious human foresight can help us overcome the downsides of biological gene selfishness.

Models of behavioural strategies show that populations tend to end up with a stable strategy, and that populations engaging in a mutually altruistic strategy tend to do well, even though each individual is motivated by the best interests of their genes. But in some cases an even more optimal solution for all can be reached by forgoing the immediate survival interests of the genes. Consider a population in which there are two species with two different confrontation strategies: the Hawks, who always attack in confrontations and will fight until death or serious injury; and the Doves, who run away if attacked. Hawks will always win against individual Doves, but in the long run their strategy is actually less beneficial due to the injuries they sustain from fighting other Hawks. The solution that most benefits all the individuals is the ‘conspiracy of Doves,’ where all individuals in a population agree to be Doves, forgoing the short-term benefits of behaving like a Hawk in order to reap the long-term benefits of living peacefully and avoiding serious injury and death. 

Genes are not conscious and do not have foresight, so they will never be able to partake in a conspiracy of Doves, even if it would be in their best interests in the end. Humans, on the other hand, are capable of conscious foresight. Our culture, if thought of in terms of memes, has already divorced itself from biological imperatives. We may not be genetically or intrinsically altruistic, but we can use our foresight to counter gene selfishness and, at the very least, to enter into the conspiracy of Doves for our own future benefit. We may even be able to attain the true altruism that does not exist in nature. Conscious human foresight can help us overcome the downsides of biological gene selfishness.





Theoretical physicist and former Santa Fe Institute President Geoffrey West provides an introduction to the universal laws of growth, innovation, sustainability and the pace of life in organisms, cities, economies and countries. The characteristics and dynamics of diverse biological organisms, cities and companies are bound by surprisingly similar laws. These rules reveal astounding, and often hidden, regularities that describe the structure and systems of life, as well as its limits.


Key Learnings


A hidden pattern sustains all life and culture.

Earth is home to over 8 million different species, from microscopic bacteria to enormous blue whales, as well as an incredible diversity of social life, cultures, cities and traditions. It can be quite overwhelming to think about. But the truth is that there are some surprising systematic patterns behind the complexity of biological and socioeconomic life. For instance, if you plot a graph of the metabolic rate of animals – that is, the amount of energy they spend per unit of time – against the body mass of those animals, you’ll see a perfectly straight line. The metabolic rate of any animal from a mouse to an elephant is perfectly fixed relative to its body mass. Not only that, but if in the same equation you substitute the metabolic rate for the total number of heartbeats in an animal’s life, you’ll get another straight line.



Source: Wall Street Journal

There is, however, one trick at play. To get this result, the scales need to be logarithmic, meaning the units on each axis need to increase by factors of ten, so from one to ten to 100, and so on.

Scaling refers to how a system responds when its size changes. Research has abundantly demonstrated the predominance of quarter-power scaling laws in biology. For instance, when an animal doubles in size (i.e. doubles its body weight), then its number of cells also roughly doubles, but its metabolic rate only increases by about 75%, rather than 100%, as you would naively expect. This is a phenomenon known as Kleiber’s Law, after Max Kleiber who pioneered this type of work in the 1930s. It can be formally written as q₀ ~ M^(¾), whereby q₀ is the animal’s metabolic rate, and M the animal’s mass. This means that a cat that is 100 times heavier than a mouse only consumes about 100^(¾) ~ 32 times the energy that the mouse consumes. In physics, this nonlinear behavior characterized by the systematic savings as size increases is referred to as sublinear scaling or economy of scale. The figure above, showing metabolic rate as a function of body mass (plotted logarithmically), highlights this behavior.

Take an example from the world of economics: if you plot out the number of patents registered in a city against that city’s population, you’ll find that the number of patents will increase 15 percent faster than the population, also producing a straight line.

These incredible correlations are not mere coincidences. What you’re actually observing are called scaling relationships. The examples above are just a peek into the ways organisms and cities with size, and understanding this phenomenon can illuminate much about the world.

For instance, new drugs are often tested on mice to model the way they’ll impact the human body. However, mice are of course much smaller than people – so how can scientists draw conclusions about humans from tests on rodents? Well, scaling can explain the answer. 


Scaling laws are rarely linear, and this has important implications.

Scaling laws rarely work in a linear fashion. Just consider one square foot. If you scale up the length of each side to three feet, the enclosed area will become nine square feet. In other words, the sides will increase by three times, but the area will increase by nine. In a similar way, a three-foot cube has a volume of 27 cubic feet, which means that if the sides of a cube are increased from one foot to three feet, they would increase by three times while the volume would increase 27 times. In other words, area and volume do not scale linearly with length, but with the square and cube of the lengths. Funnily enough this proves that Godzilla couldn't actually exist in real life. Godzilla is around 60 times bigger than a human. His volume and therefore mass would be 60³, or 216,000 times, the average weight of a human. However, the length and strength of his bones would only increase by the factor 60², or 3,600 times. As a result, he would be 60 times heavier than his bones are strong, and his bones would break in an instant. 

So, nonlinearity can explain why Godzilla isn’t real, but it also has important, practical implications. For example, at the outset of the 1800s, trans-Atlantic steamships generally weren’t considered economically viable because of the tremendous amount of space needed to house fuel. That is, until the English engineer Isambard Kingdom Brunel showed that, unlike the volume of cargo a ship can carry, which scales by the cube of its dimensions, the drag forces acting upon a ship only rise proportionally to the size of the vessel’s hull, which scales by the square of the ship’s dimensions. To put it simply, this means that the bigger the ship is, the less fuel it needs to carry each ton of cargo.


Biological scaling laws can be explained by a network-based theory.

We now know how the relationship between the metabolic rate and body mass of nearly all animals abides by a simple scaling law. However, we can be even more precise. We can also say that an increase of body mass by the factor 10⁴, or by four orders of magnitude, will result in an increase of the metabolic rate by a factor of 10³, or three orders of magnitude. 

Such relationships can be virtually identical for all life forms. West has a theory about this.He believes that a network-based theory can explain the origins of biological scaling laws. Here’s what that means:

All biological systems function by way of networks, which transport energy, matter or information. Common examples are the circulatory, respiratory and neural systems. Such networks share three generic properties, which might even explain the hidden regularities of biological diversity. 

  1. Networks are space filling, which means that the tentacles of the network need to reach every piece of the system they serve.
  2. Terminal units are invariant, which means that the endpoints, or nodes of delivery, such as the capillaries of the circulatory system, are about the same size and have similar characteristics, regardless of the size of the organism.For instance, the capillaries in a blue whale are actually about the same size as those in a human. To understand why, just think about your house and the Empire State Building. If the electrical outlets in this skyscraper were scaled up relative to its height, they would be 50 times larger than those in your home.
  3. The system is optimised, Over the course of the long process that is evolution, the performance of biological networks becomes optimised. For example, because of the various design constraints it faces, the human heart has evolved to expend the least energy possible when pumping blood through the circulatory system.
By taking these three general systemic properties and translating them into mathematical language, West has found explanations for the surprising regularities that can be perceived in the world.


Biological networks extend toward a fourth dimension, explaining why humans stop growing.

If you look closely at the mathematical details behind scaling laws, there’s yet another surprise to be discovered: in most cases, biological scaling factors involve the numbers ¼ or ¾.
For instance, the number of leaves taken as a function of a plant’s mass increases by a factor of 2 to the power of ¾. So, what explains the mysterious prevalence of the number four? The answer is buried deep in the properties of biological networks. 

These systems resemble fractals, which means that their geometry demonstrates a high degree of self-similarity. In other words, if you zoom in at random on one point of the network, the local picture will look like the zoomed out image. Just think of a cauliflower; if you cut out a single floret, it would look like a miniature version of the whole thing. That being said, the more curled a shape is, the more it “extends” toward a higher dimension of space. This is the fourth dimension – and it’s actually not all that difficult to understand. Just consider a one-dimensional line on a two-dimensional piece of paper. The more curled the paper is, the more it fills the entire space of the page and the more two-dimensional it appears.

In a similar way, biological networks are, as you already learned, space filling, which means that they appear to extend toward a dimension beyond their own. It’s this “fourth dimension” that explains the common role that the number four plays in scaling laws. This important number even accounts for why humans stop growing in adulthood. Imagine you doubled the size of an organism. In so doing, you would be doubling the number of cells it contains and the amount of energy necessary for their maintenance.

However, scaling laws dictate that the metabolic rate of an organism only rises by the factor 2 to the power of ¾, which is less than 2. Because of this, the demand for energy increases faster than energy can be produced, halting the growth in its tracks. The biological world is full of such interesting instances of the laws of scaling, but the social and economic spheres also offer compelling examples. 


Scaling reveals surprising similarities between seemingly different cities, while biological networks are analogous to urban centers.

Consider the cities of New York, Paris and São Paulo. They might not appear to have much in common; after all, they’re in disparate corners of the world and are homes to highly divergent cultures. Even so, there are a number of hidden similarities in these metropolises, and scaling relationships can make them plain to see. For instance, the number of gas stations in a city and the total length of pipes, roads or electrical wires all consistently follow a simple scaling law that depends on population. Here’s how it works: 

If you double the size of a city’s population, thus increasing it by 100 percent, the number of gas stations, as well as the length of pipes, roads and wires, will only increase by 85 percent. Then, there’s the< 15-percent rule, which holds that the larger a city is, the higher the wages, per capita GDP, crime rates, cases of AIDS or flu infections, number of restaurants and patent applications. That all seems intuitive enough – but what’s shocking is that all these indices rise by a factor of 1.15. That means a city with 10,000 residents and 100 restaurants would have 1,150 restaurants if its population were to increase to 100,000. That being said, since affluence varies by nation, such scaling laws only apply to cities within the same country. 

However, the similarities between organisms and cities don’t end there. Just like with biological organisms, cities can be thought of as networked systems. After all, they metabolize energy and resources, produce waste as well as information, and grow, adapt and evolve. Even the three generic properties of biological networks find equivalent features in cities. For example, biological networks are space filling, as are urban transport networks like roads, pipes and electricity lines. If they weren’t, they would never serve all the residences in the city.


The speed of life, social interaction and economic activity all scale with the size of a city.

Modern life has become so tied to the city that West feels a new human era is upon us. West's opinion, it began with the Industrial Revolution of the late-eighteenth century and can be called the Urbanocene. So, what can scaling laws tell us about this new period in human history? Well, in biology, the pace of life slows down as size increases. For instance, an elephant metabolises energy much more slowly than a mouse and also lives for a much longer time. In cities, however, life appears to accelerate with size.

Just take walking speed, which often increases with city size. In fact, in a small town of a few thousand inhabitants, the average walking speed is just half that in a city of over a million people, where the average speed clocks in at around four miles per hour. But it’s not just the pace of life that scales with city size; social interaction and economic activity do too. For instance, the West analysed cell phone data to find that both the time people spend on the phone and the number of calls they make increase at a regular rate relative to the size of the city they live in. Consider Lisbon, Portugal, a city of 560,000. There, people spend about twice as much time on the phone and call twice as many people as their counterparts in Lixa, a rural Portuguese town of 4,200.


Source: Wallstreet Journal


Or consider another example. While it goes without saying that the larger a city is, the more businesses it contains, the diversity of businesses – that is, the number of different types of establishments – increases only very slowly with size. As a result, doubling the population of a city will result in an increase in business diversity of just five percent, while the number of total businesses will double on average.


Scaling reveals universal dynamics that correspond to a company’s size and age.

We've just learned how the number and diversity of businesses scales relative to city size. But what about the scaling that occurs within a business itself? How do sales, expenses and profits scale with size? Actually, there are surprisingly common scaling patterns for all of these metrics. For instance, net income, gross profit, total assets and sales all scale up with incredible regularity relative to company size as measured by the number of employees.
That means, if you plotted a graph with these metrics on one axis and the number of employees on the other, you’d get a perfectly straight line. In other words, if a firm with 100 employees produces sales of $10 million, the same company would make $100 million worth of sales if it employed 1,000 people. The implication here is that, regardless of industry, location or age, there are clear patterns that depend solely on the size of a business.

Age is actually an interesting factor here and has its own corresponding scaling laws. Just like living organisms, companies are born, grow and, in most cases, eventually die. Not only that, but also like organisms, companies grow quickly in their youth before settling into a steady, but slow, rate of growth. As a result, regardless of sector, location and size, a company’s survival can be calculated with incredible accuracy based solely on its age. For instance, just around half of all publicly traded business make it past the ten-year mark. The probability of a company existing longer than 100 years is just 45 in 1 million, and a microscopic minority of one in 1 billion companies make it to 200 years. To put this into context, this law means that the seemingly invincible firms of our time, like Google, Facebook and Apple, will all eventually meet their demise.


Since the Industrial Revolution, the world has witnessed a population explosion, raising questions about sustainability.

We’ve learned a number of rules of scale and how they correspond to all manner of circumstances. But what do these laws mean for human life in general? Well, they can tell us a great deal about the human population. For instance, since the Industrial Revolution, the world’s population has been growing at an incredible rate. This boom has marked an unforeseen shift since, for 2 million years, the human population had been growing at a steady, albeit much slower, rate. Because of this growth, the human population first hit 1 billion around 1805. But the next billion came just 120 years later and the third a mere 35 years after that. 

As a result, the world population now stands at over 7 billion and, in 2017 alone, it grew by 80 million, the equivalent of adding an entire new Germany to the world. In short, we’re experiencing exponential growth. For every unit of time, the quantity measured will double. Put differently, if on the first day there was one human, on the second there will be two, on the third there will be four and so on. However, as we’ve already learned, there are natural barriers to the size and growth of any biological organism and scientists are in heated debate about whether this rapid population growth can be sustained. After all, the resources on our planet are limited and every new human needs to be fed, clothed and educated. 

The first person to identify this issue was Thomas Robert Malthus, whose 1798 book An Essay on the Principle of Population predicted that the food supply would grow more slowly than the population, eventually leading to the collapse of civilizations. From there, an organisation called the Club of Rome published a highly disputed study in 1972. Called The Limits to Growth, it demonstrated the potentially catastrophic results of sustained population growth. While some of the predictions these researchers made have been proven incorrect, the fundamental issue remains; can human populations and economies continue to grow forever? 


It’s unlikely that the earth can sustain such rapidly accelerating population and economic growth.

So, the human population exploded with the Industrial Revolution and has been increasing exponentially ever since. People have been warning about the impacts this sustained growth will have and it’s becoming increasingly clear that such growth is straining the relationship between human society and nature.This begs the question: Can we sustain a global population of over 10 billion and continue increasing levels of consumption without destroying the biosphere? Well, given the finite nature of the earth’s resources, the short answer is definitely not. This is a serious issue since today, both the world’s population and its economies are growing at exponential rates. 

Traditional economic theories maintain that such an ever-expanding economic sphere is possible; however, exponential growth would also require ever-increasing supplies of both energy and natural resources, things that the earth simply cannot provide. As a result, such open-ended growth will have serious adverse impacts on the environment – but it’s also bound to fail. To counter this argument, critics of such a notion like to say that innovation will play a critical role in solving this conundrum. But, at this point, even innovation would be a long shot to save the world from a major population crash. After all, for innovation to keep up with the problems caused by growth, breakthrough discoveries would also need to occur at an exponential pace. To the credit of the people behind such innovation theories, this kind of exponential innovation has been the norm in recent history.

Indeed, thousands of years elapsed between the Stone, Bronze and Iron ages, while less than 30 years transpired between the recent Computer Age and the Information and Digital Age that followed. But other problems loom. For instance, with the level of stress endemic to most modern lifestyles, it’s hard to imagine how an ever-increasing pace of life could be sustained without a resulting collective heart attack. The earth is in dire straits and serious action needs to be taken. What’s called for is a Manhattan-style project that brings the top thinkers together to address these urgent questions of sustainability.





In this book, Matt Ridley makes the case for evolution, rather than design, as the force that has shaped much of our culture, our technology, our minds, and that even now is shaping our future. Darwinism is “the special theory of evolution”. But there is a general theory of evolution, too, and it applies to society, money, technology, language, law, culture, music, violence, history, education, politics, God, morality. The general theory says that things do not stay the same; they change gradually but inevitably. 

The Evolution of Everything is about bottom-up order and its enemy, the top-down twitch—the endless fascination human beings have for design rather than evolution, for direction rather than emergence. Ridley tries to demolish conventional assumptions that major scientific and social imperatives are dictated by those on high. On the contrary, our most important achievements develop from the bottom up. Patterns emerge, trends evolve.

The author, Matt Ridley is the 5th Viscount Ridley and is a British journalist and businessman. Ridley is known for his writings on science, the environment and economics. 




Key Learnings

This book explores evolution outside the realm of genetics, be it the evolution of morality, economy, language or technology. Typically, we're taught that these things are created in a top-down manner by leaders, scientists, priests, business people and so on. However, when evolution is understood in its broadest sense i.e. as the gradual development of something, it is far more common for things to evolve from the bottom up. Ridley argues that evolution, in the bottom-up sense can explain virtually all human cultural changes.

Evolution is not limited to biology. It's in our culture, our economy, our technology, our morality and even our religions. Ridley promotes that we shouldn't fall into creationist ways of thinking, we would better to try to see the ways in which our culture evolves. In doing so, we stand to reap the great benefits.



With few exceptions, the history of Western thought is shaped by a creationist perspective.

When we think of evolution, we often think of biology, Charles Darwin and his evolutionary theory. But the word “evolution” doesn’t just denote genetics. Originally, “evolution” meant “unfolding” and described how things gradually changed without a plan. And yet, the history of Western thought has been dominated by a creationist mode of thinking. That is, explaining the world through design and planning. Consider a few examples:

  • The ancient Greek philosopher Plato thought that society functioned by mimicking a designed cosmic order; 
  • in The Iliad, Homer had gods deciding the outcome of battles; 
  • much later, the Christian reformer Martin Luther stated that our fate lay in the hands of God; 
  • the nineteenth-century German philosopher Friedrich Nietzsche believed that healthy societies were made by the plans of powerful leaders; and 
  • Karl Marx claimed that a planned state was the best means to encourage economic and social progress.
The list goes on. Again and again, we see top-down descriptions of how the world is designed or should be organised. 

However, there are a few exceptions to this creationist mode of thinking. Just take the ancient Greek philosopher Epicurus. Epicurus believed that the physical world, including society and morality, emerged spontaneously, needing no divinity or royal power to explain it. Everything, he said, was made of invisible atoms which followed the laws of nature rather than the laws of God. The Roman poet Lucretius adopted Epicurus’s stance, stating that the world was made of invisible particles. He believed the world had no creator and life had no end or purpose. Epicurus and Lucretius were thus precursors to Darwin. 


Darwinian evolution removed the notion of creationism from biology.

It was the ideas of philosophers and poets such as Epicurus and Lucretius and, later, Enlightenment thinkers like David Hume, which gave rise to the question: “If God is the designer of humans and the world, who designed the designer?” However, it was Charles Darwin who eliminated creationism from biology and replaced it with a theory of evolution through natural selection. Darwin came up with his theory of biological evolution after his sailing expedition to the Galápagos Islands, where he collected various animals and plants, and meticulously observed and reflected on his findings. 

Darwinian evolution argued for a mechanism that explained the emergence of complex organisms from simple cells. This mechanism was natural selection, or the process by which beings with specific characteristics that make them better suited to their environment have increased chances of survival.Today, Darwinian evolution is widely accepted as truth. Yet, since we have been able to decode genes, people now ask what individual genes are for. 

It has been argued that genes aren’t designed to serve the body. Rather, they use the body to serve themselves. As Richard Dawkins stated in his book The Selfish Gene, the only reasonable way to understand organisms is to view them as temporary vehicles used by genes to secure their continued survival. This idea is supported by the finding that many of the genes that humans and other organisms have appear to have no function. They don’t exist for the needs of the body: they’re just hitching a ride in a vessel. Dawkins’s description of the selfish gene provides a strong argument against creationism as it seems unlikely that an intelligent, divine designer would create “useless” genes. 


Evolution exists in culture, the economy and technology.

Although we associate it with biology and genetics, evolution’s reach is much longer than this. Evolution is inevitable in any system where information is transmitted with a degree of randomness, such as the genetic information in our DNA that we pass on to our children or the cultural information we impart to them when we raise them. In other words, evolution applies to human culture, too. The best example can be seen in the evolution of language. Actually, there is a strong parallel between the evolution of DNA and the evolution of language. Both are systems capable of combining a small number of basic building blocks to form virtually infinite permutations. The building blocks of DNA consist of four nucleobases; the building blocks of many languages are the letters of the alphabet. Moreover, DNA evolves through natural selection and, in a sense, so do languages. For instance, words and phrases that are popularly used in written and spoken language are likely to endure, while words that nobody uses will die out. 

The concept of evolution also applies to economy and technology. It was Adam Smith who first realised that markets could regulate themselves without an overseer such as a government. In his book The Wealth of Nations, Smith argues that general prosperity is produced by the free exchange of goods and services.

Later, in the twentieth century, economist Joseph Schumpeter understood markets as evolutionary systems that were constantly testing new products and services to meet human needs. The “fittest” products on the market were bought and sold, i.e., they “survived,” whereas the unfit products didn’t.

Technological progress, too, can be seen as an evolutionary phenomenon. Like biological evolution, technology moves from tool to tool through trial and error. In communication technology, for instance, the telegraph evolved into the traditional telephone, which evolved into the cell phone, which will inevitably evolve into another device one day.


Morality and religion are not God-given, but have evolved with society.

Most religions teach that morality is prescribed by God. For instance, the Judeo-Christian God had Moses climb Mount Sinai to receive the Ten Commandments to pass on to his people. In Islam, it was Muhammad who received the word of God and imparted this to his people. However, God isn’t necessary for morality. Rather, morality evolves through social interaction in which people seek out ways to communicate successfully and happily. While Adam Smith is famous for The Wealth of Nations, he also spent a lot of time exploring morality. Smith observed that morality was not so much taught as evolved - an attribute that develops as we mature in our societal framework. As children, we discover by trial and error which actions evoke positive responses and sympathy from others, and it’s through these discoveries that we have evolved toward a common moral code. So morality isn’t God-given. But since teaching morality is central to religion, what does this say about religion itself? It means that not even religion is passed on to us by God. Instead, it’s an evolving, man-made invention. Moreover, some examples make clear that the concept of God has an evolutionary history, too. For example, the ancient Greeks and Romans believed in several gods, while Christianity dictates the existence of only one God. There was also a shift from gods who were temperamental, foolish and desirous, to gods who were disembodied and virtuous. Just compare the jealous and moody Zeus to the holy and perfect Allah. Religions are also the result of selection among various people and beliefs. Christianity, for example, arose in the first century AD from a number of different competing religions in the Roman Empire. So in that sense, religions have evolved, too.


Creationist thinking shapes concepts of personality development and education.

Twins raised apart have very similar personalities. This is a fascinating discovery, because until the 1990s, psychologists widely assumed that personality depended only on a child’s upbringing. Even today, our idea of personality development is shaped by the creationist belief that culture creates a child’s personality when, in actuality it evolves from within. Consider the following example: toy shops are split into girls’ and boys’ aisles where parents are encouraged to buy trucks for boys and dolls for girls. This angers people who believe that behavioural differences between the sexes are culturally forced upon children. But while it’s true that culture evolves, this doesn’t necessarily mean that personality evolves along with culture, or that culture creates personality. In fact, there’s evidence against the theory that behavioural differences between sexes were generated by culture. 

Experiments show that, when offered a truck and a doll, girls will choose to play with the doll and boys with the truck, regardless of their previous experience. And, interestingly, the same is true of male and female monkeys. Therefore, personality evolves from within, and isn’t just influenced by culture. Education, too, is shaped by creationist thinking. However, evolving and experimental educational systems seem to be more successful. Education is governed by the belief that the best way to impart knowledge to children is through adult instruction, the idea being that teachers “create” educated children. But one educational system does better than many traditional schools – Montessori system. The Montessori method of collaborative, self-directed learning techniques have given the schools an impressive track record of producing entrepreneurs. Interestingly, the founders of Amazon, Google and Wikipedia all attended Montessori schools, demonstrating that learning thrives in evolving, bottom-up educational systems.


Innovation evolves on its own – there’s no need for leaders or governments to “create” it.

In its first edition, the Encyclopédie – the encyclopedia of the French Enlightenment published between 1751 and 1772 – contained nearly no entries on people. The authors wanted to remind readers that innovation evolves on its own, rather than being created by a handful of powerful people. These days, though, leaders are viewed as the creators of innovation. But really, innovation can flourish without top-down creation. Take leadership in business. Hugely influential CEOs like Bill Gates, Steve Jobs, Jeff Bezos and Mark Zuckerberg are granted nearly godlike powers for their innovation and success. So much so that, when Steve Jobs died in 2011, many people assumed that Apple would simply go under without him. And yet, companies can create success without any leadership at all. 

The Californian company Morning Star Tomatoes understands this and has been experimenting with self-management for two decades. And it’s working. It is a highly innovative company and its profits have increased rapidly, despite the fact that it has no managers or CEOs. Moreover, its success came about without any central planning or leadership.

Laws can also evolve from the bottom up. In most political science classes, students are taught that governments create laws and that it’s the state’s job to enforce them. But this is only partly true. Consider the Wild West. Many people assume that the nineteenth century American West was lawless and violent because it had no government. But the Wild West wasn’t as wild as we’ve been made to believe. With few formal law enforcement systems in place, the people regulated themselves. Customs and laws evolved from the people and weren’t dictated by a governing body.


Money and the internet are evolutionary phenomena.

Most of us take for granted that the internet belongs to nobody in particular. It is neither controlled by monopolising companies nor governments. So when it comes to money, which today is created and issued solely by governments through central banks, why do so many of us assume that it’s always been a government monopoly? In fact, money was once free to develop much in the way the internet does today. Money gradually emerged among traders, and wasn’t always controlled by rulers. Take Sweden, which established a free banking system in the nineteenth century. During this time, several banks – the central bank among them – competed to issue their own banknotes. This system worked remarkably well and not a single bill-issuing bank went out of business. Canada, too, took a similar approach. In the 1930s, it had no central bank and its banking system came out unscathed after the Great Depression. 

Today, thanks to the internet, we’re seeing new forms of self-organising money systems. For example, air miles, mobile phone credit and the internet currency Bitcoin. And so, the internet itself is an evolutionary phenomenon. The internet emerged in an unplanned, unpredictable way; no one had anticipated blogs, social networks or search engines. The internet has no core or hierarchy. Nobody controls it, yet it isn’t chaotic. Its inception came about through decentralised programming and hobbyist groups. Unfortunately, however, the internet is in danger of becoming controlled and centralised, as the number of governments that have opted to censor it has steadily risen. So, if we’d prefer the internet to avoid suffering the same fate as money, we must advocate for an internet that can continue to evolve freely.





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