On April 26, 1956 a truck driver from North Carolina changed our lives forever. Thanks to Malcolm McLean and his standardized shipping container, products could be manufactured in the places where they were cheapest to make and then shipped anywhere around the globe. This innovation in efficiency irrevocably changed the world economy. Geography was no longer a barrier as items crisscrossed the world in a new globalized economy where consumers were spoilt for choice.
Before the historic 1956 voyage of McLean's fifty-eight containers from Newark, New Jersey to Houston, Texas, goods were sent by trucks to docks and then loaded onto ships. But first the goods that had just arrived by ship had to be unloaded. Ever seen old pictures of dock workers rolling barrels and moving huge sacks with ropes, pulleys, and planks? That's what it was like before McLean. The process was expensive, inefficient, and time-consuming – goods often sat on docksides for weeks. The high cost and long wait times disincentivized long-distance trade. And there was no way you would ship anything perishable.
McLean was an entrepreneur who started with one used truck and eventually owned a fleet. He took more of a Mark Zuckerberg Facebook-style, ‘move fast and break things’ approach. Ship and iterate, in this case, literally. Initially, he simply drove his trucks onto ships. That was an improvement from loading and unloading goods, but he quickly realized the waste of space the engine and wheels represented. So McLean started loading just the trailers. These trailers were incrementally improved to make them more easily movable by crane, which also made them easier to transport by train. Like many innovations, from trains to transistors, it was a massive net gain. But, as always, this creativity destroyed occupations. Dock workers, for example, became redundant.
Thanks to the standardized container, goods could be packed into a box, which could be put on a truck, then a train, then a ship, then back on a train, truck, and into a warehouse, from where they could be distributed. Of course, it took another fifteen to twenty years before a process of refinement, logistical innovation, and revised regulations would lead to one-click orders that arrive the next day.
The shipping container led to the rapid growth of Asian manufacturing and the decline of US manufacturing. Out-of-season fruits and vegetables were now cheaply available all year round. Television sets could be shipped from China to the United States for just two dollars per device; iPads to Europe for just five cents. It was such an efficient way to transport goods that the carbon footprint of sun-loving tomatoes could be lower if grown in hotter places and then shipped than if locally grown under a heated greenhouse. Eating local isn't always better for the environment.
The price of goods also fell because manufacturers could take advantage of arbitrage opportunities, finding the cheapest labor anywhere on the planet and then cheaply shipping the product to where it would sell at the highest price. In the West, more people could afford what were previously luxury products. In the East, exports raised wages and grew the economies of what became known as the Asian Tigers – Singapore, Hong Kong, South Korea, Taiwan, later China and others. Standards of living rose everywhere.
The story of the standardized 8-foot by 8.5-foot by 10-foot, 20-foot, or 40-foot corrugated Corten, all-weather steel shipping container is a story of wealth creation and the expansion of the space of the possible by energy savings under the law of innovation. And it follows many of the innovation lessons we learned about in Chapter 4.
It was an adjacent possible – more people were driving cars, creating congestion on roads. Trucking became less efficient. It was a simultaneous discovery – McLean wasn't alone in his idea of putting trucks on to ships. The basic concept had been developed by the military, and others were also trying to develop a standard approach, calculating the most efficient size and logistics for the boxes.
Today, 80–95% of manufactured goods are shipped with shipping containers. The next waves of innovation in shipping may be electric self-driving ships, loaded and unloaded by autonomous robot cranes. It's an easier self-driving problem than cars on roads – there are fewer lanes and pedestrians in the open water. But the results will be incremental relative to the invention of the shipping container itself.
Innovation drives economic growth by expanding the space of the possible. It is by the law of evolution and our collective brains that we innovate. Our innovative efforts have focused on efficiencies such as the shipping container, but we're running out of ways to become more efficient. Remember, higher income beats frugal spending; higher revenue beats lower overheads. Without new energy technologies, improvements in efficiency become smaller and smaller and harder to find, leading to what economist Tyler Cowen calls the Great Stagnation.
Our story is one of slow but steady progress – the background sound of everyday life – punctuated by leaps in human capacity driven by key new technological innovations that unlock new energy. This in turn increases cooperation. And in turn allows us to innovate improvements in efficiency by the law of evolution. From hunter-gatherers to farmers to industrialists to technologists.
Some innovations open up new possibilities, creating a scramble for low-hanging fruit. The Internet led to a burst of activity in websites and e-commerce; the iPhone led to a proliferation of apps; artificial fertilizers vastly improved agriculture in the Green Revolution; the shipping container revolutionized trade; lithium batteries allowed for electric vehicles with a reasonable range; CRISPR has led to massive advancements in gene editing such as GMO foods increasing the efficiency of agricultural production; machine learning and AI may supplement or even replace human cognition.
The real leaps, however, happen when those innovations raise the energy ceiling. And so while it may seem like the Internet is as large a leap as the Industrial Revolution, it is not. Instead, the Internet has led to a Second Enlightenment which we hope will lead to a true Second Industrial Revolution – an energy revolution.
The Internet and its spaces, such as Facebook and Twitter, are the modern coffee shops of our Second Enlightenment, allowing scientists, engineers, politicians, entrepreneurs, and everyone else to share tweets, podcasts, blogs, newsletters, TikTok videos, and other modern pamphlets. This new Enlightenment includes us all. While we lament the rise of fake news and apparent polarization, all the Internet has done is speed up the processes that always took place, of misinformation and correction.
The fake news of the past – that carrots improve eyesight, Napoleon was short, or that the Great Wall of China can be seen from space – persisted for decades. But with the Internet, misinformation spreads and so too do the corrections. In the xkcd comic Duty Calls, Randall Munroe immortalized this urgency we feel to correct people on the Internet. The protagonist is asked, ‘Are you coming to bed?’ They reply, ‘I can't. This is important. Someone is wrong on the Internet.’
The urgency with which netizens seem to want to correct people has a name: Cunningham's Law, after the inventor of the Wiki, Ward Cunningham. Wikipedia, arguably one of the greatest contributions to the modern world that exceeds whatever the Library of Alexandria might have been, is powered by this inexorable desire to correct others.
Cunningham's Law states that the best way to get the right answer on the Internet is not to ask a question but to post the wrong answer. A software engineering friend once sheepishly admitted that when they ask questions on StackOverflow – a Q&A platform for programmers – they use a puppet account to post a wrong answer to their question, which typically brings in a brigade of programmers eager to correct the injustice.
‘Someone is wrong on the Internet! I must correct them!’
Just asking the question elicits far fewer responses.
And so just as the Enlightenment laid the foundation for the Industrial Revolution and then empowered it, so the foundation for the next true energy revolution is being laid by the flurry of ideas flowing around the Internet, that are debated and dismissed; the fifteen minutes of fame and falls to infamy; the calls for cancellation and the reading beyond our bubbles. And with that revolution will come the unlocking of the next level of human potential.
The next energy revolution will be fusion. Perhaps a mix of harnessing the fusion reactor in the sky – our sun – through solar power, and control over fusion, if we ever achieve it. With greater energy control, we can begin accessing the vast trove of resources relatively close to us. For example, mining asteroids for rare metals using robots and then gradually figuring out how to do it ever more efficiently. The Jetsons promised us flying cars. Back to the Future promised us hoverboards. In contrast to other science-fiction tropes that are now commonplace – cellphones, video conferencing, robotic surgery – flying cars, hoverboards, moon bases, and interplanetary travel have been stifled by the stillborn nuclear age and transition to the next energy level – fusion. With fusion, all these and more once again enter the realm of the possible.
As we improve fusion, its EROI increases and the virtually limitless availability of hydrogen will lead to an unimaginably large space of possibilities. It is impossible to predict the heights our grandchildren will reach, but it will be staggering. Our lives and all that we have achieved on the back of fossil fuels will seem as primitive to our descendants as the Middle Ages are to us.
But to get there, we need to increase our scale of cooperation, incentivize wealth creation over wealth appropriation, and trigger a creative explosion.
Cultural evolution creates punctuated innovation – lots of incremental innovation with some occasional leaps via serendipity and recombination. Some of these innovations open up new spaces that lead to an innovation gold rush. Computing and information technology has seen such a gold rush in recent times: various innovations big and small in the microchip, Internet, lithium batteries, communication, machine learning, and most recently artificial intelligence. How do we trigger that same kind of creative explosion in other spheres of life? In Chapter 4 we focused on COMPASS's seven secrets of innovation and how they can be used at an individual level and at a corporate level to vastly improve our collective brain and the speed of cultural evolution. We can apply similar insights from our theory of everyone to practical policies at a societal level. Here are some examples.
Language, speech, talking to one another. These are social synapses that are firing in our collective brain. Restricting that firing reduces trust in one another and cripples our capacity for innovation. It is collective brain damage.
In his vigorous defense of liberty, philosopher John Stuart Mill reminded us ‘that it is important to give the freest scope possible to uncustomary things, in order that it may in time appear which of these are fit to be converted into customs’. Mill was describing what we would now call cultural evolution – the evaluation of different ideas and the spread of those that work best. But cultural evolution is most efficient when ideas are allowed to flow freely. Limitations on free speech are like blockages in the pipes of progress, preventing us from seeing the world as it is. And if we can't see the world as it is, we can't figure out how to fix it.
We used to believe the Earth was the center of the universe. You got into trouble for suggesting otherwise. We used to believe that it was natural that some people should be able to own others. Wars were fought to end slavery. For the uncustomary to become customary, we must be exposed to alternatives so that we can evaluate them.
To solve problems, we must first understand them. Take the gender wage gap for example – the gap between the average earnings of all women versus all men, often quoted as 70 cents to the dollar. If we stubbornly insist that the main explanation for this gap is bias, discrimination, and/or sexism, we are guilty of either not being specific enough about what constitutes and causes bias, sexism, and discrimination to be able to act, or, worse still, we may jump to solutions that may not work or, like proximate patches, create new problems. The large industry of HR implicit bias training or attempts to debias hiring committees are examples of failed policies that lack evidence. A 2019 review of 492 implicit bias studies consisting of 87,418 participants found no evidence that implicit bias training programs brought about behavioral change. Other reviews suggest diversity training can even backfire, increasing bias.
An alternative approach is a free exchange of hypotheses with critical tests and remediations based on evidence. Seventy cents to the dollar is a statistic that looks at the median wage of all men and all women across all occupations – the unadjusted wage gap. It compares high-paid majority male CEOs with low-paid majority female social workers. What leads men and women to these different careers with different tasks, wages, and lifestyles may be a result of limited choice, boys and girls receiving different encouragement to pursue different careers, differences in long-standing evolved preferences for types of tasks, inequalities in male and female participation in child-rearing, lack of societal support for balancing child-rearing and careers, or many other possibilities. When related factors such as occupation, experience, or hours worked are controlled – the adjusted wage gap – the size of the gap shrinks or disappears. But these controls, regardless of what they are, are precisely the policy levers and potential solutions we need to address the wage gap.
Easy answers or certainty over what the answer must be – or worse still, sanctioning unfavorable hypotheses – hinders our ability to discover the truth and act on it.
The world is a complicated place and doesn't always conform to what we think or hope the answers are. We can only arrive at the truth in a diverse environment of different backgrounds, considering all hypotheses and ideas – both those we like and those we don't. Cultural evolution needs the fuel of diversity and free speech to create the variation for transmission and selection. This kind of exploration needs a diversity of people with different experiences to come together in a safe space that enables unfettered free speech.
This is how science works best.
We are all biased. We all think we're on the factually and morally correct side of any debate. None of us is immune and none of us can even see the full extent of our bias – what's called the bias blindspot. I'd like to think that scientists are more likely to change their minds in the face of new evidence, but I know that this is rare even among scientists trying their hardest to be unbiased.
Science doesn't work because we're enlightened humans who see past our incentives and our life experience. It doesn't work because we readily change our minds in the face of new evidence. No, science works because we commit to a method of discovery, there is agreement on what counts as evidence, and, most importantly, we are incentivized to show others that they're wrong. It's a collective act that slowly converges on the truth. But our findings can only be trusted if we are free to find the opposite to whatever current political sentiments suggest is the right answer.
In 2020 researchers Bedoor AlShebli, Kinga Makovi, and Talal Rahwan published a paper in Nature Communications, a journal within the prestigious Nature family of academic journals. The paper was titled ‘The Association between Early Career Informal Mentorship in Academic Collaborations and Junior Author Performance’. Using the Microsoft Academic Graph database of scientific papers, citation networks, and information about authors, they found that the work of female scientists with female mentors is associated with lower scientific impact than female scientists who have male mentors. They argued that this finding raises ‘the possibility that opposite-gender mentorship may actually increase the impact of women who pursue a scientific career. These findings add a new perspective to the policy debate on how to best elevate the status of women in science.’
Understandably, the paper was met with a swift negative response on social media. There is a real potential that these findings could lead to female researchers receiving fewer applications from talented female students, a feedback loop that could further perpetuate whatever might be driving the finding (assuming the finding replicates). The negative response eventually led to a retraction. With no further context, this might have been the story of a bad paper with careless consideration for the implications of the findings. But it is instead the story of how bias can creep into the scientific record, distorting truth and affecting our ability to understand the world.
In 2018, just two years earlier, Nature Communications had published another paper, this time by Bedoor AlShebli, Talal Rahwan, and Wei Lee Woon. This was titled ‘The Preeminence of Ethnic Diversity in Scientific Collaboration’. Using the same Microsoft Academic Graph database, the authors had used a similar method, finding that ‘ethnic diversity had the strongest correlation with scientific impact. To further isolate the effects of ethnic diversity, we used randomized baseline models and again found a clear link between diversity and impact.’ They concluded that ‘recruiters should always strive to encourage and promote ethnic diversity’.
This paper, published by two of the same authors in the same journal with the same dataset and similar methods, was met with praise and remains, unretracted, in the scientific record.
As with any paper, both studies have their strengths and flaws, and supporters and critics can point to these as evidence for why one, both, or neither deserved to be retracted or never published.
The main critique of work like this often boils down to perceived harmful effects. A finding from the same dataset that female mentors are bad for female scientists is harmful, but a finding that ethnic diversity is good for impact is beneficial. This harm and benefit may very well be true, but there is a long-term cost to this short-term thinking. Selective condemnation based not on accuracy but harm supports what Plato called a noble lie – something false that is nonetheless maintained and promoted because it has perceived positive effects on society. Noble lies, especially when naked in their bias, squander scientific credibility. Whatever the truth, if people don't believe that for any finding an opposite finding could have also been published, then science becomes nothing more than untrustworthy propaganda, mirroring and supporting what we already believe.
The solution to misinformation is more information. The answer to the infamous fire in a theater analogy is that when someone falsely shouts ‘Fire!’, we need other voices to shout ‘No there isn't!’ And we need to exploit indirect reciprocity, tracking reputations like the boy who cried wolf, turning false fire alarmists into untrustworthy sources who lack credibility in other domains of life.
Many point out that there are problems associated with a policy of free speech, but these problems are not resolved by restricting speech. For example, some fear that power differences mean that speech is never truly free because some voices will be louder than others. But this problem is only made worse by restricting free speech. Powerful voices that can shout loudly in an environment of free speech can be balanced by whispers that grow into roars. But in an environment where speech is restricted, those same powerful voices can ensure alternative softer voices never speak at all.
This is not a left or right issue. There are real legislative proposals restricting speech in both directions. In US states governed by Democrats laws have been proposed to regulate social media companies when it comes to hate speech and extremism. In US states governed by Republicans laws have been proposed to prevent social media companies from removing hate speech. Scientists are disincentivized from saying things that would upset donors or their funders or cause them to lose their livelihoods. Some have attempted to pass laws that explicitly restrict what scientists can say. This is a bipartisan issue that affects all of us. None of us likes hearing things we disagree with, things that undermine our livelihoods or challenge features of the world that benefit us. If you have enough information to audit people's incentives, you'll often find that they advocate for things that directly or indirectly improve their material well-being, reputation, or status.
Unfettered free speech is historically unusual. That's why it was explicitly enshrined in the First Amendment of the US Constitution. It was an unusual and important cultural innovation in a world where laws prosecuted blasphemy, offensive speech, or insulting the monarch. Many of these laws are still on the books in the old worlds of Asia and even Europe. In 2009 an Austrian woman was fined for insulting the Prophet Mohammad, a ruling upheld in 2011 by the European Court of Human Rights. In 2022, after the death of Queen Elizabeth II, British anti-monarchist protesters with Not My King placards were threatened with arrest. British police regularly arrest people over online posts and comments deemed racist, offensive, or hate speech – not protected speech in the UK. Where the freedom to speak is uncertain, it has a chilling effect on people's willingness to express their honest opinions and the free exchange of the ideas that lead to innovation and creativity.
Of course, the US First Amendment only restricts government, but the broader principle of free and open exchange – free speech – protecting even and especially speech we would rather see banned, is essential to science and progress. The First Amendment has bled over into a culture of free expression that requires protection.
The importance of a safe space to speak one's mind and where we can reveal how we think the world really works is emphasized by research on psychological safety.
In a famous analysis conducted by Google, Project Aristotle, psychological safety – the freedom to express what you really think and resilience to hearing ideas you don't like – emerged as a key prerequisite for successful teams, especially diverse teams. Diverse minds can only combine into a brilliant collective brain when they trust one another. When people trust each other, they feel more comfortable saying what they really think. And that's critical to being shown why they're wrong, showing others why they're wrong, or discovering a new truth at the intersection of ideas and beliefs previously isolated in the heads of different people.
We can create a culture of psychological safety by encouraging in interpersonal interactions what's called the robustness principle (Postel's Law) in software engineering: be conservative in what you do, be liberal in what you accept from others. In programming this refers to, for example, outputting well-formatted files but robustly accepting poorly formatted files from other programs. Don't create files with missing sections or stray semicolons, but be able to read them if they have these mistakes. In communication it means being generous to others’ intentions – ‘steel-manning’ rather than ‘straw-manning’ their position – but personally making an effort to communicate clearly. A steel-man argument attempts to make the best version of someone else's argument, perhaps even better than they made themselves. Steel-manning is the strategy for people who see arguments as a means of together arriving at the truth rather than sparring to win for the sake of winning. Straw-manning is the opposite, taking the weakest version of an argument and arguing against it with the goal of winning rather than learning.
It's hard to know in advance what will and what won't cause harm in the long term, and so the bar for what we should ban must be incredibly high and err on the side of not banning or suppressing speech. This is particularly important when it comes to freedom of speech in science, because reality is complicated and science is never settled. If we can't trust that the scientists are speaking freely then how can we trust science? Take, for example, group differences and the role of genes that we discussed in Chapter 3. Based on my reading of the evidence, I come down on the side of culture being the primary cause of these differences, but you should only believe me if those who believe otherwise are equally able to express the most defensible version of their position. If the only voice that could be heard in polite circles was mine then how could you know that there was an alternative argument and hear the evidence for it?
No one has a right or even a reasonable expectation to not be offended. We make progress not by bludgeoning our opponents into believing they are bigots and bad people, but by finding out what people think and why they think it. What evidence they have and what critical evidence they would need to change their mind. The reasons why we disagree with someone have to be based on logic and evidence, not group membership or prejudices. To err is human, but being wrong should not end people's livelihoods or their ability to say something else. Though it may change the credibility of what they say, it should not change their ability to say it. It would be like preventing an entrepreneur from starting another company because their previous company had failed. So many innovations would be lost in such a closed culture. Free speech is critical to the process of discovery and the triggering of a creative explosion, especially for social innovation. The vibrancy of the United States – its robust debates, fights, and protests, and even racist and anti-racist polarizing discussions – is a product of the freedom to speak freely. But the goal should not be to win the argument, it should be to arrive at the truth as a society. The norms of how we argue are critical to this process.
The world is a complicated place. Yesterday's obvious truths are today's falsehoods and vice versa. As scientists we try our best to steel-man an opposition's arguments. The goal is not to win the argument, but to arrive at the truth. And that means seeing our opponent not as an opponent but as a fellow truth seeker who deserves whatever assistance we may render in developing the best version of their argument no matter how wrong we think it is.
That's why censorship by government institutional misinformation tribunals or making Mark Zuckerberg, Elon Musk, or whomever they designate arbiter over what is true and false is not a solution to the real problem of misinformation. Instead, like many proximate, band-aid solutions, it creates new problems. Misinformation is a real challenge, but banning or suppressing speech is not the answer.
The person in charge of deciding the truth may not always be the person you want. Remember the opposition may one day be in power and a person with different politics may one day run the company. Laws must be made in a Rawlsian manner, prepared for a time when you and yours are no longer in charge. We must be ruled by principles, not people. For tackling misinformation, we want emergent, systems-level solutions such as offering more, not less, context and information.
There is value in minimizing the ability to create bots and fake accounts that poison our social network streams by flooding them with content that is not representative of what actual people think in an attempt to exploit our social learning biases. But real people should not be restricted in what they have to say.
A lack of free speech cripples the collective brain. It deprives it of information, the sparks of ideas moving from person to person that could light the next fire that radically changes our lives. It is cultural evolution and cultural-group selection that sorts it out through differences in scientific discovery.
None of this abrogates our responsibility as individuals to consider the impact of dual-use discoveries or harms we care about. Good science and good policy require careful consideration of the broader impact of what we discover and how it can be contextualized for mass consumption. In engineering, these are referred to as dual-use technologies. As we discussed previously, nuclear technology gets you power plants and bombs. Rockets can launch satellites and warheads. Care is required in these areas of research, even if they are the path toward energy abundance.
The rigorous defense of speech – even speech you vehemently disagree with – is perhaps the most important policy for triggering a creative explosion. At an interpersonal level, laws and cultural norms that protect free speech and provide psychological safety ensure that ideas can flow. At an institutional level, the same is achieved by ensuring people have more access to the ideas and discoveries of others. These institutions and technologies then become knowledge and skill boosters.
Creating greater connections between people and greater access to diverse cultural packages, ways of thinking, analogies, metaphors, skills, and knowledge lead to greater educational and income outcomes. Interpersonally, this often requires talking to people you disagree with, opening yourself up to a wide array of weak links with different ideas. Your best ideas and new jobs come not from those you regularly interact with – your strong links who share your preferences, consume the same information, and think like you – but those you know peripherally who belong to other, outside networks. Tighter, more closed communities are the least likely to see new solutions.
Beyond interpersonal dynamics, access to high-quality education, libraries, and the Internet have all been shown to boost graduation rates, income, and lifetime outcomes. One study found an up to 300% return in spending on annual Internet access by a school district in terms of incomes for former students, mediated by their improved academic performance. Those are fantastic returns. Obviously, like providing micro-nutrients to calorie-deficient communities, the impact of school Internet access will be larger among communities with lower household Internet access.
Before the booster that is the Internet, people found information through public libraries. When Andrew Carnegie, the richest man in the world at the turn of the twentieth century, created free libraries across the United States, cities with those libraries had 7 to 11% higher patent rates than comparable cities without Carnegie libraries. It's the kind of philanthropic spending that concentrated wealth allows and that governments don't always provide. Instead, in a beneficial exchange, Carnegie can serve as an innovator through the philanthropic sector while governments can then select the successful ideas and scale them in a way that few philanthropists can. The private sector often excels at innovation that the public sector can then more efficiently deploy at scale.
The brains of a cultural species do well when they have access to high-quality information and skills transmission. Indeed, this is part of why Silicon Valley is so innovative.
The story of Prometheus stealing fire from the gods is a story of intellectual property (IP) law. After Prometheus stole fire from the gods, the gods still had fire, but now humans did too. And with that IP theft, we cooked on camp fires, smelted steel, blasted rockets, and made unimaginable progress. The ability to recombine IP is critical to innovation.
Japanese brands were once synonymous with poor quality. The car industry is a good example. Early Japanese cars were poor-quality knock-offs of European and American models. Some were hybrids of the different designs that Japanese car manufacturers could access. But eventually, copying turned to recombining. The careful, incrementally improved culture that led to modern bonsai was recombined with Western culture to create new processes such as kaizen, the Toyota Way, and other ways to continuously and incrementally improve technology. The result was Toyota, Nissan, Mazda, and other Japanese car companies becoming the reliable brands they are today.
Chinese brands, for example Huawei and Haier, are now going through a similar process.
Patent laws give inventors exclusive rights over their invention for some set period of time. The relationship between patents and innovation is one of balance. Too strong patent laws stifle recombination by restricting others from building on the invention. Too weak patent laws create weak incentives to innovate without the ability to economically benefit from the risks taken to reach the invention. In fast-moving industries, policies that err on the side of opening up discoveries encourage more innovation while still allowing inventors to enjoy a first-mover advantage.
In the tech sector, the restrictions of patents are overcome through cross-licencing. Companies are mutually dependent on each other's intellectual property (IP). Faced with the possibility of a cold war of patents and mutually assured destruction via patent litigation, the industry has adopted a policy of allowing the free use of others’ patents within reason.
In Silicon Valley, the flow of IP, ideas, skills, and culture is also enabled because California doesn't enforce non-compete agreements. Job hopping is common and one way to acquire IP and talent is to simply hire the engineers responsible for creating a particular product. This means skills and cultural traits can recombine across start-ups, empowering recombination in the Valley's collective brain, giving the West Coast a distinct advantage over the East when it comes to innovation and giving the United States an advantage over other countries.
It also helps that merit and performance are highly competitive and equally highly rewarded in Silicon Valley. These incentivized demonstrations of merit have side effects such as the empowerment of the open source software movement. People are eager to demonstrate what they can do, even for free, because reputation is heavily rewarded in the long run. The power of the meritocracy and rewarding ability has a long history in successful enterprises and empires.
Evidence for the way in which meritocratic systems outcompete those based on group membership or who you know is manifold.
China's imperial examinations led to a scholar class, selecting the best regardless of background to administer vast empires that lasted for centuries. Genghis Khan is famous for implementing a meritocracy that selected the best and brightest for the most important positions regardless of tribe or family. The Great Khan's meritocracy incentivized followers to give their best in bloody conquests. They knew that they were judged by their ability and that there was no preordained limit to what they could achieve. In the United States, there is a long history of successful concerted meritocratic efforts, including the Manhattan Project to develop a nuclear bomb and the Apollo program to put a man on the Moon.
Today, that meritocracy is under threat as more objective measures are replaced by measures that are easier to game. Standardized tests such as the SAT and GRE are being dropped in favor of more subjective, less comparable, and easier-to-game measures such as teacher grades, letters of reference, or work experience open to only a few. These measures are more susceptible to outside influence and create the uneven playing field and subsequent inequality we discussed in the previous chapter. Some privileged students may have more access to test preparation than others, but an objective test gives everyone a shot and has been a leading source of opportunity for talented poorer kids with huge potential to prove themselves. References, on the other hand, require connections. Work experience requires time, opportunity, and funding, all scarce resources for the less affluent. This move to avoid objective measures of ability is a coalition of the privileged who want to protect that privilege and those who want more flexibility to create better representation. Some of this is nobly motivated, but it ends up as an unfortunate alliance that will harm our innovative capacity and harm those it's trying to help. This eventually hurts us all.
Moreover, these policies lead to increased intergroup division and stigmatize minority candidates who may have comparable or greater ability than their peers in other groups. If the bar seems lower for one group than another, any graduates or hires in that group could be perceived to have less ability even when this is not the case. This leads to the problem of rational racists and Bayesian bigots that I'll discuss in Chapter 12. When some win prestigious places at the expense of others on the basis of uncontrollable factors and not skills or cognition, they turn an individual competition into a zero-sum intergroup competition. They create Enron effects.
In the year 2000 a large energy company – Enron Corporation – was flying high with a market capitalization of over $100 billion and a share price that had risen from $20 to over $80. By the end of 2001 it was pennies a share and the company went bankrupt. What became known as the Enron Scandal was widespread fraud and illegal accounting practices hiding Enron's failures and true value. As a result of the cooperative fraud, Enron's collapse also took down its accounting firm, Arthur Andersen, turning the Big Five into the Big Four (leaving Deloitte, EY, KPMG, and PWC). Tens of thousands lost their jobs, investments, and retirement funds. The CEO, Jeffrey Skilling, was sentenced to twenty-four years in prison, but was released after twelve.
Skilling was a huge fan of evolution. His favorite book was Richard Dawkin's The Selfish Gene. Skilling attempted to implement evolutionary principles in his business practices and corporate culture. But too little knowledge is a dangerous thing. Skilling understood that at the heart of evolution is selection and competition but forgot that there is also diversity and cooperation. Skilling's policies created a zero-sum environment. One in which another's failures were predictive of others’ success. We can call this the Enron effect.
‘Rank and yank’ was one of Enron's more famous policies. Indeed, it was celebrated in business books and media at the time. Performance reviews involved ranking employees on a bell curve. The top 5% were considered superior and received the largest rewards. The bottom 15% were fired. This led to a toxic culture of destructive competition where people lied, deceived, formed alliances, and undermined one another to avoid losing their job. Remember, it's easier to be nice when there's lots to go around. Skilling didn't invent rank and yank, but where it's found, it creates zero-sum conditions conducive to destructive rather than productive competition. People work hard to harm one another rather than work hard to be better.
Though it may seem counterintuitive, helping other countries, even former enemies, avoid Enron effects by improving their development is good for the world as a whole. The Marshall Plan, providing aid to help rebuild Western Europe, including former enemy Germany, contributed to the long-standing peace in Europe following the Second World War.
We are clever because our culture is clever and we are kind because there is plenty to go around. Only conditions whereby rewards are shared and the success of others contributes to our success can keep us together. Otherwise, ever-present diversity causes us to come apart.
Today, we all face Enron effects thanks to rising inequality, slowed growth, and economic decline triggering zero-sum biases and incentivizing destructive competition between people and groups. This in turn is weakening one of the solutions to the paradox of diversity: structured diversity.
Microsoft, the United States, and the Roman Catholic Church all have one thing in common. It has led to their persistence and historical success. All have incorporated structural diversity into their organization to boost knowledge and spread solutions. They offer a middle-path solution to the paradox of diversity.
There are different ways to distribute diversity. As we discussed, at one extreme, one could solve the paradox of diversity by each person having a greater diversity of experiences. For example, workers and researchers with an interdisciplinary educational background have within them a diversity of skills and knowledge. Similarly, people who have a more culturally diverse background or have lived in many places around the world, particularly when younger (often called ‘third culture kids’), have within them a greater diversity of cultural experience. The most famous third culture kid is probably Barack Obama, who had parents and step-parents from different cultures and who grew up in Indonesia and Hawai‘i.
At the other extreme of personal diversity, diversity could be completely diffuse but with a common communication protocol. Examples include interdisciplinary teams of people with different training and educational backgrounds or multinational teams working on a common challenge.
A more attainable strategy is clustered cultural diversity whereby separate parts all work together toward a common goal. These are the administrative units and states, the departments and divisions, the work functions and specializations whose futures are inexorably tied.
At the core of this puzzle is what is called evolvability or adaptability in biology. The most innovative groups are diverse. So too are the least innovative groups. The difference is in how much they trust one another and share enough to work together. Because resolving this paradox is difficult, many companies and some countries opt for homogeneity. They may adopt a policy of superficial diversity of sex or skin color, but ultimately they hire according to the strategy of ‘more like me’ because it is easier. They do enough to tick the necessary boxes and avoid embarrassing imbalances in outward-facing situations and effectively practice a form of tokenism. But when we grab the bull by both horns and resolve the paradox through proper structuring, the rewards are massive.
One of Nadella's successful strategies at Microsoft was to turn it into an ecosystem of start-ups. It is the start-up city approach applied to an organization. There is a trade-off between centralization and diffusion. Nadella's change from centralized to diffuse at Microsoft was a way for it to innovate. The United States, too, benefits from its federal structure and lack of strong central authority – each state as a laboratory for innovations in democracy. And the Roman Catholic Church has found the balance between centralization and dissent through regional variation – bishops in each country have a certain degree of autonomy over their parishes and the same is true within the different religious orders.
Of course, not all countries or corporations can take this approach. It requires a certain size to engage in high-risk research and development skunkworks, to take massive business risks or allow for internal division. Smaller companies and countries exist as part of the units taking risks but can benefit from copying and learning successful strategies.
Our species needs the next Industrial Revolution – a true energy revolution. For that, we need a creative explosion. Policies that ensure that information is freely transmitted and that successful outcomes are rewarded without overly punishing failure lest we harm diversity and risk-taking give us the best chance of triggering that creative explosion. One place where it is essential we get it right is where the Second Enlightenment was born: the Internet.