Most people don't just think the world should be run meritocratically, they think it is meritocratic.
'We are true to our creed when a little girl born into the bleakest poverty knows that she has the same chance to succeed as anybody else …' Barack Obama, inaugural address, 2013
'We must create a level playing field for American companies and workers.' Donald Trump, inaugural address, 2017
Meritocracy has become a leading social ideal. Politicians across the ideological spectrum continually return to the theme that the rewards of life – money, power, jobs, university admission – should be distributed according to skill and effort. The most common metaphor is the "even playing field" upon which players can rise to the position that fits their merit. Conceptually and morally, meritocracy is presented as the opposite of systems such as hereditary aristocracy, in which one's social position is determined by the lottery of birth.
Under meritocracy, wealth and advantage are merit's rightful compensation, not the fortuitous windfall of external events.
Most people don't just think the world should be run meritocratically, they think it is meritocratic. In the U.K., 84 percent of respondents to the 2009 British Social Attitudes survey stated that hard work is either 'essential' or 'very important' when it comes to getting ahead, and in 2016 the Brookings Institute found that 69 percent of Americans believe that people are rewarded for intelligence and skill. Respondents in both countries believe that external factors, such as luck and coming from a wealthy family, are much less important. While these ideas are most pronounced in these two countries, they are popular across the globe.
Although widely held, the belief that merit rather than luck determines success or failure in the world is demonstrably false. This is not least because merit itself is, in large part, the result of luck. Talent and the capacity for determined effort, sometimes called 'grit', depend a great deal on one's genetic endowments and upbringing.
This is to say nothing of the fortuitous circumstances that figure into every success story. In his book Success and Luck (2016), the US economist Robert Frank recounts the long-shots and coincidences that led to Bill Gates's stellar rise as Microsoft's founder, as well as to Frank's own success as an academic. Luck intervenes by granting people merit, and again by furnishing circumstances in which merit can translate into success. This is not to deny the industry and talent of successful people. However, it does demonstrate that the link between merit and outcome is tenuous and indirect at best.
According to Frank, this is especially true where the success in question is great, and where the context in which it is achieved is competitive. There are certainly programmers nearly as skillful as Gates who nonetheless failed to become the richest person on Earth. In competitive contexts, many have merit, but few succeed. What separates the two is luck.
In addition to being false, a growing body of research in psychology and neuroscience suggests that believing in meritocracy makes people more selfish, less self-critical and even more prone to acting in discriminatory ways. Meritocracy is not only wrong; it's bad.
The 'ultimatum game' is an experiment, common in psychological labs, in which one player (the proposer) is given a sum of money and told to propose a division between him and another player (the responder), who may accept the offer or reject it. If the responder rejects the offer, neither player gets anything. The experiment has been replicated thousands of times, and usually the proposer offers a relatively even split. If the amount to be shared is $100, most offers fall between $40–$50.
One variation on this game shows that believing one is more skilled leads to more selfish behaviour. In research at Beijing Normal University, participants played a fake game of skill before making offers in the ultimatum game. Players who were (falsely) led to believe they had 'won' claimed more for themselves than those who did not play the skill game. Other studies confirm this finding. The economists Aldo Rustichini at the University of Minnesota and Alexander Vostroknutov at Maastricht University in the Netherlands found that subjects who first engaged in a game of skill were much less likely to support the redistribution of prizes than those who engaged in games of chance. Just having the idea of skill in mind makes people more tolerant of unequal outcomes. While this was found to be true of all participants, the effect was much more pronounced among the 'winners'.
By contrast, research on gratitude indicates that remembering the role of luck increases generosity. Frank cites a study in which simply asking subjects to recall the external factors (luck, help from others) that had contributed to their successes in life made them much more likely to give to charity than those who were asked to remember the internal factors (effort, skill).
Perhaps more disturbing, simply holding meritocracy as a value seems to promote discriminatory behaviour. The management scholar Emilio Castilla at the Massachusetts Institute of Technology and the sociologist Stephen Benard at Indiana University studied attempts to implement meritocratic practices, such as performance-based compensation in private companies. They found that, in companies that explicitly held meritocracy as a core value, managers assigned greater rewards to male employees over female employees with identical performance evaluations. This preference disappeared where meritocracy was not explicitly adopted as a value.
This is surprising because impartiality is the core of meritocracy's moral appeal. The 'even playing field' is intended to avoid unfair inequalities based on gender, race and the like. Yet Castilla and Benard found that, ironically, attempts to implement meritocracy leads to just the kinds of inequalities that it aims to eliminate. They suggest that this 'paradox of meritocracy' occurs because explicitly adopting meritocracy as a value convinces subjects of their own moral bona fides. Satisfied that they are just, they become less inclined to examine their own behaviour for signs of prejudice.
Meritocracy is a false and not very salutary belief. As with any ideology, part of its draw is that it justifies the status quo, explaining why people belong where they happen to be in the social order. It is a well-established psychological principle that people prefer to believe that the world is just.
However, in addition to legitimation, meritocracy also offers flattery. Where success is determined by merit, each win can be viewed as a reflection of one's own virtue and worth. Meritocracy is the most self-congratulatory of distribution principles. Its ideological alchemy transmutes property into praise, material inequality into personal superiority. It licenses the rich and powerful to view themselves as productive geniuses. While this effect is most spectacular among the elite, nearly any accomplishment can be viewed through meritocratic eyes. Graduating from high school, artistic success or simply having money can all be seen as evidence of talent and effort. By the same token, worldly failures becomes signs of personal defects, providing a reason why those at the bottom of the social hierarchy deserve to remain there.
This is why debates over the extent to which particular individuals are 'self-made' and over the effects of various forms of 'privilege' can get so hot-tempered. These arguments are not just about who gets to have what; it's about how much 'credit' people can take for what they have, about what their successes allow them to believe about their inner qualities. That is why, under the assumption of meritocracy, the very notion that personal success is the result of 'luck' can be insulting. To acknowledge the influence of external factors seems to downplay or deny the existence of individual merit.
Despite the moral assurance and personal flattery that meritocracy offers to the successful, it ought to be abandoned both as a belief about how the world works and as a general social ideal. It's false, and believing in it encourages selfishness, discrimination and indifference to the plight of the unfortunate.
This article was originally published at Aeon and has been republished under Creative Commons.
Meritocracy doesn't work when some people benefit from the system disproportionately.
- When fighting for social justice, there is a difference between equality and equity.
- It's not radical to fight for a world where everyone has the same access to education, has food, and is equal in the eyes of the criminal justice system.
- There is no real meritocracy if some people disproportionately benefit from the system just because of their skin color.
Complex problems undermine the very principle of meritocracy: the idea that the ‘best person’ should be hired. There is no best person.
While in graduate school in mathematics at the University of Wisconsin-Madison, I took a logic course from David Griffeath. The class was fun. Griffeath brought a playfulness and openness to problems. Much to my delight, about a decade later, I ran into him at a conference on traffic models. During a presentation on computational models of traffic jams, his hand went up. I wondered what Griffeath – a mathematical logician – would have to say about traffic jams. He did not disappoint. Without even a hint of excitement in his voice, he said: ‘If you are modelling a traffic jam, you should just keep track of the non-cars.’
The collective response followed the familiar pattern when someone drops an unexpected, but once stated, obvious idea: a puzzled silence, giving way to a roomful of nodding heads and smiles. Nothing else needed to be said.
Griffeath had made a brilliant observation. During a traffic jam, most of the spaces on the road are filled with cars. Modelling each car takes up an enormous amount of memory. Keeping track of the empty spaces instead would use less memory – in fact almost none. Furthermore, the dynamics of the non-cars might be more amenable to analysis.
Versions of this story occur routinely at academic conferences, in research laboratories or policy meetings, within design groups, and in strategic brainstorming sessions. They share three characteristics. First, the problems are complex: they concern high-dimensional contexts that are difficult to explain, engineer, evolve or predict. Second, the breakthrough ideas do not arise by magic, nor are they constructed anew from whole cloth. They take an existing idea, insight, trick or rule, and apply it in a novel way, or they combine ideas – like Apple’s breakthrough repurposing of the touchscreen technology. In Griffeath’s case, he applied a concept from information theory: minimum description length. Fewer words are required to say ‘No-L’ than to list ‘ABCDEFGHIJKMNOPQRSTUVWXYZ’. I should add that these new ideas typically produce modest gains. But, collectively, they can have large effects. Progress occurs as much through sequences of small steps as through giant leaps.
Third, these ideas are birthed in group settings. One person presents her perspective on a problem, describes an approach to finding a solution or identifies a sticking point, and a second person makes a suggestion or knows a workaround. The late computer scientist John Holland commonly asked: ‘Have you thought about this as a Markov process, with a set of states and transition between those states?’ That query would force the presenter to define states. That simple act would often lead to an insight.
The burgeoning of teams – most academic research is now done in teams, as is most investing and even most songwriting (at least for the good songs) – tracks the growing complexity of our world. We used to build roads from A to B. Now we construct transportation infrastructure with environmental, social, economic and political impacts.
The complexity of modern problems often precludes any one person from fully understanding them. Factors contributing to rising obesity levels, for example, include transportation systems and infrastructure, media, convenience foods, changing social norms, human biology and psychological factors. Designing an aircraft carrier, to take another example, requires knowledge of nuclear engineering, naval architecture, metallurgy, hydrodynamics, information systems, military protocols, the exercise of modern warfare and, given the long building time, the ability to predict trends in weapon systems.
The multidimensional or layered character of complex problems also undermines the principle of meritocracy: the idea that the ‘best person’ should be hired. There is no best person. When putting together an oncological research team, a biotech company such as Gilead or Genentech would not construct a multiple-choice test and hire the top scorers, or hire people whose resumes score highest according to some performance criteria. Instead, they would seek diversity. They would build a team of people who bring diverse knowledge bases, tools and analytic skills. That team would more likely than not include mathematicians (though not logicians such as Griffeath). And the mathematicians would likely study dynamical systems and differential equations.
Believers in a meritocracy might grant that teams ought to be diverse but then argue that meritocratic principles should apply within each category. Thus the team should consist of the ‘best’ mathematicians, the ‘best’ oncologists, and the ‘best’ biostatisticians from within the pool.
That position suffers from a similar flaw. Even with a knowledge domain, no test or criteria applied to individuals will produce the best team. Each of these domains possesses such depth and breadth, that no test can exist. Consider the field of neuroscience. Upwards of 50,000 papers were published last year covering various techniques, domains of enquiry and levels of analysis, ranging from molecules and synapses up through networks of neurons. Given that complexity, any attempt to rank a collection of neuroscientists from best to worst, as if they were competitors in the 50-metre butterfly, must fail. What could be true is that given a specific task and the composition of a particular team, one scientist would be more likely to contribute than another. Optimal hiring depends on context. Optimal teams will be diverse.
Evidence for this claim can be seen in the way that papers and patents that combine diverse ideas tend to rank as high-impact. It can also be found in the structure of the so-called random decision forest, a state-of-the-art machine-learning algorithm. Random forests consist of ensembles of decision trees. If classifying pictures, each tree makes a vote: is that a picture of a fox or a dog? A weighted majority rules. Random forests can serve many ends. They can identify bank fraud and diseases, recommend ceiling fans and predict online dating behaviour.
When building a forest, you do not select the best trees as they tend to make similar classifications. You want diversity. Programmers achieve that diversity by training each tree on different data, a technique known as bagging. They also boost the forest ‘cognitively’ by training trees on the hardest cases – those that the current forest gets wrong. This ensures even more diversity and accurate forests.
Yet the fallacy of meritocracy persists. Corporations, non-profits, governments, universities and even preschools test, score and hire the ‘best’. This all but guarantees not creating the best team. Ranking people by common criteria produces homogeneity. And when biases creep in, it results in people who look like those making the decisions. That’s not likely to lead to breakthroughs. As Astro Teller, CEO of X, the ‘moonshoot factory’ at Alphabet, Google’s parent company, has said: ‘Having people who have different mental perspectives is what’s important. If you want to explore things you haven’t explored, having people who look just like you and think just like you is not the best way.’ We must see the forest.
Scott E Page
This article was originally published at Aeon and has been republished under Creative Commons.
Look at Wall Street in 2008, and the White House right now. Diversity—of people and cognitive perspectives—is crucial for avoiding failure.
We need to rethink our diversity strategy, says Sallie Krawcheck. What we've been trying for the last decade hasn't been working, but what exactly is the problem? Research reveals that diversity is actually worse in meritocracies. Managers—and particularly middle managers, Krawcheck points out—fall into the cognitive trap of hiring people who "remind me of a young me" (i.e. look like them and think like them) instead of more cognitively diverse people who would bring a missing skill set to a team. This is as important now, under the almost all-white male Trump administration, as it was in the 2008 Financial Crash. Wall Street is one of the most homogenous institutions in America, and Krawcheck has no doubt that having a more diverse set of minds in finance would have lessened the severity of the global crash. In addition, risk-taking and the poor decision making that results can be tracked to fluctuations in one hormone: testosterone. Whether it's the housing bubble, America's healthcare, or foreign policy, these are mistakes that affect millions of lives. As a CEO, Krawcheck's approach and advice on diversity is changing. The current strategy has been a failure, but what if companies paid their managers, in part, based on the diversity of their hires? What if we thought of diversity as more important than meritocracy? Sallie Krawcheck is the author of Own It: The Power of Women at Work.