Tag: Cooperation

The High Price of Mistrust

Reading Time: 10 minutes

When we can’t trust each other, nothing works. As we participate in our communities less and less, we find it harder to feel other people are trustworthy. But if we can bring back a sense of trust in the people around us, the rewards are incredible.

There are costs to falling community participation. Rather than simply lamenting the loss of a past golden era (as people have done in every era), Harvard political scientist Robert D. Putnam explains these costs, as well as how we might bring community participation back.

First published twenty years ago, Bowling Alone is an exhaustive, hefty work. In its 544 pages, Putnam negotiated mountains of data to support his thesis that the previous few decades had seen Americans retreat en masse from public life. Putnam argued Americans had become disconnected from their wider communities, as evidenced by changes such as a decline in civic engagement and dwindling membership rates for groups such as bowling leagues and PTAs.

Though aspects of Bowling Alone are a little dated today (“computer-mediated communication” isn’t a phrase you’re likely to have heard recently), a quick glance at 2021’s social landscape would suggest many of the trends Putnam described have only continued and apply in other parts of the world too.

Right now, polarization and social distancing have forced us apart from any sense of community to a degree that can seem irresolvable.

Will we ever bowl in leagues alongside near strangers and turn them into friends again? Will we ever bowl again at all, even if alone, or will those gleaming aisles, too-tight shoes, and overpriced sodas fade into a distant memory we recount to our children?

The idea of going into a public space for a non-essential reason can feel incredibly out of reach for many of us right now. And who knows how spaces like bowling alleys will survive in the long run without the social scenes that fuelled them. Now is a perfect time to revisit Bowling Alone to see what it can still teach us, because many of its warnings and lessons are perhaps more relevant now than at its time of publication.

One key lesson we can derive from Bowling Alone is that the less we trust each other—something which is both a cause and consequence of declining community engagement—the more it costs us. Mistrust is expensive.

We need to trust the people around us in order to live happy, productive lives. If we don’t trust them, we end up having to find costly ways to formalize our relationships. Even if we’re not engaged with other people on a social or civic level, we still have to transact with them on an economic one. We still have to walk along the same streets, send our children to the same schools, and spend afternoons in the same parks.

To live our lives freely, we need to to find ways to trust that other people won‘t hurt us, rip us off, or otherwise harm us. Otherwise we may lose something too precious to put a price tag on.

***

No person is an island

As community engagement declines, Putnam refers to the thing we are losing as “social capital,” meaning the sum of our connections with other individuals and the benefits they bring us.

Being part of a social network gives you access to all sorts of value. Putnam explains, “Just as a screwdriver (physical capital) or a college education (human capital) can increase productivity (both individual and collective), so too can social contacts affect the productivity of individuals and groups.” For example, knowing the right people can help you find a job where your skills are well utilized. If you don’t know many people, you might struggle to find work and end up doing something you’re overqualified for or be unemployed for a while.

To give another example, if you’re friends with other parents in your local neighborhood, you can coordinate with them to share childcare responsibilities. If you’re not, you’re likely to end up paying for childcare or being more limited in what you can do when your kids are home from school.

Both individuals and groups have social capital. Putnam also explains that “social capital also can have externalities that affect the wider community, so that not all of the costs and benefits of social connections accrue to the person making the contact . . . even a poorly connected individual may derive some of the spillover benefits from living in a well-connected community.” A well-connected community is usually a safer community, and the safety extends, at least partly, to the least connected members.

For example, the more neighbors know each other, the more they notice when something on the street is out of the norm and potentially harmful. That observation benefits everyone on the street—especially the most vulnerable people.

Having social capital is valuable because it undergirds certain norms. Our connections to other people require and encourage us to behave in ways that maintain those connections. Being well-connected is both an outcome of following social norms and an incentive to follow them. We adhere to “rules of conduct” for the sake of our social capital.

Social capital enables us to trust other people. When we’re connected to many others, we develop a norm of “generalized reciprocity.” Putnam explains this as meaning “I’ll do this for you without expecting anything specific back from you, in the confident expectation that someone else will do something for me down the road.” We can go for the delayed payoff that comes from being nice without an agenda. Generalized reciprocity makes all of our interactions with other people easier. It’s a form of trust.

Putnam goes on to write, “A society characterized by generalized reciprocity is more efficient than a distrustful society, for the same reason that money is more efficient than barter. If we don’t have to balance every exchange instantly, we can get a lot more accomplished. Trustworthiness lubricates social life.” Trust requires that we interact with the same people more than once, or at least think that we might.

Generalized reciprocity as a norm also enables us to work together to do things that benefit the whole group or even that don’t benefit us personally at all, rather than focusing on ourselves. If you live in a neighborhood with a norm of generalized reciprocity, you can do things like mowing a neighbor’s lawn for free because you know that when you need similar help, someone will come through. You can do things that wouldn’t make sense in an “every person for themselves” area.

Societies and groups with a norm of generalized reciprocity maintain that norm through “gossip and other valuable ways of cultivating reputation.”

When people are linked to each other, they know that news will spread if they deviate from norms. If one member of a bowling league cheats and another member notices, they’re likely to discuss it with others, and everyone will know to trust that member a little less. Knowing gossip will spread enables us to trust our perceptions of others, because if something were amiss we would have surely heard about it. It also nudges us towards behaving well—if something is amiss about us, others are sure to hear of that, too.

But with the decline of community participation comes the decline of trust. If you don’t know the people around you, how can you trust them? The more disconnected we are from each other, the less we can rely on each other to be good and nice. Without repeated interactions with the same people, we become suspicious of each other. This suspicion carries heavy costs.

***

Rising transaction costs

In economics, a “transaction cost” refers to the cost of making some sort of trade within a market. Transaction costs are the price we pay in order to exchange value. They’re in addition to the cost of producing or otherwise providing that value.

For example, when you make a credit card purchase in a shop, the shop likely pays a processing fee to the card company. It’s part of the cost of doing business with you. Another cost is that the shop needs people working in it to ensure you pay. They can’t just rely on you popping the right money in the till then leaving.

Putnam explains later in the book that being able to trust people as a result of a norm of generalized reciprocity in our social lives leads to reduced transaction costs. It means we can relax around other people and not be distracted by “worrying whether you got back the right change from the clerk to double-checking that you locked the car door.” We can easily be honest if we know others will do the same.

With the decline of social capital comes rising transaction costs. We can’t rely on other people to treat us as they would like to be treated because we don’t know them and haven’t built the opportunities to engage in reciprocal relationships.

Much like trusting trustworthy people has great benefits, trusting untrustworthy people has enormous costs. No one likes being exploited or ripped off because they assumed good faith in the wrong person.

If we’re uncertain, we default to mistrust. You can see the endpoint of a loss of trust in societies and groups which must rely on the use or threat of force to get anything done because everyone is out to rip off everyone else.

At a certain point, transaction costs can cancel out the benefits of transacting at all. If lending a leaf blower to a neighbor requires a lawyer to set up a contract stipulating the terms of its use, then borrowing it doesn’t save them any money. They might as well hire someone or buy their own.

We don’t try new things when we can’t trust other people. So we have to find additional ways of making transactions work. One way we do this is through “the rule of law—formal contracts, courts, litigation, adjudication, and enforcement by the state.” During the period since the 1970s when Putnam considers social capital to have declined, the ratio of lawyers to other professions increased more than any other profession: “After 1970 the legal profession grew three times faster than the other professions as a whole.”

While we can’t attribute that solely to a decline in social capital, it seems clear that mistrusting each other makes us more likely to prefer to get things in writing. We are “forced to rely increasingly on formal institutions, and above all the law, to accomplish what we used to accomplished through informal networks reinforced by generalized reciprocity—that is, through social capital.”

***

The high price of mistrust

The cost of mistrust doesn’t just show up in the form of bills from lawyers. It poisons everything we do and further drives us apart.

Mistrust drives us to install remote monitoring software on our employees’ laptops and ask them to fill in reports on every tiny task to prove they’re not skiving off. It drives us to make excuses when a friend asks for help moving or a lift to the airport because no one was available last time we needed that same help. It drives us to begrudgingly buy a household appliance or tool we’ll only use once because we don’t even consider borrowing it from a neighbor.

Mistrust nudges us to peek at the search history of a partner or to cross-reference what a child says. It causes us to keep our belongings close in public, to double-lock the doors, to not let our kids play in the street, and a million other tiny changes.

Mistrust costs us time and money, sure. But it also costs us a little bit of our humanity. We are sociable animals, and seeing the people around us as a potential threat, even a small one, wears on us. Constant vigilance is exhausting. So is being under constant suspicion.

One lesson we can take from Bowling Alone is that anything we can do to increase trust between people will have tremendous knock-on benefits. Trust allows us to relax, delay gratification, and generally be nicer to everyone. It makes for a nicer day-to-day existence. We don’t need to spend so much time and money checking up on others. Ultimately, it’s worth investing in trust whenever possible, as opposed to investing in more ways of monitoring and controlling people.

That’s not to say that there was ever a golden utopia when everyone trusted everyone. People have always abused the trust of others. And people on the fringes of society have always been unfairly mistrusted and struggled to trust that others would act in good faith. Nonetheless, whenever we go to install some mechanism intended to replace trust, it’s worth asking if there’s a different way.

The ingredients for trust are simple. We need to repeatedly interact with the same people, know that others will warn us about their bad behavior, and feel secure in the knowledge we’ll be helped when and if we need it. At the same time, we need to know others will be warned if we behave badly and that everything we give to others will come back to us, perhaps multiplied.

If you want people to trust you, the best place to start is by trusting them. That isn’t always easy to do, especially if you’ve paid the price for it in the past. But it’s the best place to start. Then you need to combine it with repeat interactions, or the possibility thereof. In the iterated Prisoner’s Dilemma, a game that reveals how cooperation works, the best strategy to adopt is tit for tat. In the first round you cooperate, then in subsequent rounds do whatever the other player did last.

How might that play out in real life? If you want your employees to trust you, then you might start by trusting them—while also making it clear that you’re not going to fire them suddenly and you want them to stick around.

Mistrust is expensive. But trusting the wrong people can sometimes seem too risky. The lesson we can take from Bowling Alone is that building trust is absolutely worthwhile—and that the only way to do it is by finding ways to get out there and engage with other people.

We can create trust by contributing to existing communities and creating new ones. The more we show up and are willing to have faith in others, the more we’ll get back in return.

Tagged: , , , , , ,

Mental Models For a Pandemic

Reading Time: 8 minutes

Mental models help us understand the world better, something which is especially valuable during times of confusion, like a pandemic. Here’s how to apply mental models to gain a more accurate picture of reality and keep a cool head.

***

It feels overwhelming when the world changes rapidly, abruptly, and extensively. The changes come so fast it can be hard to keep up—and the future, which a few months ago seemed reliable, now has so many unknown dimensions. In the face of such uncertainty, mental models are valuable tools for helping you think through significant disruptions such as a pandemic.

A mental model is simply a representation of how something works. They are how we simplify complexity, why we consider some things more relevant than others, and how we reason. Using them increases your clarity of understanding, providing direction for the choices you need to make and the options you want to keep open.

Models for ourselves

During a pandemic, a useful model is “the map is not the territory.” In rapidly changing situations like a global health crisis, any reporting is an incomplete snapshot in time. Our maps are going to be inaccurate for many reasons: limited testing availability, poor reporting, ineffective information sharing, lack of expertise in analyzing the available information. The list goes on.

If past reporting hasn’t been completely accurate, then why would you assume current reporting is? You have to be careful when interpreting the information you receive, using it as a marker to scope out a range of what is happening in the territory.

In our current pandemic, we can easily spot our map issues. There aren’t enough tests available in most countries. Because COVID-19 isn’t fatal for the majority of people who contract it, there are likely many people who get it but don’t meet the testing criteria. Therefore, we don’t know how many people have it.

When we look at country-level reporting, we can also see not all countries are reporting to the same standard. Sometimes this isn’t a matter of “better” or “worse”; there are just different ways of collating the numbers. Some countries don’t have the infrastructure for widespread data collection and sharing. Different countries also have different standards for what counts as a death caused by COVID-19.

In other nations, incentives affect reporting. Some countries downplay their infection rate so as to not create panic. Some governments avoid reporting because it undermines their political interests. Others are more worried about the information on the economic map than the health one.

Although it is important to be realistic about our maps, it doesn’t mean we shouldn’t seek to improve their quality. Paying attention to information from experts and ignoring unverified soundbites is one step to increasing the accuracy of our maps. The more accurate we can get them, the more likely it is that we’ll be able to unlock new possibilities that help us deal with the crisis and plan for the future.

There are two models that we can use to improve the effectiveness of the maps we do have: “compounding” and “probabilistic thinking.”

Compounding is exponential growth, something a lot of us tend to have a poor intuitive grasp on. We see the immediate linear relationships in the situation, like how one test diagnoses one person, while not understanding the compounding effects of that relationship. Increased testing can lead to an exponential decrease in virus transmission because each infected person usually passes the virus onto more than just one other person.

One of the clearest stories to illustrate exponential growth is the story of the man who asked to be paid in rice. In this story, a servant is to be rewarded for his service. When asked how he wanted to be paid, he asks to be paid in rice, using a chessboard to determine the final amount. Starting with one grain, the amount of rice is to be doubled for each square. One grain on the first square looks pathetic. But halfway through the chessboard, the servant is making a good yearly living. And after doubling the rice sixty-four times, the servant is owed more rice than the whole world can produce.

Improving our ability to think exponentially helps us understand how more testing can lead to both an exponential decrease in testing prices and an exponential increase in the production of those tests. It also makes clear just how far-reaching the impact of our actions can be if we don’t take precautions with the assumption that we could be infected.

Probabilistic thinking is also invaluable in helping us make decisions based on the incomplete information we have. In the absence of enough testing, for example, we need to use probabilistic thinking to make decisions on what actions to pursue. We ask ourselves questions like: Do I have COVID-19? If there’s a 1% chance I have it, is it worth visiting my grandparents?

Being able to evaluate reasonable probability has huge impacts on how we approach physical distancing. Combining the models of probabilistic thinking and map is not the territory suggests our actions need to be guided by infection numbers much higher than the ones we have. We are likely to make significantly different social decisions if we estimate the probability of infection as being three people out of ten instead of one person out of one thousand.

Bayesian updating can also help clarify the physical distancing actions you should take. There’s a small probability of being part of a horrendous chain of events that might not just have poor direct consequences but also follow you for the rest of your life. Evaluating how responsible you are being in terms of limiting transmission, would you bet a loved one’s life on it?

Which leads us to Hanlon’s Razor. It’s hard not to get angry at reports of beach parties during spring break or at the guy four doors down who has his friends over to hang out every night. For your own sanity, try using Hanlon’s Razor to evaluate their behavior. They are not being malicious and trying to kill people. They are just exceptionally and tragically ignorant.

Finally, on a day-to-day basis, trying to make small decisions with incomplete information, you can use inversion. You can look at the problem backwards. When the best way forward is far from clear, you ask yourself what you could do to make things worse, and then avoid doing those things.

Models for society

Applying mental models aids in the understanding the dynamics of the large-scale social response.

Currently we are seeing the counterintuitive measures with first-order negatives (closing businesses) but second- and third-order positives (reduced transmission, less stress on the healthcare system). Second-order thinking is an invaluable tool at all times, including during a pandemic. It’s so important that we encourage the thinking, analysis, and decision-making that factors in the effects of the effects of the decisions we make.

In order to improve the maps that our leaders have to make decisions, we need to sort through the feedback loops providing the content. If we can improve not only the feedback but also the pace of iterations, we have a better chance of making good decisions.

For example, if we improve the rate of testing and the speed of the results, it would be a major game-changer. Imagine if knowing whether you had the virus or not was a $0.01 test that gave you a result in less than a minute. In that case, we could make different decisions about social openness, even in the absence of a vaccine (however, this may have invasive privacy implications, as tracking this would be quite difficult otherwise).

As we watch the pandemic and its consequences unfold, it becomes clear that leadership and authority are not the same thing. Our hierarchical instincts emerge strongly in times of crisis. Leadership vacuums, then, are devastating, and disasters expose the cracks in our hierarchies. However, we also see that people can display strong leadership without needing any authority. A pandemic provides opportunities for such leadership to emerge at community and local levels, providing alternate pathways for meeting the needs of many.

One critical model we can use to look at society during a pandemic is Ecosystems. When we think about ecosystems, we might imagine a variety of organisms interacting in a forest or the ocean. But our cities are also ecosystems, as is the earth as a whole. Understanding system dynamics can give us a lot of insight into what is happening in our societies, both at the micro and macro level.

One property of ecosystems that is useful to contemplate in situations like a pandemic is resilience—the speed at which an ecosystem recovers after a disturbance. There are many factors that contribute to resilience, such as diversity and adaptability. Looking at our global situation, one factor threatening to undermine our collective resilience is that our economy has rewarded razor-thin efficiency in the recent past. The problem with thin margins is they offer no buffer in the face of disruption. Therefore, ecosystems with thin margins are not at all resilient. Small disturbances can bring them down completely. And a pandemic is not a small disturbance.

Some argue that what we are facing now is a Black Swan: an unpredictable event beyond normal expectations with severe consequences. Most businesses are not ready to face one. You could argue that an economic recession is not a black swan, but the particular shape of this pandemic is testing the resiliency of our social and economic ecosystems regardless. The closing of shops and business, causing huge disruption, has exposed fragile supply chains. We just don’t see these types of events often enough, even if we know they’re theoretically possible. So we don’t prepare for them. We don’t or can’t create big enough personal and social margins of safety. Individuals and businesses don’t have enough money in the bank. We don’t have enough medical facilities and supplies. Instead, we have optimized for a narrow range of possibilities, compromising the resilience of systems we rely on.

Finally, as we look at the role national borders are playing during this pandemic, we can use the Thermodynamics model to gain insight into how to manage flows of people during and after restrictions. Insulation requires a lot of work, as we are seeing with our borders and the subsequent effect on our economies. It’s unsustainable for long periods of time. Just like how two objects of different temperatures that come into contact with each other eventually reach thermal equilibrium, people will mix with each other. All borders have openings of some sort. It’s important to extend planning to incorporate the realistic tendencies of reintegration.

Some final thoughts about the future

As we look for opportunities about how to move forward both as individuals and societies, Cooperation provides a useful lens. Possibly more critical to evolution than competition, cooperation is a powerful force. It’s rampant throughout the biological world; even bacteria cooperate. As a species, we have been cooperating with each other for a long time. All of us have given up some independence for access to resources provided by others.

Pandemics are intensified because of connection. But we can use that same connectivity to mitigate some negative effects by leveraging our community networks to create cooperative interactions that fill gaps in the government response. We can also use the cooperation lens to create more resilient connections in the future.

Finally, we need to ask ourselves how we can improve our antifragility. How can we get to a place where we grow stronger through change and challenge? It’s not about getting “back to normal.” The normal that was our world in 2019 has proven to be fragile. We shouldn’t want to get back to a time when we were unprepared and vulnerable.

Existential threats are a reality of life on earth. One of the best lessons we can learn is to open our eyes and integrate planning for massive change into how we approach our lives. This will not be the last pandemic, no matter how careful we are. The goal now should not be about assigning blame or succumbing to hindsight bias to try to implement rules designed to prevent a similar situation in the future. We will be better off if we make changes aimed at increasing our resilience and embracing the benefits of challenge.

Still curious? Learn more by reading The Great Mental Models.

Tagged: , , , , , ,

Competition, Cooperation, and the Selfish Gene

Reading Time: 6 minutes

Richard Dawkins has one of the best-selling books of all time for a serious piece of scientific writing.

Often labeled “pop science”, The Selfish Gene pulls together the “gene-centered” view of evolution: It is not really individuals being selected for in the competition for life, but their genes. The individual bodies (phenotypes) are simply carrying out the instructions of the genes. This leads most people to a very “competition focused” view of life. But is that all?

***

More than 100 years before The Selfish Gene, Charles Darwin had famously outlined his Theory of Natural Selection in The Origin of Species.

We’re all hopefully familiar with this concept: Species evolve over long periods time through a process of heredity, variation, competition, and differential survival.

The mechanism of heredity was invisible to Darwin, but a series of scientists, not without a little argument, had figured it out by the 1970’s: Strands of the protein DNA (“genes”) encoded instructions for the building of physical structures. These genes were passed on to offspring in a particular way – the process of heredity. Advantageous genes were propagated in greater numbers. Disadvantageous genes, vice versa.

The Selfish Gene makes a particular kind of case: Specific gene variants grow in proportion to a gene pool by, on average, creating advantaged physical bodies and brains. The genes do their work through “phenotypes” – the physical representation of their information. As Helena Cronin would put in her book The Ant and the Peacock, “It is the net selective value of a gene’s phenotypic effect that determines the fate of the gene.”

This take of the evolutionary process became influential because of the range of hard-to-explain behavior that it illuminated.

Why do we see altruistic behavior? Because copies of genes are present throughout a population, not just in single individuals, and altruism can cause great advantages in those gene variants surviving and thriving. (In other words, genes that cause individuals to sacrifice themselves for other copies of those same genes will tend to thrive.)

Why do we see more altruistic behavior among family members? Because they are closely related, and share more genes!

Many problems seemed to be solved here, and the Selfish Gene model became one for all-time, worth having in your head.

However, buried in the logic of the gene-centered view of evolution is a statistical argument. Gene variants rapidly grow in proportion to the rest of the gene pool because they provide survival advantages in the average environment that the gene will experience over its existence. Thus, advantageous genes “selfishly” dominate their environment before long. It’s all about gene competition.

This has led many people, some biologists especially, to view evolution solely through the lens of competition. Unsurprisingly, this also led to some false paradigms about a strictly “dog eat dog” world where unrestricted and ruthless individual competition is deemed “natural”.

But what about cooperation?

***

The complex systems researcher Yaneer Bar-Yam argues that not only is the Selfish Gene a limiting concept biologically and possibly wrong mathematically (too complex to address here, but if you want to read about it, check out these pieces), but that there are more nuanced ways to understand the way competition and cooperation comfortably coexist. Not only that, but Bar-Yam argues that this has implications for optimal team formation.

In his book Making Things Work, Bar-Yam lays out a basic message: Even in the biological world, competition is a limited lens through which to see evolution. There’s always a counterbalance of cooperation.

Counter to the traditional perspective, the basic message of this and the following chapter is that competition and cooperation always coexist. People see them as opposing and incompatible forces. I think that this is a result of an outdated and one-sided understanding of evolution…This is extremely useful in describing nature and society; the basic insight that “what works, works” still holds. It turns out, however, that what works is a combination of competition and cooperation.

Bar-Yam uses the analogy of a sports team which exists in context of a sports league – let’s say the NBA. Through this lens we can see why players, teams, and leagues compete and cooperate. (The obvious analogy is that genes, individuals, and groups compete and cooperate in the biological world.)

In general, when we think about the conflict between cooperation and completion in team sports, we tend to think about the relationships between the players on a team. We care deeply about their willingness to cooperate and we distinguish cooperative “team players” from selfish non-team players, complaining about the latter even when their individual skill is formidable.

The reason we want players to cooperate is so that they can compete better as a team. Cooperation at the level of the individual enables effective competition at the level of the group, and conversely, the competition between teams motivates cooperation between players. There is a constructive relationship between cooperation and competition when they operate at different levels of organization.

The interplay between levels is a kind of evolutionary process where competition at the team level improves the cooperation between players. Just as in biological evolution, in organized team sports there is a process of selection of winners through competition of teams. Over time, the teams will change how they behave; the less successful teams will emulate strategies of teams that are doing well.

At every level then, there is an interplay between cooperation and competition. Players compete for playing time, and yet must be intensively cooperative on the court to compete with other teams. At the next level up, teams compete with each other for victories, and yet must cooperate intensively to sustain a league at all.

They create agreed upon rules, schedule times to play, negotiate television contracts, and so on. This allows the league itself to compete with other leagues for scarce attention from sports fans. And so on, up and down the ladder.

Competition among players, teams, and leagues is certainly a crucial dynamic. But it isn’t all that’s going on: They’re cooperating intensely at every level, because a group of selfish individuals loses to a group of cooperative ones.

And it is the same among biological species. Genes are competing with each other, as are individuals, tribes, and species. Yet at every level, they are also cooperating. The success of the human species is clearly due to its ability to cooperate in large numbers; and yet any student of war can attest to its deadly competitive nature. Similar dynamics are at play with ants, rats, and chimpanzees, among other species of insect and animal. It’s a yin and yang world.

Bar-Yam thinks this has great implications for how to build successful teams.

Teams will improve naturally – in any organization – when they are involved in a competition that is structured to select those teams that are better at cooperation. Winners of a competition become successful models of behavior for less successful teams, who emulate their success by learning their strategies and by selecting and trading team members.

For a business, a society, or any other complex system made up of many individuals, this means that improvement will come when the system’s structure involves a completion that rewards successful groups. The idea here is not a cutthroat competition of teams (or individuals) but a competition with rules that incorporate some cooperative activity with a mutual goal.

The dictum that “politics is the art of marshaling hatreds” would seem to reflect this notion: A non-violent way for competition of cooperative groups for dominance. As would the incentive systems of majorly successful corporations like Nucor and the best hospital systems, like the Mayo Clinic. Even modern business books are picking up on it.

Individual competition is important and drives excellence. Yet, as Bar-Yam points out, it’s ultimately not a complete formula. Having teams compete is more effective: You need to harness competition and cooperation at every level. You want groups pulling together, creating emerging effects where the whole is greater than the sum of the parts (a recurrent theme throughout nature).

You should read his book for more details on both this idea and the concept of complex systems in general. Bar-Yam also elaborated on his sports analogy in a white-paper here. If you’re interested in complex systems, check out this post on frozen accidents. Also, for more on creating better groups, check out how Steve Jobs did it.

Tagged: , , , , , ,

Explore

Browse