Nowak and Sigmund regarded Axelrod’s work as an elegant exercise of mathematics but wanted to change the game so that it applied more directly to specific questions in evolution. The classic Darwinian theory of natural selection suggests that individuals who cooperate threaten their own evolutionary fitness, since cooperation always involves a cost to the self (the vampire bat that shares blood has less food for itself). Still, life is full of cooperation, from the single cells that joined to form higher organisms to the construction of cities by humans and intricate communal nests by ants. If cooperation exists so widely, Nowak wondered, what mechanisms were at work to increase cooperation when natural selection seemed to argue against it?
A paper published in Nature in 1976 by Lord Robert May, a British physicist who has made notable contributions to theoretical biology, introduced some new ideas for changing the game and teasing out those mechanisms. May argued that virtual tournaments like Axelrod’s might not accurately replicate the interplay of cooperation and defection in real life. “I pointed out that many of the results from computer modeling depended on [virtual] people deciding on a strategy and following it exactly,” May says. “In reality, there is going to be a lot of noise and error. You need to allow for this.”
In other words, real creatures rarely follow a strategy perfectly. Neighbor Jones usually repays Neighbor Newell’s helpfulness, but if Jones has just had an argument with his wife when he sees Newell coming to ask for help with the flat tire, he may decide he doesn’t want to get his hands dirty. So Nowak and Sigmund set out to create virtual tournaments that allowed for noise and error by conferring probabilistic behavior on the virtual players. Some might defect 80 percent of the time after their partner defected in a previous round; others might cooperate 50 percent of the time even when their previous partner defected. This probabilistic behavior added in the kind of noise that May deemed lacking in pristine models that came before.
To further put the terms of the game into a plausible evolutionary context, Nowak and Sigmund gave winning players and their strategies the power of reproduction. In this new version of the game, the virtual players didn’t just accumulate points when they won; they were rewarded with a duplicate of themselves equipped with the same winning strategy. Their offspring then took the place of another player in the population. The game now mimicked what happens to real organisms: Random mutations resulted in some players having winning strategies that allowed them to triumph and spread those strategies while others died off. After thousands of rounds of the computer playing the game, Nowak and Sigmund would see what kind of strategy for cooperation or defection dominated the population.
As Nowak and Sigmund expected, an approach called Always Defect triumphed for 100 generations. Then it gave way to Tit for Tat for generations, with the two scientists cheering as they watched the gimlet-eyed Always Defectors fizzle out. The game churned on even after Nowak finished his Ph.D. in 1989. He then moved to England to do postdoctoral research with May at the University of Oxford. The first breakthrough in his work with Sigmund happened when Nowak returned to Vienna for a vacation, toting his computer with him. Checking in on his virtual world, he was amazed to see the emergence of a new winning strategy. Later named Generous Tit for Tat, players with this strategy occasionally cooperated, even after the other one had defected.
Nowak saw a huge evolutionary message emerging from these simulations. “What we were seeing was the evolution of forgiveness,” he says. “Generous Tit for Tat suggests that we never forget a good turn, but we occasionally forgive a bad one. It makes a lot of sense. Tit for Tat can create a vendetta, but Generous Tit for Tat allows you to move on.”
As the game continued, Nowak saw that even though Generous Tit for Tat was a long-lived strategy, it didn’t hold sway forever. There were still some Always Defectors that survived, and they were ultimately able to break down the new highly cooperative status quo. A society filled with happy cooperators becomes easy pickings for the selfish, who can tip things back toward dog-eat-dog. But that state, too, will have a few remaining cooperators who eventually tip things back to mass generosity.
We see this pattern all the time in human society. Peace is followed by war, which is followed by peace again. Empires rise and fall. Companies grow, attract the attention of competitors, and lose their market share, but can then reorganize (requiring internal cooperation) and dominate the market again. Every trend of cooperation and defection, it seems, contains the seeds of its opposite. But no matter what happens, Nowak realized that there is always selective pressure toward cooperation.
One day when Nowak was back in Austria, hiking the mountains with Sigmund, they began to talk about cooperation between people who barely knew each other, a behavior called indirect reciprocity. While some experiments have a long and arduous genesis, Nowak in three weeks developed a computer simulation that explained indirect reciprocity. In this game, as in the prisoner’s dilemma, the players either defected or cooperated with each other, but only once—they couldn’t decide how to behave on the basis of previous experience with the other player. But Nowak also added a mechanism by which the players built up a reputation, one that rose or fell according to their history of cooperative behavior. As he expected, the players with good reputations experienced more cooperation than those with bad reputations.
Nowak became convinced that the power of reputation, or indirect reciprocity—being willing to cooperate with someone despite not knowing him personally—is a hugely important factor in human cooperation. And because cooperation has been so important in human development, he concluded that the need to grapple with reputation was a major factor driving the development of language and our powerful brains.
“From very early on, the selection pressure was about social interactions in a group,” Nowak says. “You need to be smart enough to monitor the social interactions in the group, to understand motives and intentions for action. You need to be able to keep it in memory, and you need to be able to talk about it. One theory before this had been that big brains make language possible, but I believe it was the opposite—that the need for language created big brains.”
After nearly two decades of studying the rise of cooperation in populations, Nowak sees the entire world through the prism of the prisoner’s dilemma: He is always looking at the tension between cooperation and defection. In 2006 he had an epiphany of sorts while sitting in a meeting in Japan, jet-lagged from his trip. Working in his head, like the mathematicians at the seminary, he counted five crucial mechanisms that drove cooperation in highly social species like ours.
The first mechanism is Tit for Tat, or direct reciprocity—“I will if you will”—which represented the first outbreak of cooperation in the prisoner’s dilemma simulation.
Next comes the much more advanced mechanism of indirect reciprocity, or reputation, when one individual is willing to help another not because of personal experience but because others have described having good prior encounters with that person.
Nowak identifies the third mechanism as “spatial selection”—interaction born of living in proximity. Within a small area, social networks aid survival and cooperation flowers.
The fourth is multilevel selection, involving larger groups like towns, tribes, or companies. These structures encourage cooperation among their members.
The fifth mechanism is a version of the familiar kin selection, the tendency to cooperate with blood relations. Nowak believes blood ties might play a role—but one defined more by social cooperation than by the propagation of family genes.
Nowak is also open to the possibility of an additional cooperative strategy he has missed. “It would be exciting if we found one. It would make me very happy—I’d have to figure out why it developed and why I missed it. The beauty of all this is how it’s so open-ended,” he says.