Fears about how robots might transform our lives have been a staple of science fiction for decades.  In the 1940s, when widespread interaction between humans and artificial intelligence still seemed a distant prospect, Isaac Asimov posited his famous Three Laws of Robotics, which were intended to keep robots from hurting us.  The first—“a robot may not injure a human being or, through inaction, allow a human being to come to harm”—followed from the understanding that robots would affect humans via direct interaction, for good and for ill.  Think of classic sci-fi depictions: C-3PO and R2-D2 working with the Rebel Alliance to thwart the Empire in Star Wars , say, or HAL 9000 from 2001: A Space Odyssey and Ava from Ex Machina plotting to murder their ostensible masters.  But these imaginings were not focused on AI’s broader and potentially more significant social effects—the ways AI could affect how we humans interact with one another. 

As it turned out, this clumsy, confessional robot helped the groups perform—by improving communication among the humans.  They became more relaxed and conversational, consoling group members who stumbled and laughing together more often.  Compared with the control groups, whose robot made only bland statements, the groups with a confessional robot were better able to collaborate. In another, virtual experiment, we divided 4,000 human subjects into groups of about 20, and assigned each individual “friends” within the group; these friendships formed a social network.  The groups were then assigned a task: Each person had to choose one of three colors, but no individual’s color could match that of his or her assigned friends within the social network.  Unknown to the subjects, some groups contained a few bots that were programmed to occasionally make mistakes.  Humans who were directly connected to these bots grew more flexible, and tended to avoid getting stuck in a solution that might work for a given individual but not for the group as a whole.  What’s more, the resulting flexibility spread throughout the network, reaching even people who were not directly connected to the bots.  As a consequence, groups with mistake-prone bots consistently outperformed groups containing bots that did not make mistakes.  The bots helped the humans to help themselves. Both of these studies demonstrate that in what I call “hybrid systems”—where people and robots interact socially—the right kind of AI can improve the way humans relate to one another.  Other findings reinforce this.  For instance, the political scientist Kevin Munger directed specific kinds of bots to intervene after people sent racist invective to other people online.  He showed that, under certain circumstances, a bot that simply reminded the perpetrators that their target was a human being, one whose feelings might get hurt, could cause that person’s use of racist speech to decline for more than a month. 

As consequential as these innovations were, however, they did not change the fundamental aspects of human behavior that comprise what I call the “social suite”: a crucial set of capacities we have evolved over hundreds of thousands of years, including love, friendship, cooperation, and teaching.  The basic contours of these traits remain remarkably consistent throughout the world, regardless of whether a population is urban or rural, and whether or not it uses modern technology. But adding artificial intelligence to our midst could be much more disruptive.  Especially as machines are made to look and act like us and to insinuate themselves deeply into our lives, they may change how loving or friendly or kind we are—not just in our direct interactions with the machines in question, but in our interactions with one another. 

But adding AI to our social environment can also make us behave less productively and less ethically.  In yet another experiment, this one designed to explore how AI might affect the “tragedy of the commons”—the notion that individuals’ self-centered actions may collectively damage their common interests—we gave several thousand subjects money to use over multiple rounds of an online game.  In each round, subjects were told that they could either keep their money or donate some or all of it to their neighbors.  If they made a donation, we would match it, doubling the money their neighbors received.  Early in the game, two-thirds of players acted altruistically.  After all, they realized that being generous to their neighbors in one round might prompt their neighbors to be generous to them in the next one, establishing a norm of reciprocity.  From a selfish and short-term point of view, however, the best outcome would be to keep your own moneyreceive money from your neighbors.  In this experiment, we found that by adding just a few bots (posing as human players) that behaved in a selfish, free-riding way, we could drive the group to behave similarly.  Eventually, the human players ceased cooperating altogether.  The bots thus converted a group of generous people into selfish jerks. Let’s pause to contemplate the implications of this finding.  Cooperation is a key feature of our species, essential for social life.  And trust and generosity are crucial in differentiating successful groups from unsuccessful ones.  If everyone pitches in and sacrifices in order to help the group, everyone should benefit.  When this behavior breaks down, however, the very notion of a public good disappears, and everyone suffers.  The fact that AI might meaningfully reduce our ability to work together is extremely concerning.