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.
Consider some experiments from my lab at Yale, where my colleagues and I have been exploring how such effects might play out. In one, we directed small groups of people to work with humanoid robots to lay railroad tracks in a virtual world. Each group consisted of three people and a little blue-and-white robot sitting around a square table, working on tablets. The robot was programmed to make occasional errors—and to acknowledge them: “Sorry, guys, I made the mistake this round,” it declared perkily. “I know it may be hard to believe, but robots make mistakes too.”
As it turned out, this clumsy, confessional robot helped the groups perform better—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.