Social Preferences Towards Machines and Humans

There is growing interest in the field of Cooperative AI, hence settings where humans and machines cooperate with each other. By now more than 160 studies from various disciplines have studied how people cooperate with machines in behavioral experiments. Our systematic review of the instructions of these studies reveals that the implementation of the machine payoffs and the information participants receive about it differs drastically across these studies. In an online experiment, we systematically compare how these different payoff implementations shape people's social preferences toward machines. When matched with machine partners, people reveal substantially higher social preferences when they know that human beneficiaries receive the machine payoffs compared to when they know that no such “human behind the machine” exist. Not informing people about the machine payoffs leads to low social preferences as people form beliefs about the payoffs in a self-favoring way. Our results thus indicate that the degree to which humans cooperate with machines depends on the implementation and information about the machine's earnings