This research investigates adults' understanding of differences in the basic nature of intelligence exhibited by humans and by machines such as computers and robots. We tested these intuitions by asking participants to make predictions about the behaviors of different entities in situations where actions could be based on either goal-directed intentional thought or more mechanical nonintentional thought. Across several studies, adults made more intentional predictions about the behavior of humans than about the behavior of robots or computers. Although initial experiments demonstrated that participants made very similar predictions for computers and anthropomorphic robots, when asked to track robots' attention to objects, participants began to predict more intentional behaviors for the robot. A multiple regression demonstrated that differential behavioral predictions about mechanical and human entities were associated with ratings of goal understanding but not overall intelligence of current computers/rob...

In previous research, we demonstrated that people distinguish between human and nonhuman intelligence by assuming that humans are more likely to engage in intentional goal-directed behaviors than computers or robots. In the present study, we tested whether participants who respond relatively quickly when making predictions about an entity are more or less likely to distinguish between human and nonhuman agents on the dimension of intentionality. Participants responded to a series of five scenarios in which they chose between intentional and nonintentional actions for a human, a computer, and a robot. Results indicated that participants who chose quickly were more likely to distinguish human and nonhuman agents than participants who deliberated more over their responses. We suggest that the short-RT participants were employing a first-line default to distinguish between human intentionality and more mechanical nonhuman behavior, and that the slower, more deliberative participants engaged in deeper second-line reasoning that led them to change their predictions for the behavior of a human agent.

We have previously demonstrated that people apply fundamentally different concepts to mechanical agents and human agents, assuming that mechanical agents engage in more location-based, and feature-based behaviors whereas humans engage in more goal-based, and category-based behavior. We also found that attributions about anthropomorphic agents such as robots are very similar to those about computers, unless subjects are asked to attend closely to specific intentional-appearing behaviors. In the present studies, we ask whether subjects initially do not attribute intentionality to robots because they believe that temporary limits in current technology preclude real intelligent behavior. In addition, we ask whether a basic categorization as an artifact affords lessened attributions of intentionality. We find that subjects assume that robots created with future technology may become more intentional, but will not be fully equivalent to humans, and that even a fully human-controlled robot will not be as intentional as a human. These results suggest that subjects strongly distinguish intelligent agents based on intentionality, and that the basic living/mechanical distinction is powerful enough, even in adults, to make it difficult for adults to assent to the possibility that mechanical things can be fully intentional.