Towards Dual Processing of Social Robots: Differences in the Automatic and Reflective System

Social robots increasingly diffuse into our lives in work, health, and many other areas. However, theoretical approaches that explain how social robots should be designed to maximize experiential and performance-related outcomes in human-robot interaction (HRI) are still rare. To close this research gap, we aim to develop a dual process model of HRI with the help of two experiments. Results of the first experiment show that individuals categorize humans and robots differently in the automatic and reflective system, leading to different forms of robotic biases in these systems. Specifically, whereas humans show a bias against all types of robots in the reflective system, they only show biases against robots with low anthropomorphism in the automatic system. With the second experiment, we aim to complement these results from a neurophysiological perspective to gain more insights into cognitive processes during classification and evaluation of robots