Mind-Reading Machines: Distinct User Responses to Thought-Detecting and Emotion-Detecting Robots

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Abstract

Human-like robots and other systems with artificial intelligence are increasingly capable of recognizing and interpreting the mental processes of their human users. The present research examines how people evaluate these seemingly mind-reading machines based on the well-established distinction of human mind into agency (i.e., thoughts and plans) and experience (i.e., emotions and desires). Theory and research that applied this distinction to human–robot interaction showed that machines with experience were accepted less and were perceived to be eerier than those with agency. Considering that humans are not yet used to having their thoughts read by other entities and might feel uneasy about this notion, we proposed that thought-detecting robots are perceived to be eerier and are generally evaluated more negatively than emotion-detecting robots. Across two pre-registered experiments (N1 = 335, N2 = 536) based on text vignettes about different kinds of mind-detecting robots, we find support for our hypothesis. Furthermore, the effect remained independent of the six HEXACO personality dimensions, except for an unexpected interaction with conscientiousness. Implications and directions for future research are discussed.

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Grundke, A., Stein, J. P., & Appel, M. (2022). Mind-Reading Machines: Distinct User Responses to Thought-Detecting and Emotion-Detecting Robots. Technology, Mind, and Behavior, 3(1). https://doi.org/10.1037/tmb0000053

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