Implicit Attitudes Towards Robots Predict Explicit Attitudes, Semantic Distance Between Robots and Humans, Anthropomorphism, and Prosocial Behavior: From Attitudes to Human–Robot Interaction

AbstractHow people behave towards others relies, to a large extent, on the prior attitudes that they hold towards them. In Human–Robot Interactions, individual attitudes towards robots have mostly been investigated via explicit reports that can be biased by various conscious processes. In the present study, we introduce an implicit measure of attitudes towards robots. The task utilizes the measure of semantic priming to evaluate whether participants consider humans and robots as similar or different. Our results demonstrate a link between implicit semantic distance between humans and robots and explicit attitudes towards robots, explicit semantic distance between robots and humans, perceived robot anthropomorphism, and pro/anti-social behavior towards a robot in a real life, interactive scenario. Specifically, attenuated semantic distance between humans and robots in the implicit task predicted more positive explicit attitudes towards robots, attenuated explicit semantic distance between humans and robots, attribution of an anthropomorphic characteristic, and consequently a future prosocial behavior towards a robot. Crucially, the implicit measure of attitudes towards robots (implicit semantic distance) was a better predictor of a future behavior towards the robot than explicit measure of attitudes towards robots (self-reported attitudes). Cumulatively, the current results emphasize a new approach to measure implicit attitudes towards robots, and offer a starting point for further investigations of implicit processing of robots

Why Real Citizens Would Turn to Artificial Leaders

Governments are increasingly using artificial intelligence to improve workflows and services. Applications range from predicting climate change, crime, and earthquakes to flu outbreaks, low air quality, and tax fraud. Artificial agents are already having an impact on eldercare, education, and open government, enabling users to complete procedures through a conversational interface. Whether replacing humans or assisting them, they are the technological fix of our times. In two experiments and a follow-up study, we investigate factors that influence the acceptance of artificial agents in positions of power, using attachment theory and disappointment theory as explanatory models. We found that when the state of the world provokes anxiety, citizens perceive artificial agents as a reliable proxy to replace human leaders. Moreover, people accept artificial agents as decision-makers in politics and security more willingly when they deem their leaders or government to be untrustworthy, disappointing, or immoral. Finally, we discuss these results with respect to theories of technology acceptance and the delegation of duties and prerogatives

A mouse-tracking study of the composite nature of the Stroop effect at the level of response execution.

By forcing selection into response execution processes, the present mouse-tracking study investigated whether the ongoing process of response selection in the colour-word Stroop task is influenced by conflict and facilitation at both the level of response and stimulus. Mouse-tracking measures including partial errors provided credible evidence that both response and semantic conflict (i.e., distinct constituents of interference) contribute to the overall Stroop interference effect even after a response has been initiated. This contribution was also observed for the overall facilitation effect (that was credibly decomposed into response and semantic components in response times but not in mouse deviation measures). These results run counter to the dominant single-stage response competition models that currently fail to explain: 1) the expression of Stroop effects in measures of response execution and; 2) the composite nature of both interference and facilitation. By showing that Stroop effects-originating from multiple levels of processing-can cascade into movement parameters, the present study revealed the potential overlap between selection and execution process. It therefore calls for further theoretical efforts to account for when, where and under what conditions Stroop effects originating from different loci are controlled

National Stereotypes and Robots' Perception: The “Made in” Effect

In the near future, the human social environment worldwide might be populated by humanoid robots. The way we perceive these new social agents could depend on basic social psychological processes such as social categorization. Recent results indicate that humans can make use of social stereotypes when faced with robots based on their characterization as “male” or “female” and a perception of their group membership. However, the question of the application of nationality-based stereotypes to robots has not yet been studied. Given that humans attribute different levels of warmth and competence (the two universal dimensions of social perception) to individuals based in part on their nationality, we hypothesized that the way robots are perceived differs depending on their country of origin. In this study, participants had to evaluate four robots differing in their anthropomorphic shape. For each participant, these robots were presented as coming from one of four different countries selected for their level of perceived warmth and competence. Each robot was evaluated on their anthropomorphic and human traits. As expected, the country of origin's warmth and competence level biased the perception of robots in terms of the attribution of social and human traits. Our findings also indicated that these effects differed according to the extent to which the robots were anthropomorphically shaped. We discuss these results in relation to the way in which social constructs are applied to robots