Presentation Type

Poster

Abstract

Previously, the Implicit Associations Test (IAT) has been used to measure attitudes toward different human variables (i.e. race, religion, age) (Fazio, R. H., & Olson, M. A., 2003). In this present study, we extend this research to examine biases toward robots by assessing the association between humans and robots with negative and positive stimuli. Participants were recruited at a large southeastern university in the U.S. (n = 23, Mage = 19). The IAT was created in the Qualtrics survey engine where it contains 7 tasks. An improved scoring algorithm was used to examine reaction times from tasks 3, 4, 6, and 7 (Greenwald, 2009). Tasks 3 and 4 measured the association between humans with negative stimuli, and robots with positive stimuli. Tasks 6 and 7 measured the association between humans with positive stimuli, and robots with negative stimuli. As the mean gets smaller, the reaction time increases leading to a stronger association. We hypothesized that people may hold stronger negative associations toward robots than toward humans. Therefore, the reaction time for Tasks 3 and 4 will be significantly larger than for Tasks 6 and 7. As predicted, our results indicate a higher mean for Tasks 3 and 4 (M = 1.09, SD = 0.49) compared to the mean for Tasks 6 and 7 (= 0.71, SD = 0.20). By implementing the IAT in the novel field of robotics, useful information about user’s implicit perceptions toward robots may aid in future human robot interaction.

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Using Implicit Associations to Reveal Hidden Biases Toward Robots

Previously, the Implicit Associations Test (IAT) has been used to measure attitudes toward different human variables (i.e. race, religion, age) (Fazio, R. H., & Olson, M. A., 2003). In this present study, we extend this research to examine biases toward robots by assessing the association between humans and robots with negative and positive stimuli. Participants were recruited at a large southeastern university in the U.S. (n = 23, Mage = 19). The IAT was created in the Qualtrics survey engine where it contains 7 tasks. An improved scoring algorithm was used to examine reaction times from tasks 3, 4, 6, and 7 (Greenwald, 2009). Tasks 3 and 4 measured the association between humans with negative stimuli, and robots with positive stimuli. Tasks 6 and 7 measured the association between humans with positive stimuli, and robots with negative stimuli. As the mean gets smaller, the reaction time increases leading to a stronger association. We hypothesized that people may hold stronger negative associations toward robots than toward humans. Therefore, the reaction time for Tasks 3 and 4 will be significantly larger than for Tasks 6 and 7. As predicted, our results indicate a higher mean for Tasks 3 and 4 (M = 1.09, SD = 0.49) compared to the mean for Tasks 6 and 7 (= 0.71, SD = 0.20). By implementing the IAT in the novel field of robotics, useful information about user’s implicit perceptions toward robots may aid in future human robot interaction.

 

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