Ideal Warrior and Robot Relations: Stress and Empathy's Role in Human-Robot Teaming

The battlefield of the future will look very different than the battlefields of the past. Automated technologies are finding themselves more and more integrated into every aspect of the fight. As technology continues to advance, the United States Military must consider what a human-machine team will look like and how an optimal relationship between the two assets can be formed, especially under the stressful conditions that often characterize military contexts. For a human-machine team in a military context to work at maximum efficiency, an ideal level of empathy towards an automated teammate must be obtained. The goal of this study is to determine the effect stress can have on an individual's empathetic reaction toward a Pepper robot. Twenty-eight participants interacted with a Pepper robot either under stress or not. Empathy toward the robot was measured through subjective assessments as well as by participant decisions to continue interacting with Pepper even though doing so would harm the robot. Although not conclusive, the results suggest an interaction between participant gender and stress on empathy toward the Pepper robot. Women showed more empathy toward Pepper under higher levels of stress than lower levels of stress. However, the opposite was true for men. Men showed less empathy toward Pepper under higher levels of stress. The results of this study could help to inform military training and robot design.

[1]  Xuan Zhao,et al.  What is Human-like?: Decomposing Robots’ Human-like Appearance Using the Anthropomorphic roBOT (ABOT) Database , 2018, 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[2]  S. Shamay-Tsoory The Neural Bases for Empathy , 2011, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[3]  Mark H. Davis Empathy: A Social Psychological Approach , 1994 .

[4]  Nicole C. Krämer,et al.  Investigations on empathy towards humans and robots using fMRI , 2014, Comput. Hum. Behav..

[5]  Brian T. Gill,et al.  "Robovie, you'll have to go into the closet now": children's social and moral relationships with a humanoid robot. , 2012, Developmental psychology.

[6]  Arindam Dey,et al.  He who hesitates is lost (...in thoughts over a robot) , 2018, APAScience.

[7]  R. N. Spreng,et al.  The Toronto Empathy Questionnaire: Scale Development and Initial Validation of a Factor-Analytic Solution to Multiple Empathy Measures , 2009, Journal of personality assessment.

[8]  Ryan Weber Seeing like a Rover: How Robots, Teams, and Images Craft Knowledge of Mars , 2018, Technical Communication Quarterly.

[9]  Katsumi Watanabe,et al.  FFAB—The Form Function Attribution Bias in Human–Robot Interaction , 2018, IEEE Transactions on Cognitive and Developmental Systems.

[10]  C. Windischberger,et al.  Increased neural responses to empathy for pain might explain how acute stress increases prosociality , 2016, Social cognitive and affective neuroscience.

[11]  Cynthia Breazeal,et al.  Empathic concern and the effect of stories in human-robot interaction , 2015, 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).

[12]  Chad Tossell,et al.  Band of Brothers and Bolts: Caring About Your Robot Teammate , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[13]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[14]  Florian Jentsch,et al.  From Tools to Teammates , 2011 .

[15]  Julie Carpenter Culture and Human-Robot Interaction in Militarized Spaces: A War Story , 2016 .