Doing Right by Not Doing Wrong in Human-Robot Collaboration
- URL: http://arxiv.org/abs/2202.02654v1
- Date: Sat, 5 Feb 2022 23:05:10 GMT
- Title: Doing Right by Not Doing Wrong in Human-Robot Collaboration
- Authors: Laura Londo\~no, Adrian R\"ofer, Tim Welschehold, Abhinav Valada
- Abstract summary: We propose a novel approach to learning fair and sociable behavior, not by reproducing positive behavior, but rather by avoiding negative behavior.
In this study, we highlight the importance of incorporating sociability in robot manipulation, as well as the need to consider fairness in human-robot interactions.
- Score: 8.078753289996417
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: As robotic systems become more and more capable of assisting humans in their
everyday lives, we must consider the opportunities for these artificial agents
to make their human collaborators feel unsafe or to treat them unfairly. Robots
can exhibit antisocial behavior causing physical harm to people or reproduce
unfair behavior replicating and even amplifying historical and societal biases
which are detrimental to humans they interact with. In this paper, we discuss
these issues considering sociable robotic manipulation and fair robotic
decision making. We propose a novel approach to learning fair and sociable
behavior, not by reproducing positive behavior, but rather by avoiding negative
behavior. In this study, we highlight the importance of incorporating
sociability in robot manipulation, as well as the need to consider fairness in
human-robot interactions.
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