Outline of a sensory-motor perspective on intrinsically moral agents
Balkenius, Christian; Canamero, Lola; Parmanets, Philip; Johansson, Birger; Butz, Martin; Olsson, Andreas
Citation: Balkenius , C , Canamero , L , Parmanets , P , Johansson , B , Butz , M & Olsson , A 2016 , ' Outline of a sensory-motor perspective on intrinsically moral agents ' Adaptive Behavior , vol 24 , no. 5 , pp. 306-319 . DOI: 10.1177/1059712316667203
We propose that moral behaviour of artificial agents could (and should) be intrinsically grounded in their own sensory-motor experiences. Such an ability depends critically on seven types of competencies. First, intrinsic morality should be grounded in the internal values of the robot arising from its physiology and embodiment. Second, the moral principles of robots should develop through their interactions with the environment and with other agents. Third, we claim that the dynamics of moral (or social) emotions closely follows that of other non-social emotions used in valuation and decision making. Fourth, we explain how moral emotions can be learned from the observation of others. Fifth, we argue that to assess social interaction, a robot should be able to learn about and understand responsibility and causation. Sixth, we explain how mechanisms that can learn the consequences of actions are necessary for a robot to make moral decisions. Seventh, we describe how the moral evaluation mechanisms outlined can be extended to situations where a robot should understand the goals of others. Finally, we argue that these competencies lay the foundation for robots that can feel guilt, shame and pride, that have compassion and that know how to assign responsibility and blame.
This is the accepted version of the following article: Christian Balkenius, Lola Cañamero, Philip Pärnamets, Birger Johansson, Martin V Butz, and Andreas Olson, ‘Outline of a sensory-motor perspective on intrinsically moral agents’, Adaptive Behaviour, Vol 24(5): 306-319, October 2016, which has been published in final form at DOI: https://doi.org/10.1177/1059712316667203 Published by SAGE ©The Author(s) 2016
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