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Unpredictable robots elicit responsibility attributions.

Matija Franklin1, Edmond Awad2, Hal Ashton3

  • 1Experimental Psychology Department, University College London, London WC1E 6BT, UK matija.franklin@ucl.ac.uk; https://www.ucl.ac.uk/pals/research/experimental-psychology/person/matija-franklin/ d.lagnado@ucl.ac.uk; https://www.ucl.ac.uk/pals/research/experimental-psychology/person/david-lagnado/.

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People may hold robots responsible for unexpected actions. This research suggests current frameworks for robot interpretation overlook user accountability assignment in specific unpredictable scenarios.

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Area of Science:

  • Human-Robot Interaction
  • Social Robotics
  • Moral Psychology

Background:

  • Existing frameworks for interpreting social robots, like Clark and Fischer's, offer valuable insights.
  • However, these models may not fully capture the nuances of human attributions of responsibility to robots.

Purpose of the Study:

  • To investigate the extent to which people assign responsibility to robots.
  • To identify contexts where responsibility assignment to robots occurs, particularly when actions are unpredictable.

Main Methods:

  • Analysis of existing theoretical frameworks on robot interpretation.
  • Argumentation based on specific contextual factors influencing responsibility assignment.

Main Results:

  • Current frameworks inadequately explain people's willingness to assign responsibility to robots.
  • Responsibility is more likely assigned when robot actions deviate from user or programmer expectations.

Conclusions:

  • Human-robot interaction involves complex attributions of responsibility.
  • Future frameworks should incorporate the impact of unpredictability on assigning agency and accountability to robots.