Challenges of Transparency for Learning Robots

Mattia Racca, Ville Kyrki

Research output: Contribution to conferencePosterScientificpeer-review


With the importance of transparency for autonomous intelligent systems (AISs) becoming clear to the robotics community, definitions of transparency and guidelines for its implementation have started being proposed. In this paper, we adopt from the literature a model characterizing different aspects of transparency in the light of human-robot interaction and apply it to the specific case of robots learning from humans. Requirements deriving by the specific nature of learning systems are remarked and the main challenges highlighted and discussed.
Original languageEnglish
Number of pages2
Publication statusPublished - 2018
MoE publication typeNot Eligible
EventACM/IEEE International Conference on Human-Robot Interaction - Chicago, United States
Duration: 5 Mar 20188 Mar 2018
Conference number: 13


ConferenceACM/IEEE International Conference on Human-Robot Interaction
Abbreviated titleHRI
CountryUnited States
Internet address


  • autonomous intelligent systems
  • robot learning
  • transparency


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