22. – 26. April 2019, Dagstuhl-Seminar 19171

Ethics and Trust: Principles, Verification and Validation


Michael Fisher (University of Liverpool, GB)
Christian List (London School of Economics, GB)
Marija Slavkovik (University of Bergen, NO)
Astrid Weiss (TU Wien, AT)

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Artificial morality, also called machine ethics, is an emerging field in artificial intelligence that explores how autonomous systems can be enhanced with sensitivity and respect for the legal, social, and ethical norms of human society. Academics, engineers, and the public at large, are all wary of autonomous systems, particularly robots, drones, “driverless” cars, etc. Robots will share our physical space, and so how will this change us? With the predictions in hand of roboticists we can paint portraits of how these technical advances will lead to new experiences and how these experiences may change the ways we function in society. Two key issues are dominant, once robot technologies have advanced and yielded new ways we and robots share the world:

  1. will robots behave ethically, i.e.: as we would want them to, and
  2. can we trust them to act to our benefit.

Rather than any engineering issues, it is these barriers concerning ethics and trust that are holding back the development and use of autonomous systems. One of the hardest challenges in robotics seems to be reliably determining desirable and undesirable behaviours for robots. Our aim here is to advance the work in these areas, bringing together a range of disciplines that can impact upon these problems.

Some of us organised the Dagstuhl 16222 Engineering Moral agents: From human morality to artificial morality seminar in 2016 with the goal of initiating a conversation between Philosophers studying ethics, Robotics researchers developing novel autonomous machines, and Computer Scientists studying AI and reasoning. This provides a clearer understanding of the issues and several avenues for future collaboration. However, it also highlighted further important areas to be exposed, specifically:

  • the extension of ‘ethics’ to also address issues of ‘trust’
  • the practical problems of implementing ethical and trustworthy autonomous machines; and
  • the new verification and validation techniques that will be required to assess these dimensions.

We expect the seminar to:

  • Give researchers across the contributing disciplines an integrated overview of current research in machine ethics and trustworthy robotics from the artificial intelligence side and of relevant areas of philosophy and psychology.
  • Open up a communication channel among researchers tackling ethics and trust, bridging the computer science/humanities/social-science divide in these fields.
  • Identify the central research questions and challenges concerning (i) the definition and operationalisation of the concept of ethics and trust in autonomous systems; (ii) the formalisation and algorithmization of theories of ethics and trust; and (iii) the relationships between ethics and trust in both human and non-human systems.
  • Identify existing and potential societal consequences of these systems. What are the risks, what are the chances, what are beneficial use cases for these systems?

Artificial ethics and trust between humans and autonomous entities both bring together many disciplines which have a vast amount of relevant knowledge and expertise, but which are often inaccessible to one another and insufficiently develop their mutual synergies. Researchers need to communicate to each other their experiences, research interests, and knowledge to move forward. We plan the seminar as a combination of three structures: tutorials, contributed talks, and discussion sessions.

Motivation text license
  Creative Commons BY 3.0 DE
  Michael Fisher, Christian List, Marija Slavkovik, and Astrid Weiss

Related Dagstuhl-Seminar


  • Artificial Intelligence / Robotics
  • Society / Human-computer Interaction
  • Verification / Logic


  • Verification
  • Artificial Morality
  • Social Robotics
  • Machine Ethics
  • Autonomous Systems
  • Explainable AI
  • Safety
  • Trust
  • Mathematical Philosophy
  • Robot Ethics


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