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The Glass Box Approach: Verifying Contextual Adherence to Values
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.ORCID-id: 0000-0002-8423-8029
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.ORCID-id: 0000-0001-7409-5813
2019 (Engelska)Ingår i: AISafety 2019: Proceedings of the Workshop on Artificial Intelligence Safety 2019co-located with the 28th International Joint Conference on Artificial Intelligence (IJCAI-19) / [ed] Huáscar Espinoza, Han Yu, Xiaowei Huang, Freddy Lecue, Cynthia Chen, José Hernández-Orallo, Seán Ó hÉigeartaigh, Richard Mallah, CEUR-WS , 2019Konferensbidrag, Muntlig presentation med publicerat abstract (Refereegranskat)
Abstract [en]

Artificial Intelligence (AI) applications are beingused to predict and assess behaviour in multiple domains, such as criminal justice and consumer finance, which directly affect human well-being. However, if AI is to be deployed safely, then people need to understand how the system is interpreting and whether it is adhering to the relevant moral values. Even though transparency is often seen as the requirement in this case, realistically it might notalways be possible or desirable, whereas the needto ensure that the system operates within set moral bounds remains.

In this paper, we present an approach to evaluate the moral bounds of an AI system based on the monitoring of its inputs and outputs. We place a ‘Glass Box’ around the system by mapping moral values into contextual verifiable norms that constrain inputs and outputs, in such a way that if these remain within the box we can guarantee that the system adheres to the value(s) in a specific context. The focus on inputs and outputs allows for the verification and comparison of vastly different intelligent systems–from deep neural networks to agent-based systems–whereas by making the context explicit we exposethe different perspectives and frameworks that are taken into account when subsuming moral values into specific norms and functionalities. We present a modal logic formalisation of the Glass Box approach which is domain-agnostic, implementable, and expandable.

Ort, förlag, år, upplaga, sidor
CEUR-WS , 2019.
Serie
CEUR Workshop Proceedings, ISSN 1613-0073
Nyckelord [en]
artificial intelligence, safety, verification, ethics
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
datalogi
Identifikatorer
URN: urn:nbn:se:umu:diva-160949OAI: oai:DiVA.org:umu-160949DiVA, id: diva2:1330967
Konferens
AISafety 2019, Macao, China, August 11-12, 2019
Forskningsfinansiär
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Anmärkning

Session 4: AI Value Alignment, Ethics and Bias

Tillgänglig från: 2019-06-26 Skapad: 2019-06-26 Senast uppdaterad: 2020-02-07Bibliografiskt granskad

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