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A Scoresheet for Explainable AI

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conference contribution
posted on 2025-07-22, 06:22 authored by Michael WinikoffMichael Winikoff, John Thangarajah, Sebastian Rodriguez
Explainability is important for the transparency of autonomous and intelligent systems and for helping to support the development of appropriate levels of trust. There has been considerable work on developing approaches for explaining systems and there are standards that specify requirements for transparency. However, there is a gap: the standards are too high-level and do not adequately specify requirements for \emph{explainability}. This paper develops a scoresheet that can be used to specify explainability requirements or to assess the explainability aspects provided for particular applications. The scoresheet is developed by considering the requirements of a range of stakeholders and is applicable to Multiagent Systems as well as other AI technologies. We also provide guidance for how to use the scoresheet and illustrate its generality and usefulness by applying it to a range of applications.

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Preferred citation

Winikoff, M., Thangarajah, J. & Rodriguez, S. (2025, January). A Scoresheet for Explainable AI. In 24th International Conference on Autonomous Agents and Multiagent Systems, Detroit.

Conference name

24th International Conference on Autonomous Agents and Multiagent Systems

Conference start date

2025-05-19

Conference finish date

2025-05-23

Contribution type

Published Paper

Publication or Presentation Year

2025-01-01

Publication status

Published

Place of publication

Detroit

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