[2308.16377] Science Communications for Explainable Artificial Intelligence
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Computer Science > Human-Computer Interaction

arXiv:2308.16377 (cs)
[Submitted on 31 Aug 2023]

Title:Science Communications for Explainable Artificial Intelligence

Authors:Simon Hudson, Matija Franklin
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Abstract:Artificial Intelligence (AI) has a communication problem. XAI methods have been used to make AI more understandable and helped resolve some of the transparency issues that inhibit AI's broader usability. However, user evaluation studies reveal that the often numerical explanations provided by XAI methods have not always been effective for many types of users of AI systems. This article aims to adapt the major communications models from Science Communications into a framework for practitioners to understand, influence, and integrate the context of audiences both for their communications supporting AI literacy in the public and in designing XAI systems that are more adaptive to different users.
Comments: Accepted at the IJCAI-23 Workshop on XAI held at the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23)
Subjects: Human-Computer Interaction (cs.HC)
Cite as: arXiv:2308.16377 [cs.HC]
  (or arXiv:2308.16377v1 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2308.16377

Submission history

From: Matija Franklin [view email]
[v1] Thu, 31 Aug 2023 00:39:33 UTC (195 KB)
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