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arXiv 1812.08597cs.AI

Interaction Design for Explainable AI: Workshop Proceedings

Prashan Madumal, Ronal Singh, Joshua Newn, Frank Vetere

英文摘要:

As artificial intelligence (AI) systems become increasingly complex and ubiquitous, these systems will be responsible for making decisions that directly affect individuals and society as a whole. Such decisions will need to be justified due to ethical concerns as well as trust, but achieving this has become difficult due to the `black-box' nature many AI models have adopted. Explainable AI (XAI) can potentially address this problem by explaining its actions, decisions and behaviours of the system to users. However, much research in XAI is done in a vacuum using only the researchers' intuition of what constitutes a `good' explanation while ignoring the interaction and the human aspect. This workshop invites researchers in the HCI community and related fields to have a discourse about human-centred approaches to XAI rooted in interaction and to shed light and spark discussion on interaction design challenges in XAI.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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