Problem
Research questions and friction points this paper is trying to address.
leaky explanations
out-of-scope interpretations
confabulated explanatory insights
Explanation Navigator: Rectifying Out-of-Scope Human Interpretations of Leaky AI Explanations through Conversational Guidance
🤖 AI Summary
研究通过Explanation Navigator框架解决AI解释超出范围的问题，该框架检测用户信息需求与解释内容的不匹配，提供补充解释以纠正误解。
📝 Abstract
As explanations of artificial intelligence systems proliferate, their recipients must grasp not only what they convey but also recognise what they cannot. We conducted an interview study with nine participants to examine how explainees reason when their information needs exceed the scope of available explanations. Participants often unwittingly confabulated explanatory insights when relevant information was missing from the explanations, not recognising the inherent limitations thereof. We characterise such explanations as leaky explanations -- simplifications that strive to hide complexity yet whose correct interpretation hinges on understanding of the concealed details. To address out-of-scope interpretations we propose Explanation Navigator: a conversational interaction framework that detects mismatches between users' information needs and explanations' content, elucidating pertinent yet implicit details and providing complementary explanations for unmet information needs. An online study with 316 participants showed that our approach allowed explainees to recognise and rectify confabulated explanatory insights, guiding them towards developing correct understanding.
Innovation
Methods, ideas, or system contributions that make the work stand out.
conversational interaction framework
out-of-scope interpretations
leaky explanations
explanatory insights
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2024-05-22arXiv.orgCitations: 6
