Explore the concept of explainability in conversational information-seeking systems through this 14-minute conference talk presented at SIGIR 2024. Delve into the research conducted by Weronika Łajewska, Damiano Spina, Johanne Trippas, and Krisztian Balog on enhancing transparency in search and recommendation systems. Gain insights into the importance of explainable AI in the context of conversational interfaces and learn about potential strategies for improving user trust and understanding in information retrieval processes.
Explainability for Transparent Conversational Information-Seeking
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
SIGIR 2024 T1.1 [fp] Explainability for Transparent Conversational Information-Seeking
Taught by
Association for Computing Machinery (ACM)
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