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Evaluating Search System Explainability with Psychometrics and Crowdsourcing - Tutorial 1.1

Association for Computing Machinery (ACM) via YouTube

Overview

Explore the evaluation of search system explainability through psychometrics and crowdsourcing in this 11-minute conference talk from SIGIR 2024. Delve into the research presented by Catherine Chen and Carsten Eickhoff on explainability in search and recommendation systems. Gain insights into innovative methods for assessing how well search systems can explain their results and recommendations to users. Learn about the application of psychometric techniques and crowdsourcing approaches to measure and improve the transparency and interpretability of search algorithms. Understand the importance of explainable AI in the context of information retrieval and discover potential implications for enhancing user trust and system effectiveness.

Syllabus

SIGIR 2024 T1.1 [fp] Evaluating Search System Explainability with Psychometrics and Crowdsourcing

Taught by

Association for Computing Machinery (ACM)

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