Evaluating Search System Explainability with Psychometrics and Crowdsourcing

Author:

Chen Catherine1ORCID,Eickhoff Carsten2ORCID

Affiliation:

1. Brown University, Providence, RI, USA

2. University of Tübingen, Tübingen, Germany

Publisher

ACM

Reference64 articles.

1. Amina Adadi and Mohammed Berrada. 2018. Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE access , Vol. 6 (2018), 52138--52160.

2. Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

3. Max Auerswald and Morten Moshagen. 2019. How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions. Psychological methods, Vol. 24, 4 (2019), 468.

4. Eric PS Baumer, Jenna Burrell, Morgan G Ames, Jed R Brubaker, and Paul Dourish. 2015. On the importance and implications of studying technology non-use. interactions, Vol. 22, 2 (2015), 52--56.

5. Tara S Behrend, David J Sharek, Adam W Meade, and Eric N Wiebe. 2011. The viability of crowdsourcing for survey research. Behavior research methods, Vol. 43, 3 (2011), 800--813.

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