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Article

A Survey of Domain Knowledge Elicitation in Applied Machine Learning

1
Department of Computer Science and Engineering, New York University, Brooklyn, NY 11201, USA
2
Department of Computer Science, Northwestern University, Evanston, IL 60208, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Alison M. Smith-Renner, Gonzalo Ramos and Gagan Bansal
Multimodal Technol. Interact. 2021, 5(12), 73; https://doi.org/10.3390/mti5120073
Received: 16 October 2021 / Revised: 6 November 2021 / Accepted: 17 November 2021 / Published: 24 November 2021
(This article belongs to the Special Issue AI for (and by) the People)
Eliciting knowledge from domain experts can play an important role throughout the machine learning process, from correctly specifying the task to evaluating model results. However, knowledge elicitation is also fraught with challenges. In this work, we consider why and how machine learning researchers elicit knowledge from experts in the model development process. We develop a taxonomy to characterize elicitation approaches according to the elicitation goal, elicitation target, elicitation process, and use of elicited knowledge. We analyze the elicitation trends observed in 28 papers with this taxonomy and identify opportunities for adding rigor to these elicitation approaches. We suggest future directions for research in elicitation for machine learning by highlighting avenues for further exploration and drawing on what we can learn from elicitation research in other fields. View Full-Text
Keywords: elicitation; machine learning; domain expert; domain knowledge; expert knowledge elicitation; machine learning; domain expert; domain knowledge; expert knowledge
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MDPI and ACS Style

Kerrigan, D.; Hullman, J.; Bertini, E. A Survey of Domain Knowledge Elicitation in Applied Machine Learning. Multimodal Technol. Interact. 2021, 5, 73. https://doi.org/10.3390/mti5120073

AMA Style

Kerrigan D, Hullman J, Bertini E. A Survey of Domain Knowledge Elicitation in Applied Machine Learning. Multimodal Technologies and Interaction. 2021; 5(12):73. https://doi.org/10.3390/mti5120073

Chicago/Turabian Style

Kerrigan, Daniel, Jessica Hullman, and Enrico Bertini. 2021. "A Survey of Domain Knowledge Elicitation in Applied Machine Learning" Multimodal Technologies and Interaction 5, no. 12: 73. https://doi.org/10.3390/mti5120073

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