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Beyond integrative experiment design: Systematic experimentation guided by causal discovery AI

Published online by Cambridge University Press:  05 February 2024

Erich Kummerfeld Open the ORCID record for Erich Kummerfeld [Opens in a new window]  and
Bryan Andrews
Erich Kummerfeld*
Affiliation:
Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA erichk@umn.edu; https://erichkummerfeld.com/
Bryan Andrews
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA andr1017@umn.edu
*
*Corresponding author.
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Abstract

Integrative experiment design is a needed improvement over ad hoc experiments, but the specific proposed method has limitations. We urge a further break with tradition through the use of an enormous untapped resource: Decades of causal discovery artificial intelligence (AI) literature on optimizing the design of systematic experimentation.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 47 , 2024 , e52
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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