Position: the causal revolution needs scientific pragmatism

Joshua R. Loftus

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Causal models and methods have great promise, but their progress has been stalled. Proposals using causality get squeezed between two opposing worldviews. Scientific perfectionism-an insistence on only using “correct” models-slows the adoption of causal methods in knowledge generating applications. Pushing in the opposite direction, the academic discipline of computer science prefers algorithms with no or few assumptions, and technologies based on automation and scalability are often selected for economic and business applications. We argue that these system-centric inductive biases should be replaced with a human-centric philosophy we refer to as scientific pragmatism. The machine learning community must strike the right balance to make space for the causal revolution to prosper.

JEL-codes: C1 (search for similar items in EconPapers)
Pages: 9 pages
Date: 2024-07-21
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Proceedings of Machine Learning Research, 21, July, 2024, 235, pp. 32671-32679. ISSN: 1938-7228

Downloads: (external link)
http://eprints.lse.ac.uk/125578/ Open access version. (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:125578

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().