Position: the causal revolution needs scientific pragmatism

Loftus, Joshua R. ORCID: 0000-0002-2905-1632 (2024) Position: the causal revolution needs scientific pragmatism. Proceedings of Machine Learning Research, 235. pp. 32671-32679. ISSN 1938-7228

Text (loftus24a) - Published Version Download (187kB)

• Scopus publication

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.

Item Type:	Article
Additional Information:	© The Author(s)
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date Deposited:	30 Sep 2024 15:51
Last Modified:	18 Nov 2024 21:24
URI:	http://eprints.lse.ac.uk/id/eprint/125578

Actions (login required)

View Item