Algorithms for reliable decision-making need causal reasoning

Kern, Christoph ; Fischer Abaigar, Unai ; Schweisthal, Jonas ; Frauen, Dennis; Ghani, Rayid; Feuerriegel, Stefan ; van der Schaar, Mihaela und Kreuter, Frauke (2025): Algorithms for reliable decision-making need causal reasoning. In: Nature Computational Science, Vol. 5, No. 5: pp. 356-360

Abstract

Decision-making inherently involves cause-effect relationships, which introduce causal challenges. We argue that reliable algorithms for decision-making need to build upon causal reasoning. Addressing these causal challenges requires explicit assumptions about the underlying causal structure to ensure identifiability and estimatability, which means that the computational methods must successfully align with decision-making objectives in real-world tasks.

• Item Type: Journal article
• Faculties: Munich School of Management > Institute of Artificial Intelligence (AI) in Management; Mathematics, Computer Science and Statistics > Statistics > Chairs/Working Groups > Chair for Statistics and Data Science in Social Sciences and the Humanities
• Subjects: 300 Social sciences > 310 Statistics
• ISSN: 2662-8457
• Annotation: This version of the article has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s43588-025-00814-9. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/acceptedmanuscript-terms
• Language: English