ORCID: https://orcid.org/0000-0001-7363-4299; Fischer Abaigar, Unai
ORCID: https://orcid.org/0000-0003-4893-2547; Schweisthal, Jonas
ORCID: https://orcid.org/0000-0003-3725-3821; Frauen, Dennis; Ghani, Rayid; Feuerriegel, Stefan
ORCID: https://orcid.org/0000-0001-7856-8729; van der Schaar, Mihaela und Kreuter, Frauke
ORCID: https://orcid.org/0000-0002-7339-2645
(2025):
Algorithms for reliable decision-making need causal reasoning.
In: Nature Computational Science, Bd. 5, Nr. 5: S. 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.
| Dokumententyp: | Zeitschriftenartikel |
|---|---|
| Fakultät: | Betriebswirtschaft > Institute of Artificial Intelligence (AI) in Management
Mathematik, Informatik und Statistik > Statistik > Lehrstühle/Arbeitsgruppen > Lehrstuhl für Statistik und Data Science in den Sozial- und Humanwissenschaften |
| Themengebiete: | 300 Sozialwissenschaften > 310 Statistiken |
| ISSN: | 2662-8457 |
| Sprache: | Englisch |
| Dokumenten ID: | 129920 |
| Datum der Veröffentlichung auf Open Access LMU: | 16. Dez. 2025 08:29 |
| Letzte Änderungen: | 16. Dez. 2025 08:29 |
