From Statistical to Causal Learning

• URL: http://arxiv.org/abs/2204.00607v1
• Date: Fri, 1 Apr 2022 17:55:22 GMT
• Title: From Statistical to Causal Learning
• Authors: Bernhard Sch\"olkopf and Julius von K\"ugelgen
• Abstract summary: We describe basic ideas underlying research to build and understand artificially intelligent systems. Some of the hard open problems of machine learning and AI are intrinsically related to causality.
• Score: 9.327920030279586
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We describe basic ideas underlying research to build and understand artificially intelligent systems: from symbolic approaches via statistical learning to interventional models relying on concepts of causality. Some of the hard open problems of machine learning and AI are intrinsically related to causality, and progress may require advances in our understanding of how to model and infer causality from data.

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