{"id":900081,"date":"2022-11-21T20:50:24","date_gmt":"2022-11-22T04:50:24","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2023-08-17T08:37:41","modified_gmt":"2023-08-17T15:37:41","slug":"a-causal-ai-suite-for-decision-making","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/a-causal-ai-suite-for-decision-making\/","title":{"rendered":"A Causal AI Suite for Decision-Making"},"content":{"rendered":"

Critical data science and decision-making questions across a wide variety of domains are fundamentally causal questions. We present a suite of open-source causal tools and libraries that aims to simultaneously provide core causal AI functionality to practitioners and create a platform for research advances to be rapidly deployed. In this paper, we describe our contributions towards such a comprehensive causal AI suite of tools and libraries, its design, and lessons we are learning from its growing adoption. We hope that our work accelerates use-inspired basic research for improvement of causal AI.<\/p>\n","protected":false},"excerpt":{"rendered":"

Critical data science and decision-making questions across a wide variety of domains are fundamentally causal questions. We present a suite of open-source causal tools and libraries that aims to simultaneously provide core causal AI functionality to practitioners and create a platform for research advances to be rapidly deployed. In this paper, we describe our contributions 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