Research talk: Causal ML and business

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Microsoft Research
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Published on ● Video Link: https://www.youtube.com/watch?v=6cHUh-uK9yw


Duration: 5:51
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Speaker: Jacob LaRiviere, Economist, Microsoft Research Redmond

Using machine learning for causal inference can, in a subset of cases with rich data, replicate results from A/B experimentation. For other cases, like identifying the “average treatment effect for compliers” ML offers more limited scope. There is room to progress methodologically on this front. In the best-case scenario, where we get the tools to estimate average treatment effects for compliers, there is straightforward path to get a scalable inference service off the ground, similar to experimental platforms. In this session, Microsoft economics researcher Jacob LaRiviere will discuss some experiences with causal ML in business scenarios.

Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit



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Tags:
Causal Machine Learning
human-like machine intelligence
computer science
causal machine learning technologies
microsoft research summit