University of Cambridge > Talks.cam > Logic and Semantics Seminar (Computer Laboratory) > Interventions and Counterfactuals for the Working Programmer

Interventions and Counterfactuals for the Working Programmer

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If you have a question about this talk, please contact Ioannis Markakis .

Correlation famously does not imply causation! But how then can we answer interventional questions such as “Does smoking cause cancer?” or even counterfactual ones as “If I had left one minute earlier, would I have managed to arrive on time?” This is the subject of Causal Inference, as pioneered and formalized by Judea Pearl. In my talk, I want to focus on how such problems can be modelled and solved using tools from programming languages theory.

I will aim to give a general introduction to causal inference from a programmer’s point of view. I will then present work-in-progress from an ongoing collaboration dedicated to the extension of a probabilistic programming language to a causal probabilistic programming language; this includes operational semantics, a type system and denotational semantics using graded monads.

This talk is part of the Logic and Semantics Seminar (Computer Laboratory) series.

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