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Язык мероприятия - английский.
Начало: 2 октября в 17:00.
Спикеры: Dr. Alexander Gebharter, Dr. Christian Feldbacher-Escamilla

Title: Causal inference in evidence-based policy. A tale of three monsters and how to chase them away.

We live in the age of planned policy. Every step of any kind of governance is supposed to be supported by some kind of evidence. But what exactly is good evidence and how is it best used in order to infer the efficacy of such a policy? The paradigmatic example for good evidence are randomized control trials (RCTs). In this lecture, the threats that come with the ortodox view about how RCTs provide evidence for a planned policy are discussed. It is argued that an RCT that showed that a policy worked in a specific domain, though it points at the right causal connection between the policy and the intended outcome, is insufficient because it typically only reveals a small part of the more general causal structure. But way richer causal information is required for reliably predicting a policy’s efficacy in an intended domain. Classical inference patterns are discussed and it is explored how recent advances in AI (causal Bayesian networks) can supplement or even replace them.

К участию приглашаются научные сотрудники, преподаватели, аспиранты, магистры.  
 
Встреча будет организована на платформе Zoom. Ссылка на встречу будет направлена на указанный адрес электронной почты за 1 час до начала встречи.
 
Контакты:
Дарья Чирва, руководитель модуля "Мышление"
dvchirva@itmo.ru