NOTE: It is not enough to RSPV here; please get a ticket at https://www.eventbrite.co.uk/e/stockholm-ai-summit-14-causal-inference-framework-for-understanding-why-tickets-61145113681!
Causal Inference; framework for understanding Why
"Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk.
Causality is a major part of your daily life. By taking an action, we expect to see results. This event will shed light into the field of Causal Inference. The questions that motivate data insights in the most sciences are not associational but causal in nature.
For example, what is the efficiency of a given drug in a given population? Whether data can prove an employer guilty of hiring discrimination? What fraction of past crimes could have been avoided by a given policy? What was the cause of death of a given individual, in a specific incident? These are causal questions because they require some knowledge of the data-generating process; they cannot be computed from the data alone, nor from the distributions that govern the data.
We discuss how machine learning methods today focus on correlation analyses and prediction, and how this is insufficient when we need to understand causal mechanisms and design interventions.
For this AI summit, we are collaborating with Netlight. Please join us at Netlight at their new HQ to hear about the latest and greatest developments in this vibrant space!
Please do show up even if you are not able to make it for 17:30 - late arrivals are welcomed.
17:30 - 18:00 Mingle and Enlisting
18:00 - 18:30 Introduction to the topic
18:30 - 18:45 Break
18:45 - 19:15 Karina Shyrokykh : "Causal inferences with time-series cross-sectional data"
This talk will cover causal inferences using non-experimental longitudinal data. It will focus on modelling techniques and their underlining assumptions in time-series cross-sectional data.
19:15 - 19:30 Break
19:30 - 20:00 Anders Holst, Senior Research Scientist at SICS, Ph.D: "Distinguishing cause and effect from data"
This presentation we will review the challenges of distinguishing
causes and effects just using historical data, present an approach to
characterize causal mechanisms in an invariant manner, and discuss how
this can be used for causal discovery in real world situations.
20:00 - 21:00 Mingle
Eric Leijonmarck, Data Wizard Enplore
About Stockholm AI:
Stockholm AI is a non profit organisation serving as an open forum to bring industry professionals and researchers in the Stockholm area together to discuss recent and and future developments. We arrange meetups, hackathons, study groups and other events that cover a wide range of topics from the field of AI, with the aim of making Stockholm a natural centre in the world of machine learning.
For more information, visit our website stockholm.ai
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