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Thursday, February 28, 2019

Data, Data Science, Causal Thinking

"The Seven Tools of Causal Inference, with Reflections on Machine Learning," by ACM  A.M. Turing Award recipient Judea Pearl, describes tools that overcome obstacles to human-level machine intelligence. Pearl delivers a message to machine-learning and AI experts in an original video at bit.ly/2GUEyJW.

Excerpt from the long paper, ultimately positioning our challenge:

Key insights:

- Data Science is a two-body problem, connecting data and reality, including the forces behind the data.

- Data Science is the art of interpreting reality in the light of data, not a mirror through which data sees itself from different angles.

- The ladder of causation is the double helix of causal thinking, defining what can and cannot be learned about actions and about worlds that could have been. ...   "

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