Pearl used Bayesian network scheme that allowed machines to predict given a patient who returned from Africa with a fever and body aches, the most likely explanation was malaria. In 2011 Pearl won the Turing Award primarily from this work. 

Example of Author's work in Bayesian Network

The prime challenges of artificial intelligence research in 1980s was to enable mahcines to associate a potential cause to set of observable conditions.

Past prime challenge in artificial intelligence research (1980s)

The author (Judea) made great contribution to the development of Artificial intelligence models. In the 1980s he led efforts that allowed machines to reason probabilistically which is a practical application of Bayesian networks 

University of Michigan - Ann Arbor

"Bayesian intelligence failed to bridge the gap between artificial and human intelligence. I'm sure you can figure out the missing ingredient: causality"



Criticism of Bayesian Network from the Judea Pearl

Judea's contribution to Bayesian networks

He thinks that current artificial intelligence research is stuck in probabilistic associations. 

He expresses today's (in 2018) artificial intelligence is powered up versions of what machines could do three decades ago. He defines the machines as "finding hidden regularities in large sets of data"

He is not impressed by the current achievements in deep learning as it only amounts to just intensive curve fitting. 

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