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Judea Pearl argues that until computers can intuit causality true intelligence will remain unobtainable for machines.
The current data-crunching approach to machine learning misses an essential element of human intelligence. Judea Pearl and Dana Mackenzie - Judea Pearl is chancellor's professor of computer science and statistics at UCLA and co-author of " The Book of Why: The Science of Cause and Effect " with Dana Mackenzie, a mathematics writer. This column originally appeared in the Wall Street Journal. Computer programs have reached a bewildering point in their long and unsteady journey toward artificial intelligence. They outperform people at tasks we once felt to be uniquely human, such as playing poker or recognizing faces in a crowd. Meanwhile, self-driving cars using similar technology run into pedestrians and posts and we wonder whether they can ever be trustworthy. Amid these rapid developments and nagging setbacks, one essential building block of human intelligence has eluded machines for decades: Understanding cause and effect.
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