all the impressive achievements of deep learning amount to just curve fitting.” The key, as Pearl suggests, is to replace “reasoning by association” with “causal reasoning” -the ability to infer causes from observed phenomena. As Judea Pearl sees it, the underlying reason for such mistakes is that “. A corollary of such widespread commercial deployment is that when AI gets things wrong-an autonomous vehicle crashes, a chatbot exhibits “racist” behavior, automated credit-scoring processes “discriminate” on gender, etc.-there are often significant financial, legal, and brand consequences, and the incident becomes major news. Such technological developments from artificial intelligence (AI) labs have ushered concomitant applications across the world of business, where an “AI” brand-tag is quickly becoming ubiquitous.
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