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it is important to measure AI inputs, i.e., skills, software, data, and management practices as well as AI outputs i.e. AI consumption patterns. Both are difficult to measure as they are often service-based and their intangibility remains a measurement challenge

it is important to measure AI inputs, i.e., skills, software, data, and management practices as well as AI outputs i.e. AI consumption patterns. Both are difficult to measure as they are often service-based and their intangibility remains a measurement challenge


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Author Apolinario ("Sam") Ortega - founder of INVBAT.COM - AI + CHATBOTPosted on March 26, 2021May 19, 2021Categories Measurement in AI Policy

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