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Management article
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Reference no. SMR65303
Published by: MIT Sloan School of Management
Published in: "MIT Sloan Management Review", 2024
Length: 7 pages

Abstract

Today's senior business managers have the power - and the responsibility - to prevent AI project failures. But in order to do so, they need to know how to evaluate the data sets and models being used. This article offers a framework for identifying the right data set for your business problem and suggests six tough questions to ask developers before and during the deployment of artificial intelligence models.

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Abstract

Today's senior business managers have the power - and the responsibility - to prevent AI project failures. But in order to do so, they need to know how to evaluate the data sets and models being used. This article offers a framework for identifying the right data set for your business problem and suggests six tough questions to ask developers before and during the deployment of artificial intelligence models.

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