Explainable AI—A Critical Prerequisite For AI Adoption And Success

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Explainable AI—A Critical Prerequisite For AI Adoption And Success
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As AI is flourishing across multiple industries, ethical questions about its use proliferate paid intel

s artificial intelligence flourishes across multiple industries, ethical questions about its use proliferate.

“In terms of the AI ethics discussion, it is fairly unanimous that having full information is something that is beneficial and good,” she says. Consumers also want the ability to address AI decisions that appear biased or incorrect—especially when the consequences are severe, as is the case with job rejections, loss of medical benefits or denial of bail., an AI risk-assessment tool used across the U.S. to provide data on whether a criminal defendant is likely to commit another offense. The program has encountered court challenges for violating defendants’ due process by not disclosing how it makes its recommendations.

In simple classification models, it may be possible to explain how each variable contributes to a prediction. When predicting the price of a home in a certain area, for instance, those variables could be the number of bedrooms and bathrooms, the home’s square footage and whether or not there’s an attached garage. Decision-tree algorithms that represent clear “if-then” choices between several variables are also easier to explain—at least up to a certain number of variables.

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