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AI and statistics perfect together

Today’s AI developers struggle to predict which algorithms will work. AI lacks a basis for inference: a solid foundation on which to base predictions and decisions. This makes AI tough to explain, creates mistrust, and dooms many AI models to fail in deployment. However, help for AI teams and projec...

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Bibliographic Details
Main Authors: Redman, Thomas C., Hoerl, Roger Wesley (Author)
Format: eBook
Language:English
Published: [Cambridge, Massachusetts] MIT Sloan Management Review 2024
Edition:[First edition]
Subjects:
Artificial Intelligence / Http://id.loc.gov/authorities/subjects/sh85008180
Statistics / Http://id.loc.gov/authorities/subjects/sh85127580
Intelligence Artificielle
Statistics / Aat
Statistique
Artificial Intelligence / Aat
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:Today’s AI developers struggle to predict which algorithms will work. AI lacks a basis for inference: a solid foundation on which to base predictions and decisions. This makes AI tough to explain, creates mistrust, and dooms many AI models to fail in deployment. However, help for AI teams and projects is available from an unlikely source: classical statistics. This article explains how business leaders can apply statistical methods and engage statistics experts to improve results
Item Description:Reprint #65413
Physical Description:6 pages

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