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 p...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Beteiligte Personen: Redman, Thomas C. (VerfasserIn), Hoerl, Roger Wesley (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: [Cambridge, Massachusetts] MIT Sloan Management Review [2024]
Ausgabe:[First edition].
Schlagwörter:
Links:https://learning.oreilly.com/library/view/-/53863MIT65413/?ar
Zusammenfassung: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.
Beschreibung:Reprint #65413
Umfang:1 Online-Ressource (6 Seiten)