Can We Trust AI to Make Decisions?

The article focuses on the evolution of decision-making in artificial intelligence (AI), particularly the shift from traditional rule-based systems to data-driven machine learning algorithms. It explores the advantages and limitations of data-driven AI, highlighting concerns about its potential to s...

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Detalles Bibliográficos
Publicado en:	Skeptic Vol. 29; no. 1; pp. 24 - 28
Autores principales:	GASSER, URS, MAYER-SCHÖNBERGER, VIKTOR
Formato:	Artículo
Publicado:	Skeptics Society 2024
Materias:	Artificial intelligence Decision making Machine learning Algorithms Experiments
Acceso en línea:	Ver este registro en EBSCOhost

Descripción
Sumario:	The article focuses on the evolution of decision-making in artificial intelligence (AI), particularly the shift from traditional rule-based systems to data-driven machine learning algorithms. It explores the advantages and limitations of data-driven AI, highlighting concerns about its potential to stifle innovation and adaptability by favoring consistency over experimentation.