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Prediction machines

por Agrawal, Ajay

Autores adicionales: Gans, Joshua -- 1968- | Goldfarb, Avi

Publicado por : Harvard Business Review Press (Boston, Massachusetts) Detalles físicos: x, 250 páginas ISBN:9781633695672; 1633695670.

Tema(s): Inteligencia artificial -- Aspectos económicos | Toma de decisiones -- Métodos estadísticos | Predicciones -- Métodos estadísticos | Sistemas de información en administración

Año : 2018

Existencias ( 1 )
Notas de título ( 3 )

Tipo de ítem	Ubicación actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras	Reserva de ítems
Libro	Sede del Emprendimiento, Innovación y Creación 1er piso	Libro	658.0563 A277p (Navegar estantería)	Ej.1	Disponible		100159684

Total de reservas: 0

Cheap changes everything -- The magic of prediction -- Why it's called intelligence -- Data is the new oil -- The new division of labor -- Unpacking decisions -- The value of judgment -- Taming complexity -- What machines can learn -- Fully automated decision-making -- Deconstructing workflows -- Decomposing decisions -- Job redesign -- AI in the C-suite -- When AI transforms your business -- Managing AI risk -- Beyond business.

The idea of artificial intelligence--job-killing robots, self-driving cars, and self-managing organizations--captures the imagination, evoking a combination of wonder and dread for those of us who will have to deal with the consequences. But what if it's not quite so complicated? The real job of artificial intelligence, argue these three eminent economists, is to lower the cost of prediction. And once you start talking about costs, you can use some well-established economics to cut through the hype. The constant challenge for all managers is to make decisions under uncertainty. And AI contributes by making knowing what's coming in the future cheaper and more certain. But decision making has another component: judgment, which is firmly in the realm of humans, not machines. Making prediction cheaper means that we can make more predictions more accurately and assess them with our better (human) judgment. Once managers can separate tasks into components of prediction and judgment, we can begin to understand how to optimize the interface between humans and machines. More than just an account of AI's powerful capabilities, Prediction Machines shows managers how they can most effectively leverage AI, disrupting business as usual only where required, and provides businesses with a toolkit to navigate the coming wave of challenges and opportunities.--

Texto en inglés