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    Prediction machines :
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Tác giả CN Agrawal, Ajay
Nhan đề Prediction machines : the simple economics of artificial intelligence / Ajay Agrawal, Joshua Gans, Avi Goldfarb.
Thông tin xuất bản Boston, Massachusetts : Harvard Business Review Press, 2018
Mô tả vật lý x, 250 p. : ill. ; 25 cm.
Phụ chú Sách quỹ Châu Á
Tóm tắt 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
Thuật ngữ chủ đề Artificial intelligence-Economic aspects
Thuật ngữ chủ đề Decision making-Statistical methods
Thuật ngữ chủ đề Forecasting-Statistical methods
Từ khóa tự do Phương pháp thống kê
Từ khóa tự do Kinh tế
Từ khóa tự do Decision making
Từ khóa tự do Thống kê
Từ khóa tự do Dự báo
Từ khóa tự do AI
Tác giả(bs) CN Gans, Joshua
Tác giả(bs) CN Goldfarb, Avi
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08204|a658.0563|bAGR
1001|aAgrawal, Ajay
24510|aPrediction machines : |bthe simple economics of artificial intelligence / |cAjay Agrawal, Joshua Gans, Avi Goldfarb.
260 |aBoston, Massachusetts : |bHarvard Business Review Press,|c2018
300 |ax, 250 p. : |bill. ; |c25 cm.
500|aSách quỹ Châu Á
520|aThe 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
65010|aArtificial intelligence|xEconomic aspects
65010|aDecision making|xStatistical methods
65010|aForecasting|xStatistical methods
6530 |aPhương pháp thống kê
6530 |aKinh tế
6530 |aDecision making
6530 |aThống kê
6530|aDự báo
6530|aAI
7001 |aGans, Joshua
7001 |aGoldfarb, Avi
852|a100|bTK_Tiếng Anh-AN|j(5): 000113616-7, 000117195-6, 000123822
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