03468cam a2200457 i 4500999001900000001000900019003000800028005001700036006001900053007000300072008004100075010001700116020004300133020004000176040003000216041000800246042000800254050002300262082001400285100002900299245011900328264006600447300002600513336002100539337002500560338002300585505043700608520139201045650004702437650006002484650004202544650005802586650003802644650005302682650003302735700003402768700002602802906004502828942001202873952012502885  c117219d11721920147040BJBSDDR20230411090830.0a|||||r|||| 00| 0 ta171108s2018    mau           000 0 eng c  a  2017049211  a9781633695672 (hardcover : alk. paper)  a1633695670 (hardcover : alk. paper)  aMH/DLCbengerdacMHdDLC  aeng  apcc14aTA 347bA277p 201800a658/.05631 aAgrawal, Ajay K. 92539810aPrediction machines :bthe simple economics of artificial intelligence /cAjay Agrawal, Joshua Gans, Avi Goldfarb. 1aBoston, Massachusetts :bHarvard Business Review Press,c2018  ax, 250 pages ;c25 cm  atext2rdacontent  aunmediated2rdamedia  avolume2rdacarrier0 aCheap 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.  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.--cProvided by publisher 0aArtificial intelligencexEconomic aspects. 4aInteligencia artificial xAspectos económicos 926403 0aDecision makingxStatistical methods. 4aToma de decisiones xMétodos estadísticos 925809 0aForecastingxStatistical methods. 4aProbabilidades xMétodos estadísticos926405 4aGestión empresarial9100261 aGans, Joshua,  d1968-9254041 aGoldfarb, Avi 925406  a7bcbccorignewd1eecipf20gy-gencatlg  2lcccBK  00102lcc40708HUaBJBbBJBcHUd2022-10-05l0oTA 347 A277p 2018p00000164974r2022-10-05 00:00:00t1w2022-10-05yBK