000 | 03960nam a22003617a 4500 | ||
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003 | IIITD | ||
005 | 20231122182307.0 | ||
008 | 231122b xxu||||| |||| 00| 0 eng d | ||
010 | _a 2022020618 | ||
020 | _a9781647824198 | ||
040 |
_aMH/DLC _beng _erda _cDLC _dDLC _dIIITD |
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042 | _apcc | ||
050 |
_aQ335 _b.A3955 2022 |
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082 |
_a006.33 _223/eng20220910 _bAGR-P |
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100 | _aAgrawal, Ajay | ||
245 |
_aPower and prediction : _bthe disruptive economics of artificial intelligence _cby Ajay Agrawal, Joshua Gans and Avi Goldfarb |
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260 |
_aBoston : _bHarvard Business Review Press, _c©2022 |
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300 |
_axiv, 268 p. : _bill. ; _c25 cm. |
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504 | _aThis book includes bibliographical references and index. | ||
505 |
_tPart 1: The Between Times _tChapter 1: A Parable of Three Entrepreneurs Chapter 2: AI's System Future Chapter 3: AI Is Prediction Technology _tPart 2: Rules _tChapter 4: To Decide or Not to Decide Chapter 5: Hidden Uncertainty Chapter 6: Rules are Glue _tPart 3: Systems _tChapter 7: Glued vs. Oiled Systems Chapter 8: The System Mindset Chapter 9: The Greatest System of All _tPart 4: Power _tChapter 10: Disruption and Power Chapter 11: Do Machines Have Power? Agrawal et al FM- Chapter 12: Accumulating Power _tPart 5: How AI Disrupts _tChapter 13: A Great Decoupling Chapter 14: Thinking Probabilistically Chapter 15: The New Judges _tPart 6: Envisaging New Systems _tChapter 16: Designing Reliable Systems Chapter 17: The Blank Slate Chapter 18: Anticipating System Change _tEpilogue: AI Bias and Systems. |
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520 | _a"Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions-powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt-but it is coming. How do businesses prepare? In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption-what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you"-- | ||
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aPrediction of occupational success. | |
650 | 0 | _aForecasting. | |
650 | 0 | _aDisruptive technologies. | |
650 | 0 | _aPower (Social sciences) | |
700 | _aGans, Joshua | ||
700 | _aGoldfarb, Avi | ||
776 | 0 | 8 |
_iOnline version: _aAgrawal, Ajay. _tPower and prediction _dBoston, Massachusetts : Harvard Business Review Press, [2022] _z9781647824204 _w(DLC) 2022020619 |
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