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Sinopsis
Apocalyptic predictions that AI will eliminate millions of jobs have caused widespread fear. When people hear that AI can write, code, and diagnose, they often jump to a scary conclusion: If machines can think, human work is doomed. Messy Jobs argues that this gloomy belief gets the economics of work wrong.
Economists Luis Garicano, Jin Li, and Yanhui Wu offer a new framework for thinking about AI and work. They show why some roles will disappear, why others will be reshaped, and why many of the most valuable forms of human work will endure. Along the way, they explain how AI changes careers, firms, and the wider economy.
AI will automate many tasks, the authors say, but jobs are more than tasks. Jobs are bundles of judgment, coordination, accountability, tacit knowledge, and human relationships. When tasks are tightly bundled within a job, AI will be less able to eliminate it.
Drawing on organizational economics, recent evidence on the impact of AI, and vivid examples across industries, Messy Jobs answers two urgent questions: What kinds of work will remain valuable when cognition becomes cheap? And how should workers, students, parents, managers, and leaders respond?
Messy Jobs is an urgently needed, practical guide to work, opportunity, and human value in the age of AI.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca de los autores
Luis Garicano is a professor of public policy at the London School of Economics. His research focuses on how information technology and AI affect organizations, expertise, productivity, and economic growth, and on how firms and institutions adapt to change.
Jin Li is a professor in economics and strategy at the University of Hong Kong, where he is Area Head of Management and Strategy and Director of the Centre for AI, Management and Organization. His research focuses on the intersection of organizational economics, personnel economics, and labor economics, with recent work focused on AI and organizations.
Yanhui Wu is a professor at the University of Hong Kong and the head of its department of economics. His research spans organizational economics, media economics, and digital economy. Prior to his academic career, he was an award-winning journalist in China.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Messy Jobs: The Work That AI Cannot Reach
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Messy Jobs: The Work That AI Cannot Reach
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Messy Jobs
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Messy Jobs: The Work That AI Cannot Reach
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Messy Jobs : The Work That AI Cannot Reach
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Apocalyptic predictions that AI will eliminate millions of jobs have caused widespread fear. When people hear that AI can write, code, and diagnose, they often jump to a scary conclusion: If machines can think, human work is doomed. Messy Jobs argues that this gloomy belief gets the economics of work wrong. Economists Luis Garicano, Jin Li, and Yanhui Wu offer a new framework for thinking about AI and work. They show why some roles will disappear, why others will be reshaped, and why many of the most valuable forms of human work will endure. Along the way, they explain how AI changes careers, firms, and the wider economy. AI will automate many tasks, the authors say, but jobs are more than tasks. Jobs are bundles of judgment, coordination, accountability, tacit knowledge, and human relationships. When tasks are tightly bundled within a job, AI will be less able to eliminate it. Drawing on organizational economics, recent evidence on the impact of AI, and vivid examples across industries, Messy Jobs answers two urgent questions: What kinds of work will remain valuable when cognition becomes cheap And how should workers, students, parents, managers, and leaders respond Messy Jobs is an urgently needed, practical guide to work, opportunity, and human value in the age of AI. Nº de ref. del artículo: 9798995221906
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Messy Jobs
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Messy Jobs (Paperback)
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Paperback. Condición: new. Paperback. Apocalyptic predictions that AI will eliminate millions of jobs have caused widespread fear. When people hear that AI can write, code, and diagnose, they often jump to a scary conclusion: If machines can think, human work is doomed. Messy Jobs argues that this gloomy belief gets the economics of work wrong. Economists Luis Garicano, Jin Li, and Yanhui Wu offer a new framework for thinking about AI and work. They show why some roles will disappear, why others will be reshaped, and why many of the most valuable forms of human work will endure. Along the way, they explain how AI changes careers, firms, and the wider economy. AI will automate many tasks, the authors say, but jobs are more than tasks. Jobs are bundles of judgment, coordination, accountability, tacit knowledge, and human relationships. When tasks are tightly bundled within a job, AI will be less able to eliminate it. Drawing on organizational economics, recent evidence on the impact of AI, and vivid examples across industries, Messy Jobs answers two urgent questions: What kinds of work will remain valuable when cognition becomes cheap? And how should workers, students, parents, managers, and leaders respond?Messy Jobs is an urgently needed, practical guide to work, opportunity, and human value in the age of AI. Apocalyptic predictions that AI will eliminate millions of jobs have caused widespread fear. Three renowned economists argue that this assumption is wrong. Messy Jobs is an optimistic guide to work and human value in the age of AI. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798995221906
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