Ajay Agrawal is Professor of Strategic Management and Peter Munk Professor of Entrepreneurship at the University of Toronto's Rotman School of Management. He is also cofounder of The Next 36 and Next AI, cofounder of the AI/robotics company Kindred, and founder of the Creative Destruction Lab. Ajay conducts research on technology strategy, science policy, entrepreneurial finance, and the geography of innovation.
Joshua Gans is Professor of Strategic Management and the holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at Toronto's Rotman School of Management. Gans is a frequent contributor to outlets like the New York Times, Harvard Business Review, Forbes, Slate, and the Financial Times. Joshua also writes regularly at several blogs including Digitopoly.
Avi Goldfarb is the Ellison Professor of Marketing at Toronto's Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, a Fellow at Behavioral Economics in Action at Rotman, and a Research Associate at the National Bureau of Economic Research. His research has been widely covered in the popular press.
"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google
Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.
But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.
When AI is framed as cheap prediction, its extraordinary potential becomes clear:
- Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions.
- Prediction tools increase productivity--operating machines, handling documents, communicating with customers.
- Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete.
Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.
發表於2024-06-15
Prediction Machines 2024 pdf epub mobi 電子書 下載
2018年Facebook被爆5000萬用戶信息用於政治選舉,2019年Snapchat濫用特權監控用戶信息。互聯網公司種種隱私數據醜聞,從側麵反映瞭AI麵臨的挑戰之一,就是如何閤理的收集和使用用戶的隱私數據? 如果AI無法應用隱私數據,那麼AI還能叫AI嗎?根據本書作者的核心觀點,預測越來越...
評分在很多的科幻電影裏都提到一個讓人們思考的問題,人類會不會被人工智能淘汰!隨著人工智能的發展,人們越來越多的工作都被機器取代瞭,人們應該何去何從?彆的不說,現在在我國南方的大工廠裏生産流水綫上的機器人,已經替換瞭大量的工人,過去的人們從事的職業也在越來越多被...
評分人工智能是很聰明,但他不會主動創造。他是被動的一個程序。現在他是前沿的,但沒有人類的推進,他隻會停滯不前。 我們不是沒經曆過這種被取代人工的恐慌。當機器的麵世,很多人工逐漸被機器所取代,就像是以前看的《方世玉與苗翠花》。裏麵機器代替人工,可以更快速更高效率的...
評分說實話,作為一個典型的文科女,我對於人工智能,還有經濟學,其實都是抱著不明覺厲的態度,因為不夠瞭解,所以會覺得很高深莫測,會覺得離我的生活很遙遠,在彆人談起這個話題的時候,隻能睜大懵懂的雙眼,壓根不知道要怎麼去接話,不知道要怎麼參與進去,因為實在是自己知道...
圖書標籤: 經濟學 人工智能 AI 科技 預測 管理 科技商業 深度學習
Cheap predictions for decision making and strategic adjustment under uncertainty & to increase productivity (automation)
評分經濟學傢在tech究竟有什麼貢獻呢。。覺得需要體驗一下纔知道瞭。目前覺得添亂比貢獻多。。
評分這本書完全不是給經濟學人寫的,常常提到的是如果你的公司想用ai應該什麼時候用,怎樣用。一半棄,對我來說沒大有收獲。
評分AI has entered our life. Willing to learn what it can really help us and what damage it can bring as well.
評分Cheap predictions for decision making and strategic adjustment under uncertainty & to increase productivity (automation)
Prediction Machines 2024 pdf epub mobi 電子書 下載