Prediction MachinesThe Simple Economics of Artificial Intelligence - Updated Edition
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Zusammenfassungen
Artificial intelligence seems to do the impossible, magically bringing machines to life—driving cars, trading stocks, and teaching children. But facing the sea change that AI brings 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 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 masterful stroke, they lift the curtain on the AI-is-magic hype and provide economic clarity about the AI revolution as well as a basis for action by executives, policy makers, investors, and entrepreneurs.
In this new, updated edition, the authors illustrate how, when AI is framed as cheap prediction, its extraordinary potential becomes clear:
- Prediction is at the heart of making decisions amid 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 strategies to compete.
The authors reset the context, describing the striking impact the book has had and how its argument and its implications are playing out in the real world. And in new material, they explain how prediction fits into decision-making processes and how foundational technologies such as quantum computing will impact business choices.
Penetrating, insightful, and practical, Prediction Machines will help you navigate the changes on the horizon.
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Personen KB IB clear | Dan Ariely , Nick Bostrom , James Champy , Brian Christian , Pedro Domingos , Martin Ford , Carl Benedikt Frey , Claudia Goldin , Michael Hammer , Richard Harper , Walter Isaacson , Daniel Kahneman , John Markoff , Michael A. Osborne , Tom Rodden , Yvonne Rogers , Abigail Sellen , Nate Silver , Paul Slovic , Nassim Nicholas Taleb , Max Tegmark , Amos Tversky | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Fragen KB IB clear | Wie treffen wir Entscheidungen?How do we decide? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Aussagen KB IB clear | Machine learning benötigt Daten | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Begriffe KB IB clear | Alexa , Algorithmusalgorithm , AlphaGo , China , Datendata , deep learning , Gesellschaftsociety , Google , Komplexitätcomplexity , Künstliche Intelligenz (KI / AI)artificial intelligence , machine learning , Ökonomieeconomy , Prognose , Risikorisk , Statistikstatistics , Ungewissheit | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Nicht erwähnte Begriffe | facebook, Intelligenz, Siri, Sprachassistenten |
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7 Erwähnungen
- Diskriminierungsrisiken durch Verwendung von Algorithmen - Eine Studie, erstellt mit einer Zuwendung der Antidiskriminierungsstelle des Bundes. (Carsten Orwat) (2019)
- New Laws of Robotics (Frank Pasquale) (2020)
- God, Human, Animal, Machine - Technology, Metaphor, and the Search for Meaning (Meghan O'Gieblyn) (2021)
- Machtmaschinen - Warum Datenmonopole unsere Zukunft gefährden und wie wir sie brechen (Thomas Ramge, Viktor Mayer-Schönberger) (2021)
- Power and Progress - Our Thousand-Year Struggle Over Technology and Prosperity (Daron Acemoglu, Simon Johnson) (2023)
- Navigating the Jagged Technological Frontier - Field Experimental Evidence of the Effects of AI on KnowledgeWorker Productivity and Quality (Fabrizio Dell'Acqua, Saran Rajendran, Edward McFowland III, Lisa Krayer, Ethan Mollick, François Candelon, Hila Lifshitz-Assaf, Karim R. Lakhani, Katherine C. Kellogg) (2023)
- Theorien des digitalen Kapitalismus - Arbeit und Ökonomie, Politik und Subjekt (Tanja Carstensen, Simon Schaupp, Sebastian Sevignani) (2023)
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Bibliographisches
Beat und dieses Buch
Beat hat dieses Buch erst in den letzten 6 Monaten in Biblionetz aufgenommen. Er hat dieses Buch einmalig erfasst und bisher nicht mehr bearbeitet. Beat besitzt kein physisches, aber ein digitales Exemplar. (das er aber aus Urheberrechtsgründen nicht einfach weitergeben darf). Es gibt bisher nur wenige Objekte im Biblionetz, die dieses Werk zitieren. Beat selbst sagt, er habe dieses Dokument überflogen.