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Author: Ajay Agrawal

Narrator: Ryan

Format: MP3

IBSN: 9781647824198

Language: English

Publish Date: 15/11/2022

Audiobook length: 31 min

Contents

Chapter 1Overview
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Chapter 2The Mechanics of Machine Prediction
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Chapter 3Strategic Implications for Business
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Chapter 4Global Implications and Societal Change
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Chapter 5Summary and Review
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Why listen to Power And Prediction

Listening to the summary audiobook of "Power and Prediction" by Ajay Agrawal is a compelling choice for anyone interested in understanding the transformative impact of artificial intelligence on business and society. Agrawal distills complex concepts into actionable insights, showcasing how predictive analytics can enhance decision-making and foster innovation. The audiobook format makes it accessible and convenient for busy professionals, allowing listeners to grasp crucial strategies for leveraging technology in a rapidly evolving landscape. By engaging with this summary, you can gain a clear perspective on harnessing the power of AI to navigate future challenges and opportunities effectively.

Author : Ajay Agrawal

Ajay Agrawal, Joshua Gans, and Avi Goldfarb are esteemed academics and thought leaders in the intersection of economics and artificial intelligence. Agrawal, a professor at the University of Toronto, is known for his pioneering research on the economics of AI. Gans holds a chair in strategic management and is a prolific author on innovation and disruption. Goldfarb, an expert in marketing and AI, brings insights into how technology transforms business. Together, they co-founded the Creative Destruction Lab to mentor tech startups and have authored influential works, making them authoritative voices on AI's economic implications.

Key Insights from Power And Prediction

  • The book emphasizes the transformative power of predicting future outcomes through data analysis. Agrawal argues that organizations that leverage predictive analytics can make more informed decisions and maintain a competitive edge.
  • Agrawal discusses the implications of artificial intelligence and machine learning in shaping business forecasts. He posits that understanding the underlying algorithms is crucial for harnessing their predictive capabilities effectively.
  • The author explores the ethical considerations surrounding predictive technologies, including privacy concerns and the potential for bias. He advocates for a balanced approach that prioritizes transparency and accountability in data usage.
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