AI Bubbles are Bursting with Andrew Orlowski

Today we’ve got a guest who's been doing our job for decades. Andrew Orlowski is a writer who has followed the technology industry for two decades, so he’s see the hype cycle peak and trough many times.

For more on Bubble Trouble, including transcripts of the show, visit us online at http://bubbletroublepodcast.com

You can learn more about Richard at https://www.linkedin.com/in/richard-kramer-16306b2/

More on Will Page at: https://pivotaleconomics.com

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In this episode of Bubble Trouble, hosts Richard Kramer and Will Page are joined by veteran technology journalist Andrew Orlowski. They delve into the recurring market bubbles and dissect the relentless hype surrounding AI and machine learning. Orlowski discusses his track record in identifying technology bubbles and shares his skepticism about the transformative claims made about AI, comparing it to historical overhyped innovations like the metaverse and cryptocurrency. The discussion also touches on the implications of AI on productivity, labor markets, and the economy at large, highlighting the disconnect between policy elites’ expectations and real-world applications. Throughout, the panel emphasizes the broader societal impacts and the role of critical scrutiny in understanding technological advancements.

00:00 Introduction to Bubble Trouble

00:44 Part One

00:49 Meet Andrew Orlowski

01:43 The Origins of Bubble Trouble

02:06 Spotting Bubbles: Andrew's Track Record

02:39 Google's Market Manipulation

07:00 The AI Hype Cycle

12:08 AI's Economic Impact and Skepticism

19:10 The Future of AI and Technology

26:13 Debunking the Efficiency Myth in Tech Companies

26:39 The Role of AI in Financial Markets

28:10 AI Skepticism and the Hype Cycle

28:20 Part Two

29:02 The Future of Chatbots and Machine Learning

30:06 Public Skepticism vs. Elite Optimism

35:54 The Nature of Work and Productivity

42:13 The Middle Class Advantage in the Modern Workplace

45:40 The AI Bubble and Its Implications

49:01 Smoke Signals: Red Flags in the AI Industry

51:19 Conclusion and Final Thoughts

51:51 Credits

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