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The Fraught Bubble of AI: A Candid Insight from Cory Doctorow

January 11, 2024

Summary: The Fraught Bubble of AI - Insights from Cory Doctorow

  • AI and Dotcom Parallels: Cory Doctorow compares the current AI hype to the dotcom bubble, highlighting the disparity between expectations and reality.
  • Nature of Tech Bubbles: Tech bubbles can either leave behind valuable remnants or nothing substantial. Doctorow believes the AI bubble, though filled with fraud, might leave useful elements for future tech.
  • AI vs. Other Bubbles: AI's potential fallout is contrasted with the minimal value left by recent tech bubbles like cryptocurrency and NFTs.
  • Costs and Limitations of AI: Discusses the high costs of maintaining AI models and the problem of AI "hallucinating" facts.
  • Utility of AI: Acknowledges AI's usefulness in specific areas but warns against overreliance, as seen in the limitations of self-driving cars.
  • Learning from AI: Emphasizes the importance of learning data analysis and wrangling skills from the AI bubble to solve real-world issues.
  • Doctorow's Perspective: Provides a realistic view of AI, urging consideration of its role post-bubble and focusing on potential technological progress.

The Parallels Between AI and Dotcom

Renowned journalist and science fiction author Cory Doctorow has recently put forward a compelling perspective on the current state of artificial intelligence (AI), comparing it to the dotcom crisis of the early 2000s. During this period, Silicon Valley firms experienced a significant downfall when venture capital became scarce, leading to a widespread crisis. Doctorow draws a parallel to the contemporary AI landscape, which is characterized by exceedingly high expectations and promises that starkly contrast with the tangible reality. As Doctorow says, "What if I got hit by lightning while walking with an umbrella? Ban umbrellas! Fight the menace of lightning!" This encapsulates the often exaggerated response to technology's potential dangers​​​​.

The Dual Nature of Tech Bubbles

Doctorow emphasizes that tech bubbles can be of two types: those that leave something valuable behind and those that do not. The dotcom bubble, for instance, attracted millions of young individuals to the tech sector, effectively building an "army of technologists." Despite its eventual burst, it left behind a significant imprint on the technology industry. Similarly, Doctorow argues, although the AI bubble is replete with fraud and might soon burst, it could still leave behind useful remnants that could contribute to future technological advancements​​.

Comparing AI with Other Bubbles

Interestingly, Doctorow contrasts the AI bubble with other recent tech bubbles, such as those in the cryptocurrency and NFT sectors. He suggests that unlike the dotcom bubble, these recent bubbles have left behind very little of value. The fraud in the cryptocurrency bubble, according to Doctorow, was so pervasive that almost nothing substantial remains in its wake​​.

The Costs and Limitations of AI

Doctorow also sheds light on the immense costs involved in maintaining large language models like OpenAI's ChatGPT. The reliance on substantial capital investments, under the assumption that the technology will eventually become self-sustainable, is a significant concern. Moreover, he highlights the issue of AIs "hallucinating" facts, which undermines their utility​​.

AI's Potential Utility

Despite these challenges, Doctorow acknowledges the potential utility of AI in specific contexts. For instance, AI could assist radiologists in scanning X-rays for cancerous growths or aid accountants in drafting tax returns. However, he cautions against the overreliance on AI to replace human workers, citing the example of Cruise's recent decision to pull its self-driving cars from public streets following an incident in San Francisco. This, according to Doctorow, indicates the limitations and regulatory challenges that AI technologies face​​.

Learning from the AI Bubble

Doctorow concludes by emphasizing that the AI bubble has motivated people to learn about statistical analysis at scale and data wrangling. These skills could be crucial in solving real-world problems. He urges the tech sector to focus on what will be left behind after the AI bubble bursts, rather than getting distracted by current debates over AI's safety and ethics​​.

In Conclusion

Cory Doctorow's insights into the AI industry offer a realistic and critical perspective. His comparison of AI to the dotcom bubble provides a historical context to understand the potential trajectory of AI. While acknowledging the pitfalls and fraud within the AI bubble, Doctorow also highlights the potential for meaningful technological progress post-bubble. His views encourage a thoughtful examination of AI's role in our future.

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