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A guide to understanding AI as normal technology

Arvind Narayanan · 9 Sept 2025

Read the piece on normaltech.ai ↗

3 korrents from this piece ↓

Arvind Narayanan did not write this page.

Every claim below was made in this piece, quoted word for word and numbered in the order the piece makes them, so you can read it there rather than take our word for it. The sentence above each quote is our reading of the claim, not their wording. Each quote was checked against a stored copy of the page at build time; where the two differ, the quote is the fact.

  1. Our reading

    AI's societal benefits and risks are determined by how it is deployed, not by how capable the underlying models become.

    Their wordsThere is a long causal chain between AI capability increases and societal impact. Benefits and risks are realized when AI is deployed, not when it is developed.

  2. Our reading

    Recursive self-improvement in AI will not produce superintelligence because bottlenecks outside the AI system's own technical design limit what it can achieve.

    Their wordswe don't think RSI will lead to superintelligence because the external bottlenecks to building and deploying powerful AI systems cannot be overcome by improving their technical design.

  3. Our reading

    Teams of trained humans, especially when aided by simple automated tools, will continue to match or outperform AI at forecasting geopolitical events such as elections.

    Their wordsWe predict that AI will not be able to meaningfully outperform trained humans (particularly teams of humans and especially if augmented with simple automated tools) at forecasting geopolitical events (say elections).

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