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Chronicles

The story behind the story

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As researchers talk about the arrival of supersmart AI, far fewer voices are trying to envision and articulate what a world awash in AI might actually look like

What to make of the statements of the AI labs?  —  Recently, something shifted in the AI industry.

One Useful Thing Ethan Mollick

Context & Ripple Effects

The story identifies a change in AI discourse: attention is moving from concrete accounts of how AI could reshape society toward claims about “supersmart” systems. That shift follows coverage framing AI as a fast-moving analogue to industrial transformation, rather than a distant abstraction, in the industrial-revolution comparison.

It also sits alongside concern that generative AI concentrates influence in a small set of companies. A narrower focus on superintelligence can leave the nearer-term distribution of power and uses of current systems less fully articulated.

First-order effects

  • AI labs and researchers emphasizing supersmart AI set the terms of debate around long-horizon capability and control, while practical social outcomes receive less attention.
  • Policymakers, users, and critics have less shared language for evaluating the everyday institutional consequences of AI deployment.

Second-order effects

  • A discourse centered on hypothetical superintelligence may favor governance proposals aimed at controlling advanced models over approaches that address deployment, access, and market concentration.
  • Labs can gain strategic legitimacy from frontier-capability narratives, while organizations building or buying AI tools must make adoption decisions without equally prominent public visions of their broader effects.

Third-order effects

  • If this framing persists, AI governance may become split between speculative frontier-risk debates and the operational effects of systems already entering work and institutions.
  • The underlying contest is whether AI is treated chiefly as an exceptional humanlike intelligence or as a technology whose social outcomes depend on deployment choices, a tension examined in the normal-technology versus superintelligence debate.

The trend: AI policy and industry narratives are increasingly being shaped by a contest between frontier-intelligence claims and the concrete governance of AI’s present-day deployment.

Discussion

  • Vox Kelsey Piper on x
    It's getting harder to measure just how good AI is getting
  • @mergesort.me Joe Fabisevich on bluesky
    Most of my conversations about AI devolve into a question of “when will this happen”, rather than “what do we do when this all happens?” @emollick.bsky.social nails it, we need to be asking what we do next, yesterday, not when the changes start rolling in.  —  www.oneusefulthing.…
  • @carnage4life Dare Obasanjo on bluesky
    Over the past year, I've discussed “AI as a junior employee” as a near-term goal and “AI surpassing human intellect” within my lifetime.  Now, the industry treats the first as reality and the second as imminent.
  • @emollick Ethan Mollick on x
    There has been a definite shift in recent weeks where insiders in the various AI labs are suggesting that very intelligent AIs are coming very soon. I wrote a bit about why this might be happening and what we can take away from their apparent confidence. https://www.oneusefulthin…
  • r/OpenAI r on reddit
    Ethan Mollick: “Recently, something shifted in the AI industry.  Researchers began speaking urgently about the arrival of supersmart AI systems, a flood. …