Political economy · Technology · Historical parallel — Stand‑alone essay
Fifty years after the political Right redefined efficiency as a virtue of the smaller state, Silicon Valley's AI evangelists increasingly promise a far more radical economy: dramatically lower costs, drastically fewer workers, and an eventual world beyond ordinary employment.
Pau, 24 September 2026 — by Andre Zolnai
AI‑assisted research and drafting
This New York Times opinion piece argues that the most dangerous AI risk is not accidental loss of control but our deliberate choice to allow AI systems to engage in recursive self-improvement (RSI), where they autonomously design and train ever more powerful successors. The author contends that because we already struggle to understand and control current frontier models, letting them improve themselves would rapidly push capabilities beyond human comprehension and oversight, so RSI should be banned or strictly prohibited until safety can be convincingly demonstrated. The column situates this proposal within a wider debate in which some AI leaders call for “pacing the frontier” or even a moratorium on advanced AI development, while political and commercial pressures—and rival states like China—push for rapid acceleration.
HTML: Perplexity AI
Source: what is doom loop
19 September, 2026
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| Sadhu reading in Kathmandu, Nepal (1965, Greg Zolnai) |
The first three posts in this series traced the AI doom loop, the rare‑book “buy → despine → scan → discard” pipeline, and the legal and copyright fault lines. This fourth post brings the story down to the level of historical and geospatial research: what happens to projects that rely on old maps, local histories, and specialized monographs when those sources are privatized, degraded, or made less accessible.
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| AI-generated by author (Medium) |
The first two posts in this series framed the “tiger eating its tail” dynamic of AI doom loops and mapped the “buy → despine → scan → discard” pipeline for rare and out‑of‑print books. This third post focuses on the legal and copyright fault lines: who owns these texts, on what basis AI companies use them, and where the law may yet draw a line.
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| medievalist.net |
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| Mouseion Alexandreias, "Shrine of the Muses of Alexandria" |
HTML: Perplexity AI
Source: What is a doom loop
18 September, 2026
This follows on a history note here if we remember "whence AI?" First of a series continuing here.
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| Original tale, YouTube |
There is an Indian folk image, often told as a kind of nursery rhyme, of a child and a tiger chasing each other around a tree, round and round, until both are worn down and “turn into butter.” It is a vivid picture of a futile, self‑consuming loop: motion without progress, effort that only exhausts and dissolves what it started with.
That image fits the emerging “AI slop cycle” uncannily well. As models train increasingly on text generated by earlier models, and as the public web fills with AI‑influenced content, we risk a kind of cultural churning: language and knowledge going in circles, losing texture and truth, until everything starts to feel smoothed into an indistinct paste.
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| At Teknica of TekXpert Systems, Calgary 1987 |
During the final minutes of the first lunar landing, a cryptic 1202 alarm flashed on the Lunar Module's display. In Mission Control, a young engineer's quick call—"go on that alarm"—kept the mission alive. The real hero had written that resilience into the code years earlier: Margaret Hamilton.
At roughly 33,000 ft above the Moon, the Apollo Guidance Computer lit up with program alarm 1202. Buzz Aldrin read it aloud; Neil Armstrong asked what it meant. In Houston, the room went very still. The ground was rushing up, and every second of hesitation cost precious altitude.
"The alarms were not the sound of failure. They were the sound of the machine choosing correctly."
