The pinnacle of enshittification, or Large Language Models
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| Source: Mastodon | Original article
Gentoo developer Miguel Gorny posted a scathing blog entry on 5 April titled “The pinnacle of enshittification, or Large Language Models”. Gorny, a long‑time voice in the open‑source community, argues that the relentless flood of AI‑generated text, code and media is turning the internet into a self‑reinforcing echo chamber of low‑quality content. He likens today’s LLM boom to “enshittification” – a term popularised by Cory Doctorow to describe how platforms degrade user experience for profit – and warns that hallucinations, synthetic‑data feedback loops and aggressive marketing are eroding trust in digital information.
The post arrives on the heels of our own coverage on 5 April, which revealed that AI assistants misrepresent news content 45 percent of the time, regardless of language or territory. Gorny’s critique adds a community‑level perspective to the growing evidence that LLMs are not merely technical curiosities but forces reshaping the knowledge ecosystem. Researchers have already documented “model collapse”, where models trained on AI‑generated data gradually lose fidelity, and a 2025 preprint still labels hallucination an “inevitable” limitation. Together, these findings suggest that the problem is systemic rather than isolated to a single product.
The significance lies in the potential backlash from developers, enterprises and regulators who rely on trustworthy information. If the perception that LLMs are polluting the web solidifies, we could see tighter scrutiny under the EU AI Act, renewed calls for provenance‑tracking standards, and a shift toward open‑source alternatives that prioritise transparency. Companies may also accelerate work on hallucination‑reduction and synthetic‑data detection, fields that have attracted new funding in the past year.
Watch for official responses from major AI providers, upcoming policy debates in Brussels, and any Gentoo‑led initiatives to embed AI‑safety checks into its package repositories. The conversation Gorny sparked could become a catalyst for the next wave of accountability measures in the LLM market.
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