{
  "id": 11137882,
  "title": "The AI Pascal’s Wager",
  "url": "https://urgent.news/2026/10/01/the-ai-pascals-wager",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-01T02:03:34.000Z",
  "source": {
    "name": "Lobsters",
    "slug": "lobsters",
    "url": "https://ploum.net/2026-10-01-pascal_wager.html"
  },
  "original_language": "en",
  "account": "When considering the use of AI-generated contributions in open source projects, there are three potential positions to take. The middle ground, which is currently the default, may seem rational but is actually unsustainable. If a project remains in the middle ground, AI-generated code will eventually slip in despite safeguards such as mandatory human review. The longer a project stays in the middle ground, the more inevitable the infiltration of slop becomes. Instead of leaving the decision to the world, open source projects must urgently choose whether to accept or reject AI-generated contributions. Rejecting AI-generated contributions may alienate some community members and contributors, but those who refuse to use AI-generated code are likely not the best contributors for the project anyway. Rejecting AI-generated contributions will not alienate users, as nobody is turning away from software just because it was created by humans. The main issue with AI-generated code is the unknown long-term impact on the codebase. If AI assistants become too expensive or the code becomes difficult to understand, it could lead to major problems. Cory Doctorow compares AI-generated code to asbestos, as it may look appealing now but will be difficult to remove later. While mass marketing tries to create a Fear of Missing Out, the most rational approach is to strongly reject all AI-generated contributions for now. If a project adopts AI-generated contributions, it may alienate some community members and lose its independence, but contributors who are turned away may not have been valuable anyway. The worst hypothetical regret is potentially regretting not adopting AI earlier. Therefore, the conclusion is that open source projects should strongly refuse AI-generated contributions unless they can be confident that LLMs are heading towards ethical, reliable, and sustainable solutions.",
  "summary": null,
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}