Eliezer Yudkowsky Explains Why Clever Human-Designed Schemes Fail at ASI Alignment

Eliezer Yudkowsky published the essay Cat-Belling Problems following debates at the ILIAD-2026 conference on mathematical AI safety. The piece uses the historical example of Michael Lorrey's proposed reactionless L-drive to illustrate why complex compensatory systems cannot violate conservation of momentum. Yudkowsky argues that any spreadsheet or design claiming net thrust from standard physics components must contain an accounting error because every individual interaction preserves momentum. He extends the analogy to proposals for solving superalignment of ASI, noting that hidden patented compensators or uninspectable calculations do not change the underlying mathematical impossibility. The essay contrasts superficial generalizations like the Law of White Swans with deep laws derived from Noether's theorem and quantum mechanics. Richard Feynman's encounters with perpetual motion machines of the third kind are cited to show how claims of new physics require experimental demonstration rather than unverified tables.

HabrTranslated from Russian

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Eliezer Yudkowsky, a leading researcher on artificial intelligence and technological singularity issues and a central figure in the LessWrong rationalist community, has released the essay Cat-Belling Problems. The text originated in 2021 and was finalized after his August 2026 debates with Jeffrey Irving at the ILIAD-2026 conference on theoretical and mathematical problems of AI safety and control.

The essay opens with the story of Michael Lorrey and his Lorrey Drive, a proposed reactionless engine discussed on the 1990s Extropians mailing list. The design featured masses rotating inside a cylinder, accelerating on one side and decelerating on the other to produce net thrust. Participants asked for explanations because the concept appeared to violate conservation of momentum and Newton's third law.

Lorrey presented an animated diagram and later claimed an Excel spreadsheet proved net force after adding secret patented compensators. He refused to show the spreadsheet. Yudkowsky notes that even if the inventor were a Nobel laureate, the claim would remain impossible under known physics because momentum is conserved in every individual interaction between nucleons, electrons, and other particles.

The deeper reason, Yudkowsky explains, stems from quantum mechanics and Noether's theorem rather than a mere surface-level summary of past observations. Any model built from standard components will sum to zero net momentum change; an arithmetic series of zeros remains zero. Claims that rely on uninspectable compensators therefore contradict mathematics, not just empirical habit.

Yudkowsky draws the direct parallel to proposals for aligning artificial superintelligence. When someone presents an intricate human-designed plan with hidden mechanisms that supposedly solves the superalignment problem, the same epistemic standard applies. The burden is not met by asserting that the plan is clever or that the details are proprietary.

Carl Feynman is quoted recalling his father Richard Feynman's classification of perpetual-motion machines and the 1970 public demonstration that ended when the power cord was unplugged. These historical cases reinforce that experimental proof, not internal spreadsheets, is required when fundamental conservation laws appear to be broken.

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