The author explores the concept of 'counting arguments' in AI safety, which posit that if a vast majority of possible AI goals are misaligned with human survival, then a randomly generated AI is likely to have misaligned goals. This line of reasoning is compared to Bertrand's Paradox in probability, where different methods of randomly selecting a chord lead to different probability outcomes. The paradox highlights that 'randomness' is ill-defined without specifying the sampling process, and projections can distort perceived distributions, suggesting that AI safety disagreements may stem from differing implicit projections. AI
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IMPACT Challenges common reasoning patterns in AI safety discussions, suggesting that differing implicit assumptions about AI goal distribution may underlie disagreements.
RANK_REASON The article is an opinion piece discussing a philosophical concept related to AI safety, using a probability paradox as an analogy.
