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Subsequent work has demonstrated that positive testing is not inherently irrational [austerweil2011seeking, perfors2009confirmation, oeberst_toward_2023]; for instance, when target phenomena are relatively rare, positive testing approximates optimal information gathering [klayman_confirmation_1987]. Bias emerges not from the strategy itself, but from the interaction between the search strategy and the environment [klayman_varieties_1995]. When a learner’s hypothesis is a subset of, or embedded within, the truth, positive testing yields “ambiguous verifications” that the learner mistakes for strong evidence for their hypothesis [klayman_confirmation_1987]. This creates a feedback loop where the search strategy retrieves only confirming data, and the learner fails to account for the fact that they are sampling from a biased subset of reality.
Code Metal recently raised $125 million to rewrite defense industry code using AI. Google and Microsoft both report that 25–30% of their new code is AI-generated. AWS used AI to modernize 40 million lines of COBOL for Toyota. Microsoft’s CTO predicts that 95% of all code will be AI-generated by 2030. The rewriting of the world’s software is not coming. It is underway.