CONCEPT
Induction
Peirce's second mode of inference — moving from particular observations to general conclusions — the fallible but productive inference that AI systems perform at superhuman scale.
Induction moves from particular observations to general conclusions. This copper wire conducts electricity; that copper wire conducts electricity; therefore, probably, copper conducts electricity. The conclusion goes beyond the evidence — it extends from observed cases to unobserved cases — and this extension introduces risk. The generalization may be wrong. Induction is productive in a way deduction is not, because it yields genuinely new general propositions, but it is fallible, because the new propositions are never guaranteed by the evidence that supports them. Contemporary AI systems perform operations that are functionally inductive on scales that dwarf anything Peirce imagined — but they induce without knowing that they induce, without understanding the risk entailed, and without the capacity to recognize their own failures.
In The You On AI Field Guide
A large language model trained on billions of tokens has, in effect, performed inductions over the entire accessible corpus of human writing — extracting statistical regularities, identifying patterns of co-occurrence, generalizing from observed sequences to predicted sequences. The predictions are often remarkably