Part One. The simplified world: The intelligence errors -- Turing at Bletchley -- The superintelligence error -- The singularity, then and now -- Natural language understanding -- AI as technological kitsch -- Simplifications and mysteries -- Part Two. The problem of inference: Don't calculate, analyze -- The puzzle of Peirce (and Peirce's Puzzle) -- Problems with deduction and induction -- Machine learning and big data -- Abductive inference -- Inference and language I -- Inference and language II -- Part Three. The future of the myth: Myths and heroes -- AI mythology invades neuroscience -- Neocortical theories of human intelligence -- The end of science? "Futurists are certain that humanlike AI is on the horizon, but in fact engineers have no idea how to program human reasoning. AI reasons from statistical correlations across data sets, while common sense is based heavily on conjecture. Erik Larson argues that hyping existing methods will only hold us back from developing truly humanlike AI"-- | 
The myth of artificial intelligence [0,19 mb]