In research, both problem finding and problem solving are important. Surprisingly often, problem finding is more important than problem solving.
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Phil Agre’s investigation of the early history of AI/cogsci has some interesting examples. E.g., re your “developing an underlying narrative,” he looks closely at the the seminal Miller, Galanter, and Pribram paper, Newell and Simon’s GPS paper, and I think JMC’s Advice Taker
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These were out-of-the-blue, not addressing existing issues, and the set up the system of narrative metaphors that shaped AI through to the end of the symbolic era. (And arguably to the present day in some ways.)
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