Augmenting human intellect: a design case against pure automation
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augmenting human intellect when i started making software, i wasn’t dreaming of a factory. i loved that something on a screen could become an extension of my mind. a place to put a thought before i understood it. to move things around until new connections appeared. to make little systems that worked the way i worked, even if it made no sense to anyone else. the computer wasn’t interesting because it could do work without me. it was interesting because of what i could do with it. the early lineage of computing was built around this possibility. in 1962, Engelbart described augmenting human intellect as helping a person understand complex situations and find solutions that were previously out of reach. his starting point was the human being, not the autonomous machine. he wasn’t describing a faster black box. he was looking at the whole relationship between a person, their tools, their language, their methods, and what they could learn to do with them. the capability belonged to that whole system. somewhere along the way, we started telling a much smaller story about a much more powerful technology. more automation. more agents. more software producing more software. more…
Argues that AI software tools should let users ask why something works, change one part, undo it and learn to make the next change themselves. This gives builders a design criterion beyond output volume.
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