Our field isn't quite "artificial intelligence" -- it's "cognitive automation": the encoding and operationalization of human-generated abstractions / behaviors / skills. The "intelligence" label is a category error
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Cognitive automation is incredibly useful. But autonomous abstraction generation is a different creature altogether. As new lifeforms are to animated cartoon characters -- whether the cartoon character is modeled by hand or captured via example
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"If the cartoon is drawn with sufficient realism and covers sufficiently many scenes, what's the difference?", you may ask. Adaptability to the unknown. A lifeform will autonomously adapt to a changing future. An automaton will perform the scenes you planned for.
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Intelligence is adaption to unknown unknowns across an unknown range of tasks and domains. Automation is, at best, robustly handling known unknowns over known tasks (which is already incredibly difficult and resource-intensive in the real world -- whether engineering or data)
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The resource-intensiveness, naturally, comes from the lack of adaptability: you need to plan for every possible unknown, whether explicitly or via a dense sampling of possible situations (assuming a fixed distribution)
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End of conversation
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And here we are at the intersection of lifeform and automaton, [human], so ably distributed that we may eventually change the unknown’s adaptation to us, completing the...understandingness? If we were them, wouldn’t we want to see stuff like this??
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How about starting with an automaton which then learns ?
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