An important practical problem plus an attractive technical formulation generate an exciting research discipline, with funding, journals, conferences, and the appearance of interesting incremental results. Usually this is all wasted because fundamental assumptions are false.
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We should teach the skills for locating the hidden foundational assumptions of a field. Often these were explicit originally, then buried under various rhetorical devices that direct attention away. On the origins and obscuration of AI’s assumptions: https://www.gridspinoza.net/sites/default/files/2016-07/Toward%20a%20Critical%20Technical%20Practice%3A%20Lessons%20Learned%20in%20Trying%20to%20Reform%20AI%20Philip%20E.%20Agre.pdf …
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I encourage people to incorporate folks well outside of their field into discussing the experimental plan. The naive questions and need to explain things simply expose assumptions that should be tested.
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This will happen if and when the entire university system is torn up, root and branch.
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