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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I spent three years working in structure-based drug discovery before I understood that its fundamental assumption, that intermolecular force fields derived from in vacuuo small-molecule measurements can predict large-molecule interactions in water, was utterly wrong.
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Digging into this, I was probably briefly the world expert in understanding solvent effects in predicting intermolecular binding affinity, which was saying very little indeed. I only realized that I knew almost nothing, whereas most other people in the field somehow didn’t.
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Major opportunity for science culture reform: insist that the foundational assumptions of each field be made explicit and tested, instead of glossed over. Many-to-most fields will have to just start over when this happens. Some branches of psychology are doing this now—hooray!
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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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