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" These examples do not show that theoretical knowledge is worthless. Quite the reverse. A conceptual framework is vital even for the most practical men going about their business. In many circumstances, new theories have led to direct technological breakthroughs (such as the atom bomb emerging from the Theory of Relativity). The real issue here is speed. Theoretical change is itself driven by a feedback mechanism, as we noted in chapter 3: science learns from failure. But when a theory fails, like say when the Unilever mathematicians failed in their attempt to create an efficient nozzle design, it takes time to come up with a new, all-encompassing theory. To gain practical knowledge, however, you just need to try a different-sized aperture. Tinkering, tweaking, learning from practical mistakes: all have speed on their side. Theoretical leaps, while prodigious, are far less frequent. "
― Matthew Syed , Black Box Thinking: Why Some People Never Learn from Their Mistakes - But Some Do
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" But artificial intelligence has moved on since then.7 One of the vogue ideas is called temporal difference learning. When designers created TD-Gammon, a program to play backgammon, they did not provide it with any preprogrammed chess knowledge or capacity to conduct deep searches. Instead, it made moves, predicted what would happen next, and then looked at how far its expectations were wide of the mark. That enabled it to update its expectations, which it took into the next game. In effect, TD-Gammon was a trial-and-error program. It was left to play day and night against itself, developing practical knowledge. When it was let loose on human opponents, it defeated the best in the world. The software that enabled it to learn from error was sophisticated, but its main strength was that it didn’t need to sleep, so could practice all the time. "
― Matthew Syed , Black Box Thinking: Why Some People Never Learn from Their Mistakes - But Some Do
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" The greatest difficulty that many people face, as we have seen, is in admitting to their personal failures, and thus learning from them. We have looked at cognitive dissonance, which becomes so severe that we often reframe, spin, and sometimes even edit out our mistakes. Now think of the Unilever biologists. They didn’t regard the rejected nozzles as failures because they were part and parcel of how they learned. All those rejected designs were regarded as central to their strategy of cumulative selection, not as an indictment of their judgment. They knew they would have dozens of failures and were therefore not fazed by them. But when we are misled into regarding the world as simpler than it really is, we not only resist testing our top-down strategies and assumptions, we also become more defensive when they are challenged by our peers or by the data. After all, if the world is simple, you would have to be pretty stupid not to understand it. "
― Matthew Syed , Black Box Thinking: Why Some People Never Learn from Their Mistakes - But Some Do
