David Deutsch: A new way to explain explanation

Great essay, deeper than being about just Bayesianism. In the essay David talks a lot about explanations and what is good one v/s a bad one. The short TED lecture by him gives a deeper insight into his explanation of why good explanations (hard to vary theory of the world) are the key to scientific and human progress since the scientific revolution. (17 min at 1x) [VIDEO]

As kevinwang has pointed out in slightly different terms: the hypothesis that seems wooly to you seems sharply pointed to others (and vice versa) because explanationless hypotheses ("changing the colour of the button will help") are easily variable (as are the colour of the xkcd jelly beans), while hypotheses that are tied strongly to an explanation are not. You can test an explanationless hypothesis, but that doesn't get you very far, at least in understanding. As usual here I'm channeling David Deutsch's language and ideas on this, I think mostly from The Beginning of Infinity, which he delightfully and memorably explains using a different context here: [VIDEO] (the yt link if you're impatient: [VIDEO] - the part I'm talking about starts at about 9:36, but it's a very tight talk and you should start from the beginning). Incidentally, one of these TED talks of Deutsch - not sure if this or the earlier one - TED-head Chris Anderson said was his all-time favourite. plagiarist: > That doesn't test noticing the button, that tests clicking the button. If the color changes it is possible that fewer people notice it but are more likely to click in a way that increases total traffic. "Critical rationalists" would first of all say: it does test noticing the button, but tests are a shot at refuting the theory, here by showing no effect. But also, and less commonly understood: even if there is no change in your A/B - an apparently successful refutation of the "people will click more be

You have to be careful with the "Explanation(Understanding) vs. Prediction" dichotomy. They are related but Explanations should always have precedence since they are fundamental to creating a Theory in the first place that then can make Predictions. David Deutsch actually argues for Understanding/Explanations over Predictions. Here is a nice Reddit thread on this; David Deutsch argues that explanation, not prediction, is the primary goal of science. How widely accepted is this view? - [LINK] David Deutsch: A New Way To Explain Explanation - (TED talk) [VIDEO] and (Transcript of the previous) [LINK] Here he points out that "good explanations" should be "hard-to-vary". What does he mean by this? It means that "a good explanation" cannot be arbitrarily modified without unraveling its internal coherent structure or contradicting the very facts that it seeks to explain. The evidence and the internal logic that holds up the explanation are tightly coupled together as one organic whole thing.