Feynman wisdom is that you don’t truly understand something until you can explain it to a newcomer.

This gets confused with two seemingly similar claims, however, both of which are (IMO) wrong.
In particular, it doesn’t mean that if you can explain X to a newcomer, that X is true! (Even if the explanation is convincing.)

Nor does it mean that someone who explains something to you understands it.
Knowing, understanding, and explaining are all linked—but in complex ways (the subject of our currently-pinned cog sci paper).
Feynman is focused, in particular, on explaining theoretical physics—a major post-war experience for him being the Feynman Lectures on Physics.
Physicists (at least before the 1990s) got very comfortable with the idea that truth was mathematical consistency (+ mild matches to data). The main barrier after that was simply understanding; a good test of the latter was explanation.
The era of popular physics was a virtuous cycle. Physicists got it right, and made amazing strides by understanding their mathematics; this enabled them to explain revolutionary ideas to the public, who (rightly) celebrated them. We take great pleasure in explanations.
Call this the First “I fucking love science” Era (IFLSE1). The pattern transferred over to evolutionary biology, in Dawkins’ 1970s Selfish Gene, a masterpiece that was blurbed as “the kind of writing that makes the reader feel like a genius”.
IFLSE1 was a good time. But (Goodhart’s Law), we began to optimize for a proxy for truth (the feeling of having something explained), rather than truth itself.
This led to a degeneration: the IFLSE2. We began to confuse people who could explain things with people who understood them; and being able to understand something with knowing it was true.
The best example of IFLSE2 is the pseudo-evolutionary psych world, which will, for some people, never get old.
If you confuse understanding, explanation, and truth you will often come a cropper. Traders know this, and it’s a reason why @nntaleb was such a revelation (for some). Fat Tony doesn’t care about the quality of your explanation.
But in many things—indeed, in my opinion, the most important things—we aren’t kicked in the ass by reality enough. People believe ridiculous things simply because they are part of things that (look like) good explanations, and that give a feeling of understanding.
Another problem comes from the TED talk era, which has infected university teaching. Students are given the task of evaluating professors, and use the explanation heuristic.
Narratives are often very explainy. A satisfying story includes an explanation. Comedians play with this (Dan Dennett’s _Inside Jokes_ is one version of this thesis). A joke is a story with (inter alia) a surprising explanation.
This is why a student feels like he’s learning more from Joe Rogan than his mumbly stats TA. Even worse, he comes to believe that Rogan knows more than his stats TA.
Joe is IFLSE3. Bad science journalism is dying, because people can’t read another airport summary of social psych—it’s not worth it, when you have a comedian who can provide the same feeling with more charisma.
I remember the first time I was with a truly great explainer of quantum field theory (I won’t embarrass this person by naming names). It’s utterly amazing, moving experience. BUT!
I’m sure I had encountered many great explainers of QFT before that point. I had a year in front of Sidney Coleman! But I didn’t understand it yet, and so it washed over me. Physics itself is a great teaser apart...
We all knew the guy (usually a guy) who could explain why the answer on the problem set was the right one—often in a super-satisfying way. But he was rarely the one who got it first (found the key to unlock it).
This is a big danger, both intellectually and morally, because it is tempting to judge truth or understanding on the basis of how good the person is at explaining.
Socrates (paging @Plato4Now!) teases these things apart very well and in different ways over the course of the dialogues. He is often in the business of puncturing explanations—things that everyone around him considers satisfying.
Dialectic replaces explanation with (at different points) aporia, recollection, and insight. The IFLSE3 rejects the first as weakness (or even, in coded form, effeminate), the second as unscientific, the third as undemocratic.
I imagine pre-Socratic Greece as an explanation-saturated world; a time before both dialectics and empiricism. Socrates doesn’t come to *explain* things to Athens, but to put explanation in its proper place, to have it guided by yet deeper matters.
In the end, perhaps the skill Socrates urges on us is a sensitivity to the differences between the feeling of understanding something, of having it explained, and of knowing it to be true.

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More from @SimonDeDeo

17 Oct
Modal logic is fun, and I’m always disappointed that philosophers and logicians didn’t go for the obvious graph theory you can do—particularly if you allow for heterogeneity.

(Amusingly enough, this is a plot point in Neal Stephenson’s _Anathem_.) 🧵
Briefly: represent worlds as nodes, and directed arrows as the neighbor relation. An arrow from world A to B implies that something true in B is “possible” in A. Then all the logics (S5, etc) amount to graph theoretic constraints.
Then you can do fun things. There are logics with worlds where “necessarily p” doesn’t imply p; they are worlds without a self-loop, worlds that are not possible to themselves, where p can be both true and not possible.
Read 16 tweets
16 Oct
Excellent news—The Economist has released, as open source, a fully Bayesian election model as an alternative to Nate Silver’s (IMO increasingly pundit-oriented) forecasts.

Bayesian models are not Black Swan-proof but *are* the best possible way to summarize the “known unknowns”.
God bless The Economist.
Backtesting says the model has Clinton in 2016 at only ~70% win probability—the best accuracy I’ve seen. If this didn’t have @StatModeling’s name on it, I’d just assume that was fake and post hoc hacked.
Read 7 tweets
15 Oct
Important: Twitter could have shadowbanned the NY Post story: demphasized it, shown it in fewer timelines, placed it near other, more distracting content. These techniques are basic to monetizing content.

Instead, they went public with a hard ban and created a Streisand Effect…
Whatever you think about censoring content on a commercial platform, it's important not to lose sight of the fact that Jack's goal is not to "fight fake news", "improve discourse", or "shut down the right". That's a distraction.
The goal is, rather, to *appear* to other elites to be doing one or another of these things.

In the extreme capitalism we have today, you have to understand the social goals, and the psychology, of the oligarchs to make sense of their actions.
Read 13 tweets
15 Oct
And yet, it is—a commons that we contribute to, engage with, invest in. The ownership structure is completely detached from what makes it succeed. 🧵
Perhaps one of the least-acknowledged aspects of online life is the distinction between where value comes from (the users) and where it goes (the owners, a few elites). We still think of Twitter and Facebook with the same frameworks we understand USENET or Wikipedia.
The algorithms underneath Twitter guide and construct an environment over which we have very little control. It *is* the Matrix, in a way that previous systems were not. A neutering of bottom up power.
Read 15 tweets
14 Oct
In my 1990s cyberpunk phase, we said the Internet interprets censorship as damage, and routes around it... (🧵)
What we did not anticipate was that the underlying protocols would accumulate layer upon layer and that we would be sending packets on a layer (Twitter) without an RFC.
In retrospect, the RFC was an institution just as much as Twitter, the Post, or the House Judiciary Committee. Nor did public key encryption change much—VeriSign, not the user, holds the keys.
Read 9 tweets
14 Oct
Enjoyed @david_kipping's playful Bayesian analysis of the simulation argument. One missing piece is making lambda a fixed number (a parous universe produces lambda simulations), which I think it should be a Poisson distribution...
Depending on parameters, this may interact with the exponential proliferation of universes at each generation, and of course, if correctly balanced (@Jp_odwyer knows where this is going...), that would make the distribution scale free.
It is hard to think of a more @sfiscience / Interplanetary Festival topic than the question "are the epistemic parameters of the Universe poised at a phase transition, implying a scale-free distribution over simulated realities."
Read 5 tweets

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