Distil­la­tion & Pedagogy

TagLast edit: 21 Aug 2020 22:31 UTC by Raemon

Distillation is the process of taking a complex subject, and making it easier to understand. Pedagogy is the method and practice of teaching. A good intellectual pipeline requires not just discovering new ideas, but making it easier for newcomers to learn them, stand on the shoulders of giants, and discover even more ideas.

Chris Olah, founder of, writes in his essay Research Debt:

Programmers talk about technical debt: there are ways to write software that are faster in the short run but problematic in the long run. Managers talk about institutional debt: institutions can grow quickly at the cost of bad practices creeping in. Both are easy to accumulate but hard to get rid of.

Research can also have debt. It comes in several forms:

  • Poor Exposition – Often, there is no good explanation of important ideas and one has to struggle to understand them. This problem is so pervasive that we take it for granted and don’t appreciate how much better things could be.

  • Undigested Ideas – Most ideas start off rough and hard to understand. They become radically easier as we polish them, developing the right analogies, language, and ways of thinking.

  • Bad abstractions and notation – Abstractions and notation are the user interface of research, shaping how we think and communicate. Unfortunately, we often get stuck with the first formalisms to develop even when they’re bad. For example, an object with extra electrons is negative, and pi is wrong.

  • Noise – Being a researcher is like standing in the middle of a construction site. Countless papers scream for your attention and there’s no easy way to filter or summarize them.Because most work is explained poorly, it takes a lot of energy to understand each piece of work. For many papers, one wants a simple one sentence explanation of it, but needs to fight with it to get that sentence. Because the simplest way to get the attention of interested parties is to get everyone’s attention, we get flooded with work. Because we incentivize people being “prolific,” we get flooded with a lot of work… We think noise is the main way experts experience research debt.

The insidious thing about research debt is that it’s normal. Everyone takes it for granted, and doesn’t realize that things could be different. For example, it’s normal to give very mediocre explanations of research, and people perceive that to be the ceiling of explanation quality. On the rare occasions that truly excellent explanations come along, people see them as one-off miracles rather than a sign that we could systematically be doing better.

See also Scholarship and Learning, and Good Explanations.

Re­search Debt

Elizabeth15 Jul 2018 19:36 UTC
24 points
2 comments1 min readLW link

How to teach things well

Neel Nanda28 Aug 2020 16:44 UTC
74 points
13 comments15 min readLW link

[Question] What are Ex­am­ples of Great Distil­lers?

adamShimi12 Nov 2020 14:09 UTC
32 points
12 comments1 min readLW link

Learn­ing how to learn

Neel Nanda30 Sep 2020 16:50 UTC
25 points
0 comments15 min readLW link

In­fra-Bayesi­anism Unwrapped

adamShimi20 Jan 2021 13:35 UTC
19 points
0 comments24 min readLW link

DARPA Digi­tal Tu­tor: Four Months to To­tal Tech­ni­cal Ex­per­tise?

JohnBuridan6 Jul 2020 23:34 UTC
159 points
17 comments7 min readLW link

Ex­pan­sive trans­la­tions: con­sid­er­a­tions and possibilities

ozziegooen18 Sep 2020 15:39 UTC
43 points
15 comments6 min readLW link

TAPs for Tutoring

Mark Xu24 Dec 2020 20:46 UTC
20 points
2 comments5 min readLW link

Ex­per­tise and advice

John_Maxwell27 May 2012 1:49 UTC
25 points
4 comments1 min readLW link

Ex­plain­ers Shoot High. Aim Low!

Eliezer Yudkowsky24 Oct 2007 1:13 UTC
78 points
34 comments1 min readLW link

Avoid Un­nec­es­sar­ily Poli­ti­cal Examples

Raemon11 Jan 2021 5:41 UTC
102 points
42 comments3 min readLW link

Dis­cov­ery fic­tion for the Pythagorean theorem

riceissa19 Jan 2021 2:09 UTC
9 points
1 comment4 min readLW link

In­ver­sion of the­o­rems into defi­ni­tions when generalizing

riceissa4 Aug 2019 17:44 UTC
23 points
3 comments5 min readLW link

Think like an ed­u­ca­tor about code quality

adamzerner27 Mar 2021 5:43 UTC
42 points
8 comments8 min readLW link

99% shorter

philh27 May 2021 19:50 UTC
14 points
0 comments6 min readLW link

An Ap­pren­tice Ex­per­i­ment in Python Programming

konstell4 Jul 2021 3:29 UTC
65 points
4 comments9 min readLW link

Does any­one use ad­vanced me­dia pro­jects?

ryan_b20 Jun 2018 23:33 UTC
33 points
5 comments1 min readLW link

Teach­ing the Unteachable

Eliezer Yudkowsky3 Mar 2009 23:14 UTC
49 points
18 comments6 min readLW link

The Fun­da­men­tal Ques­tion—Ra­tion­al­ity com­puter game design

Kaj_Sotala13 Feb 2013 13:45 UTC
61 points
68 comments9 min readLW link

Zetetic explanation

Benquo27 Aug 2018 0:12 UTC
87 points
138 comments6 min readLW link

Pa­ter­nal Formats

abramdemski9 Jun 2019 1:26 UTC
50 points
35 comments2 min readLW link

Teach­able Ra­tion­al­ity Skills

Eliezer Yudkowsky27 May 2011 21:57 UTC
72 points
263 comments1 min readLW link

Five-minute ra­tio­nal­ity techniques

sketerpot10 Aug 2010 2:24 UTC
71 points
237 comments2 min readLW link

Just One Sentence

Eliezer Yudkowsky5 Jan 2013 1:27 UTC
58 points
142 comments1 min readLW link

Me­dia bias

PhilGoetz5 Jul 2009 16:54 UTC
39 points
47 comments1 min readLW link

The RAIN Frame­work for In­for­ma­tional Effectiveness

ozziegooen13 Feb 2019 12:54 UTC
33 points
12 comments6 min readLW link

The Up-Goer Five Game: Ex­plain­ing hard ideas with sim­ple words

Rob Bensinger5 Sep 2013 5:54 UTC
44 points
82 comments2 min readLW link

Ra­tion­al­ity Games & Apps Brainstorming

lukeprog9 Jul 2012 3:04 UTC
42 points
59 comments2 min readLW link

How not to be a Naïve Computationalist

diegocaleiro13 Apr 2011 19:45 UTC
38 points
36 comments2 min readLW link

Dense Math Notation

JK_Ravenclaw1 Apr 2011 3:37 UTC
33 points
23 comments1 min readLW link

Numer­acy ne­glect—A per­sonal postmortem

vlad.proex27 Sep 2020 15:12 UTC
77 points
29 comments9 min readLW link

Moved from Moloch’s Toolbox: Dis­cus­sion re style of lat­est Eliezer sequence

habryka5 Nov 2017 2:22 UTC
7 points
1 comment3 min readLW link

Short Primers on Cru­cial Topics

lukeprog31 May 2012 0:46 UTC
35 points
24 comments1 min readLW link

Great Explanations

lukeprog31 Oct 2011 23:58 UTC
28 points
115 comments2 min readLW link

A LessWrong “ra­tio­nal­ity work­book” idea

jwhendy9 Jan 2011 17:52 UTC
25 points
26 comments3 min readLW link

De­bug­ging the student

adamzerner16 Dec 2020 7:07 UTC
40 points
7 comments4 min readLW link

Ret­ro­spec­tive on Teach­ing Ra­tion­al­ity Workshops

Neel Nanda3 Jan 2021 17:15 UTC
57 points
2 comments31 min readLW link

[Question] What cur­rents of thought on LessWrong do you want to see dis­til­led?

ryan_b8 Jan 2021 21:43 UTC
48 points
17 comments1 min readLW link
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