Thinking about understanding knowledge as climbing a mountain. Every time novel work happens, the mountain gets a little bit taller.
Mathematics is a striking example of this. For centuries, countless minds have climbed the mountain range of mathematics and laid new boulders at the top. Over time, different peaks formed, built on top of particularly beautiful results. Now the peaks of mathematics are so numerous and steep that no person can climb them all.
Yes, the climb is hard but it could be easier. Let’s build staircases for the mountains.
How do we reduce interpretive labour for learners?
# Debt in research
- Poor exposition -> no good explanation of ideas and concepts
- Undigested ideas -> it takes effort to polish ideas, developing the right analogies, language, and ways of thinking
- Bad abstractions and notation -> abstractions and notation are the user interface of research. To have bad notation is to have bad ways to interact with the underlying knowledge
- Noise -> there’s too much new progress being made each day. How do we choose what to focus on?
Not just about poorly explained ideas, but rather the lack of ideas being digested and worked through in public (communal messiness of thought). How can we create better abstractions, notations, and visualizations to improve how we interact and interface with ideas?
Part of thinking is having a conversation with ourselves.
“Distillation is also hard. It’s tempting to think of explaining an idea as just putting a layer of polish on it, but good explanations often involve transforming the idea. This kind of refinement of an idea can take just as much effort and deep understanding as the initial discovery.”
So who should distill knowledge?
- Needs to be more than one person: too much knowledge to polish every idea from scratch
- Cannot be less skilled non-experts: refining and explaining ideas requires creativity and deep understanding
Is distillation a form of maintenance?
# Where are the Distillers?
The research distiller is an integral role for a healthy research community, yet almost no one is filling it right now.
Is it because people want their work to look hard? Do people not enjoy distillation? While both of these may play a small part, the biggest part is malalignment of incentives (relevant to incentives in open source maintenance).