Source: Why Tacit Knowledge is More Important Than Deliberate Practice | Commonplace Blog, by Cedric Chin
Tacit knowledge is knowledge that cannot be captured through words alone. … tacit knowledge instruction happens through things like imitation, emulation, and apprenticeship. You learn by copying what the master does, blindly, until you internalise the principles behind the actions.
If you are a knowledge worker, tacit knowledge is a lot more important to the development of your field of expertise than you might think.
I don’t mean to say that Hieu or the senior software engineer couldn’t explain their judgment, or that they couldn’t make explicit the principles they used to evaluate the tradeoffs between a dozen or so variables: they could. My point is that their explanations would not lead me to the same ability that they had.
Why is this the case? Well, take a look at the conversation again. When I pushed these people on their judgments, they would try to explain in terms of principles or heuristics. But the more I pushed, the more exceptions and caveats and potential gotchas I unearthed.
Could it — in principle — be possible to externalise tacit knowledge into a list of instructions? … The consensus answer to that question seems to be: “Yes, in principle it is possible to do so. In practice it is very difficult.” My take on this is that it is so difficult that we shouldn’t even bother
Source: The Value of Grey Thinking | Farnam Street
Reality is all grey area. All of it. There are very few black and white answers and no solutions without second-order consequences.
It’s only once you can begin divorcing yourself from good-and-bad, black-and-white, category X&Y type thinking that your understanding of reality starts to fit together properly. Putting things on a continuum, assessing the scale of their importance and quantifying their effects, understanding both the good and the bad, is the way to do it. Understanding the other side of the argument better than your own, a theme we hammer on ad nauseum, is the way to do it. Because truth always lies somewhere in between, and the discomfort of being uncertain is preferable to the certainty of being wrong.
quantitative thinking isn’t really about math; it’s about the idea that The dose makes the poison. … Nearly all things are OK in some dose but not OK in another dose. That is the way of the world, and why almost everything connected to practical reality must be quantified, at least roughly.
Source: “Teacher Effects on Student Achievement and Height: A Cautionary Tale”, NBER Working Paper No. 26480, by Marianne Bitler, Sean Corcoran, Thurston Domina, Emily Penner
PDF: Teacher Effects on Student Achievement and Height: A Cautionary Tale
Estimates of teacher “value-added” suggest teachers vary substantially in their ability to promote student learning. … In this paper, we conduct a new test of the validity of value-added models. Using administrative student data from New York City, we apply commonly estimated value-added models to an outcome teachers cannot plausibly affect: student height. We find the standard deviation of teacher effects on height is nearly as large as that for math and reading achievement, raising obvious questions about validity.
Source: How to do hard things, by David R. MacIver
“The Fully General System For Learning To Do Hard Things”. It’s a useful conceptual framework for how to get better at things that you currently find difficult. … The goal of the system is not to save you work, it’s to ensure that the work you do is useful.
The Single-Loop System
When you know what success looks like but cannot currently achieve it, the system works as follows:
- Find something that is like the hard thing but is easy.
- Modify the easy thing so that it is like the hard thing in exactly one way that you find hard.
- Do the modified thing until it is no longer hard.
- If you get stuck, do one of the following:
- Go back to step 3 and pick a different way in which the problem is hard.
- Recursively apply the general system for learning to do hard things to the thing you’re stuck on.
- Go ask an expert or a rubber duck for advice.
- If you’re still stuck after trying the first three, it’s possible that you may have hit some sort of natural difficulty limit and may not be able to make progress.
- If the original hard thing is now easy, you’re done. If not, go back to step 2.
The reason this works much better than just practicing the hard thing is because it gives you a much more direct feedback loop. There is exactly one aspect of the problem at any time that you are trying to get better at, and you can focus on that aspect to the exclusion of all else. When you are practicing something that is difficult in multiple ways, you will be bad at it in all of those ways. More, you will be worse at it in all of those ways than you would be if you’d tried them on their own. Additionally, when you fail you have to do a complicated root cause analysis to figure out why.
Instead, by isolating one aspect of the problem that is difficult, you will fairly rapidly improve, or hit the limits of your ability.
The Double-Loop System
If you don’t know what success looks like, you need to do double loop learning, where you mix improving your understanding of the problem with your ability to execute the solution.
- Apply the single loop system to the problem of improving your understanding of the problem space (e.g. consume lots of examples and learn to distinguish good from bad) in order to acquire a sense of good taste.
- Apply the single loop system to the problem of doing well according to your own sense of good taste.
- Get feedback on the result from others. Do they think you did it well? If yes, great! You’re good at the thing. If no, either improve your sense of taste or theirs. If you choose yours, go back to step 1 with the new example. If you choose theirs, apply the single loop system to the hard problem of convincing others that your thing is good.
Source: The Uncharity of College: The Big Business Nobody Understands, by Conrad Bastable
How Colleges Make More Money Than God By Giving It Away
A very brief summary of what’s to come in this essay:
- College degrees are more valuable than ever in post-industrial economies, so applicants to top-tier schools are up 240% over the last 25 years
- Meanwhile, available spots at top-tier colleges in America have increased just 2% over the last 25 years
- Microeconomics 101: Fixed Supply + Increased Demand = Increased Price
- That’s the obvious part
- The non-obvious part is that this is intentional
- Because the Charity-status ( 501(c)(3) )of Colleges in America depends on more-than-half of their students being unable to afford the education (read: “receiving financial aid”)
- That Charity-status protects the Investment Returns of College Endowments from Uncle Sam & the IRS
- Investment Returns Compound over time, and there is no more powerful force on Earth — anyone not playing the game to maximize Compound-returns will lose to everyone who is
- Investment Returns already generate more revenue than undergrad tuition income at: Princeton (911% more), Harvard (529% more), Yale (254% more), MIT (118% more), Stanford (115% more), Brown (29% more), Duke (13% more), Dartmouth (9% more), and U Chicago (6% more)
- Undergrad tuition brings in just 10% – 20% of total revenue at the Ivy League / Top-10 schools not listed above. Undergrad Tuition is not more than a quarter of revenue at any of these schools.
- Thus: if Colleges want to keep their Investment Returns tax-free, Tuition MUST remain unaffordable for at least 50% of undergrads
Tuition is meaningless income to MIT now — a drop in the bucket, just 3.2% of their income comes from undergraduate tuition — but so long as the Tuitions are unaffordable for 58% of undergraduates, the Investment returns on $16.4 billion dollars are tax free.