When do you need traditions? – A hypothesis

[epistemic status: speculation about domains I have little contact with, and know little about]

I’m rereading Samo Burja’s draft, Great Founder Theory. In particular, I spent some time today thinking about living, dead, and lost traditions and chains of Master-Apprenticeship relationships.

It seems like these chains often form the critical backbone of a continuing tradition (and when they fail, the tradition starts to die). Half of Nobel winners are the students of other Noble winners.

But it also seems like there are domains that don’t rely, or at least don’t need to rely on the conveyance of tacit knowledge via Master-Appreticeship relationships.

For instance, many excellent programmers are self-taught. It doesn’t seem like our civilization’s collective skill in programming depends on current experts passing on their knowledge to the next generation via close in-person contact. As a thought experiment, if all current programers disappeared today, but the computers and educational materials remained, I expect we would return to our current level of collective programing skill within a few decades.

In contrast, consider math. I know almost nothing about higher mathematics, but I would guess that if all now-living mathematicians disappeared, they’ed leave a lot of math, but progress on the frontiers of mathematics would halt, and it would take many years, maybe centuries, for mathematical progress to catch up to that frontier again. I make this bold posit on the basis of the advice I’ve heard (and I’ve personally verified) that learning from tutors is way more effective than learning just from textbooks, and that mathematicians do track their lineages.

In any case, it doesn’t seem like great programers run in lineages the way that Nobel Laureates do.

This is in part because programming in particular has some features that lends itself to autodidactictry: in particular, a novice programer gets clear and immediate feedback: his/her code either compiles or it doesn’t. But I don’t think this is the full story.

Samo discusses some of the factors that determine this difference in his document: for instance, traditions in domains that provide easy affordance for “checking work” against the territory  (such as programming) tend to be more resilient.

But I want to dig into a more specific difference.


A domain of skill entails some process that when applied, produces some output.

Gardening is the process, fruits are the output. Carpentry (or some specific construction procedure) is the process, the resulting chair is the output.  Painting is the process, the painting is the output.

To the degree that the output is or embodies the generating process, master-apprenticeship relationships are less necessary.

It’s a well trodden trope that a program is the programmer’s thinking about a problem. (Paul Graham in Holding a Program in One’s Head: “Your code is your understanding of the problem you’re exploring.“) A comparatively large portion of a programmer’s thought process is represented in his/her program (including the comments). A novice programer, looking at a program written by a master, can see not just what a well-written program looks like, but also, to a large degree, what sort of thinking produces a well-writen program. Much of the tacit knowledge is directly expressed in the final product.

Compare this to say, a revolutionary scientist. A novice scientist might read the papers of elite groundbreaking science, and the novice might learn something, but so much of the process – the intuition that the topic in question was worth investigating, the subtle thought process that led to the hypothesis, the insight of what experiment would elegantly investigate that hypothesis – are not encoded in the paper, and are not legible to the reader.

I think that this is a general feature of domains. And this feature is predictive of the degree to which skill in a given domain relies strongly on traditions of Master- Apprenticeship.

Other examples:

I have the intuition, perhaps false (are there linages of award-winning novelist the way there are linages of Nobel laureates?), that novelists mostly do not learn their craft in apprenticeships to other writers. I suggest that writing is like programing: largely self-taught, except in the sense that one ingests and internalizes large numbers of masterful works. But enough of the skill of writing great novels is contained in the finished work that new novelists can be “trained” this way.

What about Japanese wood-block printing? From the linked video, it seems as if David Bull received about an hour of instruction in wood carving once every seven years or so. But those hours were enormously productive for him. Notably, this sort of wood-carving is a step removed from the final product: one carves the printing block, and then uses the block to make a print. Looking at the finished block, it seems, does not sufficiently convey the techniques used for creating the block. But on top of that the block is not the final product, only an intermediate step. The novice outside of an apprenticeship may only ever see the prints of a master-piece, not the blocks that make the prints.

Does this hold up at all?

That’s the theory. However, I can come up with at least a few counter proposals and confounding factors:

Countertheory: The dominating factor is the age of the tradition. Computer Science is only a few decades old, so recreating it can’t take more than a few decades. Let it develop for a few more centuries (without the advent of machine intelligence or other transformative technology), and the Art of Programming will have progressed so far that it does depend on Master/Apprentice relationships, and the loss of all living programers would be as much as a hit as the loss of all living mathematicians.

This doesn’t seem like it explains novelists, but maybe “good writing” is mostly a matter of fad? (I expect some literary connoisseurs would leap down my throat at that. In any case, it doesn’t seem correct to me.)

Confounder: economic incentive: If we lost all masters of Japanese wood-carving, but there was as much economic incentive for the civilization to remaster it as there would be for remastering programming, would it take any longer? I find that dubious.

Why does this matter? 

Well for one thing, if you’re in the business of building traditions to last more than a few decades, it’s pretty important to know when you will need to institute close-contact lineages.

Separately, this seem relevant whenever one is hoping to learn from dead masters.

Darwin surely counts among the great scientific-thinkers. He successfully abstracted out a fundamental structuring principle of the natural world. As someone interested in epistemology, it seems promising to read Darwin, in order to tease out how he was thinking. I was previously planning to read the Origins of Species. Now, it seems much more fruitful to read Darwin’s notebooks, which I expect to contain more of his process than his finished works do.




Initial Comparison between RAND and the Rationality Cluster

I’m currently reading The Doomsday Machine: Confessions of a Nuclear War Planner by Daniel Ellsberg (the man who leaked the Pentagon Papers), on the suggestion of Anna Salamon.

I’m interested in the cold war planning communities because they might be relevant to the sort of thinking that is happening, or needs to happen, around AI x-risk, today. And indeed, there are substantial resemblances between the RAND corporation and at least some of the orgs that form the core of the contemporary x-risk ecosystem.

For instance…

A narrative of “saving the world”:

[M]y colleagues were driven men. They shared a feeling—soon transmitted to me—that we were in the most literal sense working to save the world. A successful Soviet nuclear attack on the United States would be a catastrophe, and not only for America.

A perception of the inadequacy of the official people in power:

But above all, precisely in my early missile-gap years at RAND and as a consultant in Washington, there was our sense of mission, the burden of believing we knew more about the dangers ahead, and what might be done about them, than did the generals in the Pentagon or SAC, or Congress or the public, or even the president. It was an enlivening burden.

We were rescuing the world from our Soviet counterparts as well as from the possibly fatal lethargy and bureaucratic inertia of the Eisenhower administration and our sponsors in the Air Force.

Furthermore, a major theme of the book is the insanity of US Nuclear Command and Control polices.  Ellsberg points repeatedly at the failures of decision-making and morality amongst the US government.

A sense of intellectual camaraderie:

In the middle of the first session, I ventured—though I was the youngest, assigned to be taking notes, and obviously a total novice on the issues—to express an opinion. (I don’t remember what it was.) Rather than showing irritation or ignoring my comment, Herman Kahn, brilliant and enormously fat, sitting directly across the table from me, looked at me soberly and said, “You’re absolutely wrong.” A warm glow spread throughout my body. This was the way my undergraduate fellows on the editorial board of the Harvard Crimson (mostly Jewish, like Herman and me) had routinely spoken to each other; I hadn’t experienced anything like it for six years. At King’s College, Cambridge, or in the Society of Fellows, arguments didn’t remotely take this gloves-off, take-no-prisoners form. I thought, “I’ve found a home.”

Visceral awareness of existential failure:

At least some of the folks at RAND had a visceral sense of the impending end of the world. They didn’t feel like they were just playing intellectual games.

I couldn’t believe that the world would long escape nuclear holocaust. Alain Enthoven and I were the youngest members of the department. Neither of us joined the extremely generous retirement plan RAND offered. Neither of us believed, in our late twenties, we had a chance of collecting on it.

That last point seems particularly relevant. Folks in our cluster invest in the development and practice of tools like IDC in part because of the psychological pressures that accompany the huge stakes of x-risk.

At least some of the “defense intellectuals” of the Cold War were under similar pressures.[1]

For this reason, the social and intellectual climate around RAND and similar organizations during the Cold War represents an important case study, a second data point for comparison to our contemporaries working on existential risk.

How did RAND employees handle the psychological pressures? Did they spontaneously invent strategies for thinking clearly in the face of the magnitude of the stakes? If so, can we emulate those strategies? If not, does that imply that their thinking about their work was compromised? Or does it suggest that our emphasis on psychological integration methods are misplaced?

And perhaps most importantly, what mistakes did they make? Can we use their example to foresee similar mistakes of our own and avoid them?

[1] – Indeed, it seems like they were under greater pressures. There’s a sense of franticness and urgency that I feel in Ellsberg’s description that I don’t feel around MIRI. But I think that this is due to the time horizons that RAND and co. were operating under compared to the those that MIRI is operating under. I expect that as we near the arrival of AGI, there will be a sense of urgency and psychological pressure that is just as great and greater than that of the cold war planners.

End note: In addition to all these more concrete correlations, there’s also the intriguing intertwining of existential risk and decision theory in both of the data points of nuclear war planning and AI safety. I wonder if that is merely coincidence or represents some deeper connection.