Paul Graham starts with this framework:

The kids in the upper left quadrant, the aggressively conventional-minded ones, are the tattletales. They believe not only that rules must be obeyed, but that those who disobey them must be punished.

The kids in the lower left quadrant, the passively conventional-minded, are the sheep. They’re careful to obey the rules, but when other kids break them, their impulse is to worry that those kids will be punished, not to ensure that they will.

The kids in the lower right quadrant, the passively independent-minded, are the dreamy ones. They don’t care much about rules and probably aren’t 100% sure what the rules even are.

And the kids in the upper right quadrant, the aggressively independent-minded, are the naughty ones. When they see a rule, their first impulse is to question it. Merely being told what to do makes them inclined to do the opposite.

He points out that universities used to be places where the aggressively independent-minded were protected from the aggressively conventional-minded. In my terms, universities were a haven for heretics, not the wellspring of the religion that is animated by the identification and persecution of heretics.

I believe that in order to have a cohesive society, you need some enforcement of conformity. But the extend and severity of that enforcement has to have limits. I think Graham’s essay makes that same point.

Russ Roberts talks with Glenn Loury, who says,

the descendants of American slaves, again, taken as a whole, are the richest and most powerful and influential population of African descent on the planet.

So, the idea that we want to scrap the [capitalist] system and start from scratch–as I say, I think it’s a very mischievous idea.

Later, Loury says,

if you brought some of the empathy for the public servants, who were teachers, over to a sense of empathy for the extremely difficult job of being a police officer in an American city, and you brought some of the sense of judgment and insistence upon accountability that is reflexively invoked when we talk about police officers over to talking about how we want to think about our public servants who are providing educational services, I think we’d all be better off.

And of course there is more.

To some people it looks that way, but I am going to say no. The key issue, in my view, is the pursuit of excellence. Can great thinkers, engineers, and entrepreneurs still pursue excellence, or are they being stifled by ankle-biting social justice activists?

I think that the pursuit of excellence is still possible. If the New York Times fails as an outlet, there is still Quillette. If many academic departments become mediocre, excellence will find its way to other departments or the corporate sector or perhaps privately-funded research institutes. If the top tech firms stifle their best talent, venture capitalists will find better uses for them.

I worry about Scott Alexander. His excellence could be harder to pursue if his worst fears about the NYT revealing his name are realized. But on the whole, I think that the ability to pursue excellence is going to still be here.

He wrote recently,

Qualified and expert researchers in such fields are already in great danger of being pushed aside by activists of the proper opinion. The rest of us will pay in the longer run, when we no longer have the will or the capacity to make use of the rare talents that make people highly competent and productive as scientists, technological innovators, engineers or mathematicians. Wake up, STEM denizens: your famous immunity to political concerns will not protect you against what is headed your way fast over the next five or so years.

A commenter points to John Tooby, Leda Cosmides, and Michael E. Price (2006)

We think that human evolutionary history has equipped the human mind with specialized psychological adaptations designed to realize gains in trade that occur both in 2-party exchanges and in n-party exchanges, including collective actions. We believe that the specific characteristics of these mechanisms (e.g. cheater detection circuits) reflect the ancestrally recurrent structure of these adaptive problems (the existence of payoffs to cheating). . .we
think that many of the ‘irrational’ behavioral expressions of these mechanisms (such as voting behavior or donating blood) will come to be recognized as engineering byproducts of these functional designs when they are activated outside of the ancestral envelope of conditions for which they were designed.

Later:

the greater the number of participants is, the greater the comparative advantage of conservatively perpetuating pre-existing arrangements will be, however beneficial or flawed those pre-existing arrangements were.

Because it is difficult to foster cooperation among large numbers of people, we rightly seek to preserve systems that work.

We feel pleasure upon becoming a valued member of a group, satisfaction in its creation and successes, and sadness at its dissipation.

Think of finding a job or losing a job.

Still later:

we think that the human mind contains an evolved, functionally specialized motivational mechanism that, when exposed to a situation of personal exploitation, generates a punitive sentiment toward the agent that is deriving an unfair advantage in an exchange

Hence the furor over “price gouging.”

Punitive strategists switch on the productive possibilities of the groups they are in, unleashing collective efforts that would otherwise be inhibited by the presence of free riders. This happens because the presence of punitive strategists in potential exchange interactions repels free riders, causing them either to avoid such interactions or to become (facultatively, in the presence of punitive strategists) behavioral cooperators. Because free riders avoid punitive strategists, punitive strategists will far more often find themselves in groups without free riders

Many people feel sentiments according to the following social exchange logic: I will give up the benefits of violating this moral rule if others in my social world do. If I followed the rule, and you did not, I have been cheated by you. The more others cheat on a rule I follow, the more exploited I feel, and the more tempted I am to discontinue following the rule when it is costly to do so

A podcast, with a transcript of Martin Gurri and me discussing the breakdown in social truth. I think it was a good discussion.

1. Michael Huemer writes,

I started thinking about other very important, general epistemological lessons. Lessons that most human beings have not gotten, which has led to lots of other errors. So here’s one; this probably wouldn’t be a good single sentence to leave to the future (since it requires further explanation), but it’s still one of the most important facts of epistemology: Your priors are too high.

Equivalently, he writes

Almost all beliefs require evidence, and they require a lot of it. Way more than you’re thinking.

One consequence of “your priors are too high” is that your mind is too hard to change.

2. Edward R. Dougherty writes,

Four conditions must be satisfied to have a valid scientific theory: (1) There is a mathematical model expressing the theory. (2) Precise relationships, known as “operational definitions,” are specified between terms in the theory and measurements of corresponding physical events. (3) There are validating data: there is a set of future quantitative predictions derived from the theory and measurements of corresponding physical events. (4) There is a statistical analysis that supports acceptance of the theory, that is, supports the concordance of the predictions with the physical measurements—including the mathematical theory justifying the application of the statistical methods.

The theory must be expressed in mathematics because science involves relations between measurable quantities and mathematics concerns such relations. There must also be precise relationships specified between a theory and corresponding observations; otherwise, the theory would not be rigorously connected to physical phenomena. Third, observations must confirm predictions made from the theory. Lastly, owing to randomness, concordance of theory and observation must be characterized statistically.

…Practically speaking, a leader need not know the mathematical particulars of a theory, but he must understand the validation process: what predictions are derived from the theory and to what extent have those predictions agreed with observations?

This is not to argue that leadership be confined to scientists and engineers, only that education include serious scientific, mathematical, and statistical courses. Certainly, one cannot expect good political leadership from someone ignorant of political philosophy, history, or economics, or from someone lacking the political skill to work productively amid differing opinions. The basic point is that good decision-making in a technical civilization requires fundamental knowledge of scientific epistemology.

…To validate a deterministic model, one can align the model and experiment with various initial states and check to see if predictions and observations agree. There might be some experimental variation, but in principle this can be reduced arbitrarily and slight disagreements ignored.

The situation with stochastic models is completely different. For a single initial condition, there are many destination states and these are described via the model by a probability distribution giving the likelihoods of ending up in different states. An experiment consists of many observation trajectories from a single initial state and the construction of a histogram giving the distribution of the experimental outcomes relative to that state. Validation concerns the degree of agreement between the theoretical, model-derived probability distribution and the data-derived histogram. Acceptance or rejection of the theory depends on some statistical test measuring the agreement between the two curves—and here it should be recognized that there is no universally agreed upon test.

…Confronting the problems of complexity, validation, and model uncertainty, I have previously identified four options for moving ahead: (1) dispense with modeling complex systems that cannot be validated; (2) model complex systems and pretend they are validated; (3) model complex systems, admit that the models are not validated, use them pragmatically where possible, and be extremely cautious when interpreting them; (4) strive to develop a new and perhaps weaker scientific epistemology.14

The first option would entail not dealing with key problems facing humanity, and the second, which seems popular, at least implicitly, is a road to mindless and potentially dangerous tinkering. Option three is risky because it requires operating in the context of scientific ignorance; but used conservatively with serious thought, it may allow us to deal with critical problems. Moreover, option three may facilitate productive thinking in the direction of option four, a new epistemology that maintains a rigorous formal relationship between theory and phenomena.

3. https://slatestarcodex.com/2020/05/18/coronalinks-5-18-20-when-all-you-have-is-a-hammer-everything-starts-looking-like-a-dance/