The First Circle

Epistemic Status: Squared

The following took place at an unconference about AGI in February 2017, under Chatham House rules, so I won’t be using any identifiers for the people involved.

Something that mattered was happening.

I had just arrived in San Francisco from New York. I was having a conversation. It wasn’t a bad conversation, but it wasn’t important.

To my right on the floor was a circle of four people. They were having an important conversation. A real conversation. A sacred conversation.

This was impossible to miss. People I deeply respected spoke truth. Their truth. Important truth, about the most important question – whether and when AGI would be developed, and what we could do about that to change that date, or to ensure a good outcome. Primarily about the timeline. And that truth was quite an update from my answer, and from my model of what their answers would be.

I knew we were, by default, quite doomed. But not doomed so quickly!

They were unmistakably freaking out. Not in a superficial way. In a deep, calm, we are all doomed and we don’t know what to do about it kind of way. This freaked me out too.

They talked in a different way. Deliberate, careful. Words chosen carefully.

I did not know the generation mechanism. I did know that to disturb the goings on would be profane. So I sat on a nearby couch and listed for about an hour. I said nothing.

At that time, decision was made to move to another room. I followed, and during the walk was invited to join. Two participants left, two stayed, and I joined.

The space remained sacred. I knew it had different rules, and did my best to follow them. When I was incorrect, they explained. Use ‘I’ statements. Things about your own beliefs, your models, your feelings. Things you know to be true. Pay attention to your body, and how it is feeling, where things come from, what they are like. Report it. At one point one participant said they were freaking out. I observed I was freaking out. Someone else said they were not freaking out. I said I thought they were. The first reassured me they thought there was some possibility we’d survive. Based on their prior statements, that was an update. It helped a little.

I left exhausted by the discussion, the late hour and the three hour time zone shift, and slept on it. Was this people just now waking up, perhaps not even fully? Or were people reacting too much to Alpha Go? Was this a west coast zeitgeist run amok? An information cascade?

Was this because people who understood that there was Impending Ancient Doom and we really should be freaking out about it used to freaking out vastly more than everyone else? So when Elon Musk freaked out and puts huge funding into OpenAI without thinking it through, and other prominent people freaked out, they instinctively kept their relative freak out level a constant amount higher than the public’s freakout level, resulting in an overshoot?

Was this actually because people were freaking out about Donald Trump giving them a sense we were doomed and finding a way to express that?

Most importantly, what about the models and logic? Did they make sense? The rest of the unconference contained many conversations on the same topic, and many other topics. There was an amazing AI timeline double crux, teaching me both how to double crux and much about timelines and AI development. But nothing else felt like that first circle.

As several days went by, and all the data points came together, I got a better understanding of both how much people had updated, and why people had updated. I stopped freaking out. Yes, the events of the previous year had been freakout worthy, and shorter timelines should result from them. And yes, people’s prior timelines had been a combination of too long and based on heuristics not much correlated to actual future events. But this was an over-reaction, largely an information cascade, for a confluence of reasons.

I left super invigorated by the unconference, and started writing again.

Meta-note: This should not convince anyone of anything regarding AI safety, AI timelines or related topics, but I do urge all to treat these questions with the importance they deserve. The links in this post by Raymond Arnold are a good place to start if you wish to learn more.

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The Sheepskin Effect

Previously: The Case Against EducationThe Case Against Education: FoundationsThe Case Against Education: Splitting the Education Premium Pie and Considering IQ

Epistemic Status: The spirit of Local Validity as a Key to Sanity and Civilization

The sheepskin effect is that completing the last year of high school, college or graduate school is much more profitable than completing any of the previous years, rivaling those other years combined. Employers seem to be paying for the degree (aka the sheepskin, which it’s printed on) rather than the human capital being built over time.

In the education chapter of Book Review: The Elephant in the Brain, I noted Robin relied on the sheepskin effect as strong evidence (along with other arguments, including impacts on national vs. personal income) that school was mostly signaling. Bryan Caplan does the same. He cites the data, seeing (on top of a 10% bonus in pay per year of school) 32% bonus pay for finishing high school, 10% for junior college, 30% for a bachelor’s degree and 18% for a masters. To those who claim this is mostly ability bias, he replies:

Ability bias explanations for sheepskin effects aren’t just hard to square with statistical evidence; they’re hard to square with the glaring fact that education spikes in degree years. If the labor market ignores credentials, why do so many college grads opt for zero graduate education? Are we supposed to believe one-third of the population has exactly the right ability to finish high school, but not advance to college? One-seventh has exactly the right ability to finish college, but not advance to graduate school?

To debunk sheepskin effects, correcting for these neglected abilities would have to drastically cut the payoff for degrees but not the payoff for years of schooling. What abilities would even conceivably qualify?

This seems like a straw man; no one thinks the labor market ignores credentials, so it’s easy to see why students act the way they do. Not only is not finishing high school severely punished as such (as the numbers show), not trying is at least sort of illegal. In addition, there’s a huge barrier to getting into college or graduate school, and large costs involved in starting, often involving relocation. Also, much of college is about being ready for the rest of college, and the early part of graduate school is largely to get you ready for the later parts.

I also notice, looking again, another instance of the mistake of assuming people are maximizing. We are definitely not supposed to believe that because a lot of people do something, it was right for them!

Having dismissed ability bias here, he then reasons:

After digesting all the evidence on the sheepskin effect, you may feel ready to channel King Solomon. Human capital and signaling come before you as litigants. They ask you to split the education premium between them. A ruling with a great ring to it: “Human capital gets credit for the payoff for years of education; signaling gets credit for the payoff for degrees.” This implies a human capital/signaling split of roughly 60/40 for high school, 40/60 for college.

Yet on reflection the Solomonic ruling treats human capital too generously. The sheepskin effect doesn’t measure signaling. Instead, the sheepskin effect sets a lower bound on signaling.

To see why, picture a world that lacks the notion of “graduation.” Can we safely declare educational signaling would vanish in such a world? Of course not.

What I wrote back in my previous review of Elephant in the Brain:

One note I would make is about the sheepskin effect, where the last year of a college degree is much more valuable than previous years. There’s been some debate about this online lately between Bryan Caplan and Noah Smith. I agree that this is largely a signaling effect, with ‘completed all eight terms’ much more impressive than ‘completed seven of eight terms’ since you don’t know how many more terms the first student could have finished if necessary.

What the discussion misses, it seems to me, is that only after graduation do you know that the first three years were real. It is easy to become ‘a senior’ through completion of a number of credits, saving the stuff they find hardest for last or even being in terrible shape to match up with graduation requirements. I strongly suspect that a lot of people who drop out in year four are much farther from finished than they would have you believe.

I’d like to expand upon that, because this effect seems huge but remains almost always unmentioned.

I’ll start with a real example.

I have a learning disability that makes it very difficult to learn foreign languages. This was bad enough to nuke my average in high school, despite having studied the same language (Hebrew) for most of a decade whether I wanted to or not (I’ve held on to maybe a hundred words?), and in college things threatened to get much worse. My college demands four terms of a single foreign language. I chose what appeared to be the easiest one for an English speaker, Italian. While it would be cool to speak Italian, I didn’t choose it for how much cooler it would make vacations and restaurants – I was fully aware that Italian was of little use. But I was desperate to get through this, ideally without my average being nuked again, and if it was marginally easier than Spanish but only 10% as useful, then Italian it would be.

When the term ended, I had spent the majority of my studying time on Italian I, and still (just barely) failed by the numbers. I managed to get the grade changed from an F to a D by promising not to take Italian II. I then managed to find a psychologist who vouched for my disability, I think on the basis of an IQ test combined with my history of failures – there really was no other explanation. So I was granted an exception, and allowed to take Asian literature (which I quite enjoyed) and Etymology (which was boring as hell but not hard) instead of the remaining three terms. The D still ended any hopes of my getting honors and crippled any hopes of a top graduate school, and after that I stopped trying that hard to get As, but I got to graduate.

Without that exception, would I have graduated? My guess is yes, because my family and I would have taken epic measures to make it work. I’d have taken a year off to live in Italy (or Israel) if I’d had to. But I can’t be sure it would have been enough.

A good friend of mine ran into this exact problem with the same requirement, couldn’t get the waiver, has no other remaining requirements, and will probably never graduate.

More data. My mother is a professor at Columbia University, where she is in charge of undergraduate biology education. One cool effect of this is that she’d bring related dilemmas and puzzles home so we could explore them at dinner. I helped her plan exam strategies, deal with discipline issues and so on, and it was both great fun and an actual education in the way that school isn’t. 

Occasionally we looked at a series of students who wanted to graduate with a major in biology. The problem was that their transcripts were, shall we say, not so flattering. They’d ‘completed’ close to the full eight terms, but did they have a high enough average in their major? Were the poor grades (Ds and sometimes Cs) in some required courses not acceptable? We all, including the school, wanted to let students graduate when we could – that’s the business, after all, and no one wants to ruin a kid’s life – but the degree has to mean something. These were many of the students who ‘complete seven of eight terms,’ and many others were those who knew a version of this examination was coming and they wouldn’t pass.

Countless others, no doubt, simply saved all the hardest and most difficult courses for the end, possibly in a way that made the logistics impossible to solve. And, well, whoops.

If I give you eight chess puzzles to solve, and you solve seven of them, that’s a lot less impressive than if you solve all eight. If I give you thirty-two courses in ten different fields of study with varying difficulty, and you choose your order so as to solve and pass the first twenty-eight, you are not remotely 7/8ths done.

I could thus tell a human capital story, or an ability bias story, for the sheepskin effect. The final test is real, so if you built up real human capital, and learned how to learn things and remembered your lessons and persevere when the going gets tough, and all that, you win out. If you didn’t do that stuff, you fail at the end when you can’t hide it any longer. Or, for ability bias, only at the end do we learn who had the right stuff all along; same principle. If the final test is sufficiently ‘more real’ than the others, that bonus at the end makes perfect sense.

Thus, I don’t think the arguments from sheepskin are as strong as many think they are. I do think that the education premium is mostly signaling and ability bias, including (but far from limited to) the sheepskin effect. And I do think Bryan offers other much stronger evidence, such as the fact that anyone could walk into any college class and take it for free sans the degree, and actual no one ever does. But I don’t think the sheepskin effect puts a lower bound on the signaling share, or offers that much evidence, because in a world without signaling you’d see it anyway, and I’m curious how Bryan would respond.

 

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The Case Against Education: Splitting the Education Premium Pie and Considering IQ

Previously: The Case Against Education: FoundationsThe Case Against Education

VI

Bryan Caplan makes several cases against education. His primary case revolves around the question of where the education premium comes from – no one doubts that the better educated make more money. As we noted last time in Part V, there are three categories of explanation: Human capital (school teaches you valuable things, so you produce more value), signaling (school sends a valuable signal, so you get better opportunities and better pay), and ability bias (those who would always have earned more money attend more school, and school is taking credit for effects it didn’t cause).

As I noted in part V, it’s undeniable (despite frequently being denied) that ability bias plays a large part in the story, as does signaling, but there’s large uncertainty on how much. It’s a difficult problem, worth looking at from multiple angles.

One way is to ask, what are the relevant measures of human capital? What do we learn in school that helps us be more productive? If we can measure that, we know how much of the story is human capital, leaving the rest to signaling and ability bias.

Another way in is to start with ability bias. If we can correct our measures for underlying ability via a natural experiment or finding good proxy measures for underlying ability, the difference between the adjusted and non-adjusted numbers represents ability bias. There’s lots of types of ability, but what we can measure and correct for would represent a safe lower bound on ability bias.

If you had a good measure of human capital, you could combine these two approaches. Measure human capital before school, then measure it again after school, and compare it to the measure of those who didn’t attend. The additional increase in human capital from school represents human capital, and the starting difference is ability bias. The rest is signaling (or unmeasured abilities and capital, so one must be careful).

We could also start by measuring signaling directly. If we can find explicit signaling effects we can measure, that’s a safe lower bound on the value of signaling.

Another alternative is to compare personal benefits, which include both signaling and human capital, to societal benefits, which should include only human capital (plus the benefits of signaling by the society, which is interesting to ponder; Bryan doesn’t get into that much). The difference is signaling.

Or you could look at exactly what causes increased earnings, and ask what stories that’s compatible with.

Additional dangers include questions such as, what if going to school’s ability bias is in the form of those who intend to work to increase their human capital? That’s tricky as hell to measure and sounds plausible. Or, if you want to measure societal benefit to schooling, what if the active ingredient is sorting the schooled for socialization purposes, in a would-have-happened-anyway, zero-sum (or worse) fashion?

It’s like any math or research problem – if you do valid things, to the extent they are valid, you’ll get a valid piece of the puzzle. Bryan takes every approach he can find and compares the implications, which is an excellent tactic here.

When he corrects for ability, what does Bryan find?

Correcting for ability, college grads earn 40% more than high school grads.

Citations needed and work must be checked and all that, and what ability means in context is worth thinking about carefully, but yeah. Wow.

Bryan begins with IQ as a source of human capital and signaling:

Almost all the research has two conclusions in common. First, IQ pays. Holding education constant, an extra point of IQ raises earnings by about 1%. Second, holding IQ constant, the education premium shrinks but never vanishes. In 1999, a comprehensive review of earlier studies found that correcting for IQ reduces the education premium by an average of 18%.

The mystery isn’t why IQ pays, but why it pays so little. I’ve known about these results for a long time, and understanding why this effect is so small seems important.

Mathematical ability might account for more than all of this, from a certain point of view, which is even more odd:

Correcting for mathematical ability may tilt the scales even more; the most prominent researchers to do so report a 40–50% decline in the education premium for men and a 30–40% decline for women.

There are a few stories that seem relevant and plausible. They are related, so there’s overlap.

Story 1: Most jobs are about being a cog in a machine, being in a given place at a given time to do a thing, or physically doing certain tasks. Being smarter might help a little, but mostly this is a threshold effect. If you’re good enough to be a retail clerk, you’re not going to produce much more value being a really smart retail clerk, and your being bored out of your mind is likely to backfire. The person fetching coffee needs to be smart enough to make and fetch coffee, but being smarter than that isn’t obviously good, if you’re assembling a car you need to be smart enough to know how, and so on for the butcher, the baker and the candlestick maker. There’s honor in all of it, but why should IQ pay off in most jobs?

This story implies those people also don’t need much education. They need to learn to submit, to learn to be cogs in a machine and do rote tasks. Of course, school is all about that.

Story 2: Smart people demand fulfilling, interesting work. Regular people just want steady work and a solid paycheck. Smart people get a much better basket of goods from their job, in the form of interesting things, but that lets employers pay them less money. 

Because economics, these smart people don’t produce that much more value for others, they mostly amuse themselves. But regular people were just as amused without all that work. So once again, investing in making people smarter slash teaching them more things isn’t worth all that much.

Story 3: Smart people have a hard time relating to (relatively) dumb people, and vice versa. You want your friends to be within one level of you, or at most two levels. At three levels, communication is all but impossible, an intelligence version of the SNAFU principle. A lot of many jobs is relating to others, so being too smart becomes a handicap even if you aren’t bored to tears.

Related, but not identical, to that is the story that no one likes a smart-ass, and people punish you for being smart, or judge you against a higher standard and thus pay you less. Even when they like that you’re smart, paying you for being smart feels unfair. They’re ‘working hard’ while you’re working smart. It’s natural to think that pay should follow who works hard rather than who produces more, even before inequality considerations or status considerations (stories 4 and 5).

This is especially true for those who create innovations and improvements and original works, the entrepreneurs and inventors and content creators. It’s notoriously hard for even corporations to capture that much of the value their new ideas create. Trying to capture the value as an individual inside an organization, or create a new one and keep that much of the equity in the one that you create, is even harder.

This story is bullish on making people smarter, teaching them how to think and be free, and on real education and skill development in general. Human capital is awesome! The few who generate worthwhile new things create tons of value. From some perspectives, they create more than all of the value, period. But they don’t capture it, so society benefits massively more than the pay statistics would suggest. We should subsidize such education, and such actions!

Alas, that doesn’t mean we should be subsidizing school. School doesn’t teach you to innovate and be free; it teaches you how not to think, and to be a cog. Those who create these types of value tend to be rebels who reject school. So it’s a strong argument against school, except insofar as it does actually raise intelligence as such as a side effect of its other actions.

Story 4: People hate inequality. The idea that the best programmer is worth 100 times the average programmer, who in turn is worth 10 times the average worker, is something we are highly motivated to reject out of hand, whether or not it is true. Besides, everyone has roughly the same needs. So the IQ 140 employee produces ten times what the IQ 110 employee produces, and gets paid 30% more.

This is definitely a huge thing. It’s related to the idea that you should be rewarding working hard or even working for X hours rather than producing value. But it’s also its own thing that says people aren’t allowed to have radically different value, people just won’t stand for it. You’re taxed on your extra value on tons of levels. People refuse to pay you for much of the extra value you capture, then they tax you, then they expect you to help the ‘less fortunate’ around you and around the world, and use any number of other techniques on you. Among them is, they forced you to consume more school, taking years off your life and saddling you with debt, and because you’re smart you need to do the same for your children. This can all easily add up to tax rates well in excess of 100%.

This story is bullish on building up intellectual human capital. Its value doesn’t show up fully in the pay statistics.

Story 5: Productivity doesn’t primarily determine pay. Primate status and social dominance, office politics and systematized oppression determine pay. If you’re not at the top, what matters is how you suck up to the boss. In extreme cases like government jobs and union shops, pure title and seniority entirely determine pay. So we’re asking the wrong questions (on many levels).

This is again bullish on human capital because its value isn’t paid for. The world gets the benefits mostly for free.

I see some truth in all of these stories. In any case, Bryan notes that intelligence enhancement can’t possibly be the bulk of what school does, because the effect size is too small:

Suppose each year of school permanently made you a whopping 3 IQ points smarter. According to standard estimates, this would raise your earnings by about 3%, leaving a supermajority of the education premium unexplained.

What of the theory  that one goes to school primarily to signal intelligence? His response is that there’s an easy and at least as effective way to test for intelligence alone: IQ tests are totally a thing.

Yes, there’s the minor catch that they’re illegal in theory:

Thanks to the landmark 1971 Griggs vs. Duke Power case, later codified in the 1991 Civil Rights Act, anyone who hires by IQ risks pricey lawsuits. Why? Because IQ tests have a “disparate impact” on black and Hispanic applicants. To escape liability, employers must prove IQ testing is a “business necessity.”

But, he argues, mostly legal in practice:

Only 4% of federal discrimination cases brought between 1987 and 2003 alleged disparate impact. That amounts to under a thousand annual cases against any form of employment testing. If disparate impact cases cost the usual amount, employers’ total test tax is under $200 million a year.

Which means that companies could just pay up when necessary:

Compared to the total upcharge a nation of employers pays for college graduates, this is a pittance. If IQ testing really let employers hire college-quality workers for high school wages, prudent employers would freely test IQ and treat the occasional lawsuit as a minor cost of doing business. Remember: correcting for ability, college grads earn 40% more than high school grads. If IQ laundering were a central function of higher education, courts could raise the test tax a hundredfold—and IQ testing would remain profitable.

Thus, employers must care mostly about other things, or they’d just pay up. In particular, they care about conscientiousness and conformity, both of which school signals strongly.

This bothered me enough that I spun off a post about this structure of argument, which is here. I’m also going to talk a bit about how I see the employers’ perspective and how I’d think about giving an IQ test.

If you Google “I don’t pay you to think” you get 147 million results. If you Google “I pay you to think” you get 51 million. The top of both searches is a TVTropes link to I Don’t Pay You To Think. So the amount of actual paying-for-thinking is not especially large. Chances are, I need you to not be a situational moron, and pass a threshold for intelligence, but don’t care about much beyond that. But lets say this is one of the exceptions, and I do want to pay you to think.

If I give an IQ test, it’ll be awkward. Applicants will see me test them and think it is weird, turning them off. Employees will see me doing it, and think it’s weird and uncaring and potentially legally dangerous. Everyone around could sue me, or more importantly could threaten to sue me, or perhaps even more importantly everyone knows that everyone is worried that anyone could implicitly threaten to sue me. So now I’m afraid of publicity, I’m afraid of anyone getting mad and wanting to go after me, I’m afraid of my own shadow. Any reporter who gets a whiff of this might shift their story to my terrible practices.

Even if none of that is a concern, I’ll have to be continuously reassuring employees, applicants, investors and everyone else that this isn’t an issue. If everyone thinks it’s an issue, it’s a huge issue, even if I never get sued and no one ever threatens to sue me. And all of them will treat this as a huge negative signal, that I take stupid legal risks and make myself vulnerable, and that I waste my weirdness points, and that I care about all the wrong things. What other similar things am I doing? Will I still be in business in a few years? Should anyone rely on me for anything? Will others think the same ways, even if they shouldn’t, or think others will think in those ways?

And of course, IQ tests have a bad reputation among Those Who Protest Things, which can itself be highly damaging.

So this is all super expensive, even if it amounts to nothing. 

And if I actually get sued, it’s a disaster that is likely to take down the whole business. Work will grind to a halt. Expensive lawyers will be brought in, stress levels will be sky high, no one will talk about anything else. Fishing expeditions take place in depositions. Employees may bolt. For the rest of time, people will remember that I was sued, that my business was sued, and I will be tainted. The actual payout cost of the suit is a small fraction of the damage it will due to me and my business. Lawsuits are nuclear weapons.

Perhaps I’ll just give this one a rest, even if I mostly do care about intelligence (and I almost certainly do care a lot about conscientiousness, and probably conformity, and definitely lots of other things, many of which I’m not supposed to care about). Plus, if I give people a numerical test, I won’t be able to use my judgment on who to hire, and no series of papers saying my judgment sucks is going to tell me I should stop using it. At most, I’ll rely on it somewhat less.

Alternatively, I can use a skills test that doubles as an IQ test. If you’re going to be a coder, I can listen to you think as you code. If you’re going to be a trader, I can give you trading situations or probability questions, and do the same. If challenged, I’m testing your applicable skills, so even if it is ruled an IQ test, it’s meeting a clear ‘business necessity.’ That’s not just a technicality, it’s actually doing that. So that seems better.

Using the IQ test combines all the disadvantages of a strict test. You’re opening yourself up to legal challenges on multiple levels, taking away your judgment. And you don’t get the most important benefit of strict testing, which is to appear to be doing a fair, sensible and responsible thing. You’re not doing something no one could blame you for. Quite the opposite. You’re actively courting mild social disapproval and awkwardness, rather than avoiding it. So why are you even doing it?

 

 

 

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Inefficient Doesn’t Mean Indifferent

Many people, including Bryan Caplan and Robin Hanson, use the following form of argument a lot. It could be considered the central principle of the (excellent) The Elephant in the Brain. It goes something like:

  1. People say they want X, and they do Y to get it.
  2. If people did C, they would get X, and the price of C is cheap!
  3. Therefore, people really value X at less than the price of C, so they don’t really care much about X.

There’s something very perverse going on here. We’re using people trying to get X in an inefficient way as evidence they don’t care about X, rather than as evidence that people aren’t efficient.

The trick is, there’s a lot of assumptions hidden in the above logic. In practice, they rarely hold outside of simple cases (e.g. consumption goods).

The motivating example was Bryan Caplan using this one in The Case Against Education:

  1. People say they want smart employees, and look at school records to get it.
  2. If people gave out IQ tests, they would get smart employees, and testing is cheap!
  3. Therefore, people don’t really value smart employees.

In that case, I agree. Employers (most often) don’t want smart employees beyond a threshold requirement. But local validity is vital, and you can’t do that.

There are lots of reasons why one might not want to do C.

As a minimal first step, people have to believe that strategy C would work. A recent example of Robin Hanson using this technique, that violates that requirement, from How Best Help Distant Future?, could be summarized this way:

  1. People say they want to help the future, and lobby for policies they think help.
  2. If people saved money to help the far future, which they almost never do, they could help more, and since you get real returns from it, it’s really cheap!
  3. Therefore, people don’t much care about the far future.

In that case, I strongly disagree. People rightfully do not have faith that saving money now to help the far future will result in the far future being helped. Perhaps it would, but there’s a lot of assumptions that case relies upon, many of which most folks disagree with – about when money will have how much impact (especially if you expect a singularity to happen), about what you can expect real returns to be especially in the worlds that need help most, about whether that money is likely to be confiscated, about whether the money if not confiscated would actually get spent in a useful way when the time comes, about what that spend will then crowd out, about whether that savings represents the creation or saving of real resources, about what virtues and habits such actions cultivate, and so forth.

(I don’t think that saving and investing money to spend in the far future is obviously a good or bad way to impact the far future.)

More generally, human actions accomplish, signal and cost many things. A lot of considerations go into our decisions, including seemingly trivial inconveniences. One should never assume that a given option is open to people, or that they know about it, or that they’re confident it would work, or that they’re confident it wouldn’t have hidden costs, or that it doesn’t carry actual large costs you don’t realize, and so forth.

The argument depends on the assumption that humans are maximizing. They’re not. Humans are not automatically strategic. The standard reaction to ‘I actually really, really do want to help the far future’ is not to take exactly those actions that maximize far future impact. The standard reaction to ‘I actually really, really care about hiring the smartest employees’ is not to give them an IQ test because that would be mildly socially awkward and carries unknown risks. Because people, to a first approximation, don’t do things, and certainly don’t do things that aren’t typically done.

If something is mildly socially awkward or carries unknown risks, or just isn’t the normal thing to do (and thus, might involve the things above on priors), it probably won’t happen, even if it would get people something they care a lot about.

So if I see you not maximizing far future impact, and accuse you of not caring much about the far future, a reasonable response would be that people don’t actually maximize much of anything. Another would be, I care about many other things too, and I’m helping, so get off your damn high horse.

A very toxic counter-argument to that is to treat all considerations as fungible and translatable to utility or dollars, again assume maximization, and assert this proves you ‘don’t really care’ about X.

An extreme version of this, to (possibly uncharitably, I’m not sure) paraphrase of part of a post by Gwern on Denmark:

  1. Denmark helps the people of Greenland via subsidy.
  2. Helping people in Greenland is expensive. Denmark could help many more people if it instead helped other people with that money.
  3. Therefore, Danish people are moral monsters.

This is a general (often implicit, occasionally explicit) argument that seems like a version of the Copenhagen Interpretation of Ethics: If you help anyone anywhere, you are blameworthy, because you could have spent more resources helping, but even more so because you could have spent those resources more effectively. So you’re terrible. You clearly don’t care about helping people – in fact, you are bad and you should feel bad, worse than if you never helped people at all. At least then you wouldn’t be a damned hypocrite.

This threatens to indict everyone for almost every action they take. It is incompatible with civilization, with freedom, or with living life as a human. And isn’t true. So please, please, stop it.

 

 

 

 

 

 

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The Case Against Education: Foundations

An Introduction: The Case Against Education

We’ll now focus more on the book and its data, reasoning and arguments, and related questions. There’s a lot to address, starting with the foundations of Bryan’s analysis. Rather than write one novella-long post, I’ll be going through my highlights and talking about related issues, and post sections as I go.

IV

Is our children learning?

Well, what’d ya know?

Bryan has the data: Not much. You?

Here are some data points about adults:

Most people who take high school algebra and geometry forget about half of what they learn within five years and forget almost everything within twenty-five years. Only people who continue on to calculus retain most of their algebra and geometry.

Yikes. We can argue about the value of geometry and calculus, but a practical proficiency in basic algebra is kind of important to functioning in the world.

Possible conclusions from this, aside from ‘Americans can’t do basic algebra, set your prices and marketing campaigns appropriately and maybe learn Mandarin’ include:

A: We don’t spend enough on algebra! Spend more time and money!

B: Don’t spend more time and money, we already spend a ton. It’s that we are horrible at teaching math. Stop it. Work smart, not hard. Maybe treat math as an adventure and not a series of memorized rules and tables.

C: Don’t spend more time and money on algebra and geometry. Make calculus mandatory. Study shows that will make people remember algebra!

D: People actually implement things like C (and also A) all the time, so maybe drop mandatory algebra and geometry, and focus on teaching statistical literacy instead.

E: Maybe before we teach anyone algebra we should see if they know how to multiply.

Good idea. How about adults’ basic arithmetic?

Barely half know that saving $.05 per gallon on 140 gallons of oil equals $7.00.

Whoops.

You can either complain that this means our failing schools need even more funding and to imprison our kids even longer, since the right response to something not working despite ludicrous investments of resources is to invest more resources do what isn’t working even harder, or you can admit the entire system is an utter failure.

Their science knowledge?

Table 2.4: Adult Science Knowledge: Some Telling Questions, With % Correct

The center of the Earth is very hot. 81%

The continents on which we live have been moving their locations for millions of years and will continue to move in the future. 78%

Does the Earth go around the Sun, or does the Sun go around the Earth? 73%

All radioactivity is man-made. 68%

Electrons are smaller than atoms. 52%

Lasers work by focusing sound waves. 46%

The universe began with a huge explosion. 33%

The cloning of living things produces genetically identical copies. 80%

It is the father’s gene that decides whether the baby is a boy or a girl. 62%

Ordinary tomatoes do not contain genes, while genetically modified tomatoes do. 47%

Antibiotics kill viruses as well as bacteria. 53%

Human beings, as we know them today, developed from earlier species of animals. 44%

(Remember, these were true/false questions, so 50% means no knowledge at all. Less than that is… worse. Answer key not included, because come on.)

Brutal. In this context, the majority of Americans not believing in evolution isn’t a strange religiously motivated outlier. It isn’t partisan, either. Mostly people just don’t know things.

That’s a bunch of facts, though. Do we teach them how to think?

One researcher tested several hundred Arizona State University students’ ability to “apply statistical and methodological concepts to reasoning about everyday-life events.” How, for example, would subjects assess the claim that students should eat more nutritiously because “the majority of students needing psychological counseling had poor dietary habits”? Would subjects realize psychological problems might cause poor dietary habits, rather than the other way around? Would they feel the need for experimental evidence? No.

In the author’s words: The results were shocking: Of the several hundred students tested, many of whom had taken more than six years of laboratory science in high school and college and advanced mathematics through calculus, almost none demonstrated even a semblance of acceptable methodological reasoning about everyday-life events described in ordinary newspaper and magazine articles. The overwhelming majority of responses received a score of 0. Fewer than 1% obtained the score of 2 that corresponded to a “good scientific response.”

Not so much. The surprising finding is that these findings were surprising.

If we got rid of school entirely, would adults score worse?

And then they voted. But that’s a different Caplan book.

But perhaps the study doth judge too harshly.

Consider this quote, about a study that showed people with poor diets experiencing more health problems (as usual, scientists are hard at work asking the hard questions with high value of information):

Totally ignoring the need for comparison groups and control of third variables, subjects responded to the “diet” example with statements such as “It can’t hurt to eat well.”

How does the author of that sentence think one gains knowledge of the world? Does he think we need a control group to know which switch turns on the light in the bathroom?

The response of “eating healthier foods might help your problem or it might do nothing, but it’s highly unlikely to make things worse, so doing so is a good idea” is exactly what a practical Bayesian analysis looks like, here. Does author think it could hurt to eat well? There’s the obvious problem that we don’t know what ‘eat well’ actually entails, but that doesn’t change the answer.

Comparison groups and control of third variables are important. It is entirely plausible that people who have good diets also take care of themselves in other ways, or both have higher socioecnomic status, or good health enables eating well, or any number of other such things. There’s a reason I tried starting a personalized medical research company. This stuff is hard!

But the response of ‘it can’t hurt’ is the right prior. It is properly taking all that uncertainty into account, whether or not the person could articulate any of it.

What matters is practical knowledge of correlation/causation and related issues. If one goes around thinking correlation proves causation, that’s really bad. But ‘it can’t hurt to eat well’ is not a confident claim that eating well would help. The null hypothesis isn’t being rejected. But if one thinks that one shouldn’t change behavior based on data unless the null hypothesis can be rejected, they’re even more wrong than thinking correlation implies causation.

Are we testing for understanding, or guessing the teacher’s password? It’s no surprise that no one remembers the password decades after the test.

If academics studying learning don’t even know what practical knowledge looks like, how much practical knowledge are students likely getting from the academy? Or as Taleb puts it in Skin in the Game:

In academia there is no difference between academia and the real world; in the real world, there is.

We then allow academics to determine our definitions, our beliefs and our policies. And our hidden assumptions.

In particular, the idea that education equals school equals skills. 

Thomas Piketty, in Capital in the Twenty-First Century, makes many questionable assumptions. But none of his mongering about inequality was half as maddening to me as when he measured job skills of a population by looking at years spent without a job, in schools. If a population lacked job skills, of course that meant we hadn’t spent enough on education! Because education equals school equals skills. 

Yesterday I was at Citi Field for Jackie Robinson Day, when we celebrate Jackie Robinson’s demonstration that we’re all the same by having all the players wear the same number so we can’t tell them apart, and also celebrate Douglas Adams by making that number 42. We got to hear about Jackie’s nine values, a solid list: Courage, determination, teamwork, persistence, integrity, citizenship, justice, commitment, and excellence. And we got quotes about how education (which is noticeably not in Jackie’s nine) was the key to our future… and once again, education equals school. 

Academics and politicians don’t reject (or even consider) the signaling model of education. They use a linguistic slight of hand to assume it away. Rendering it unthinkable. Redirecting people’s desire to help educate people into funds to add fuel to a dystopian nightmare.

It all makes me wonder even more what to take away from sentences like this one:

By the time students are in middle school, however, one summer vacation wipes out over three months of reading proficiency.

Multiple choice, choose all that apply:

A: The reading skills lost are real. We should eliminate summer vacation lest our nation fall behind. We could get twice as much reading proficiency, since instead of gaining 9 months then losing 3, we’d gain 12!

B: The reading skills lost are real. We don’t quite need to eliminate summer vacation, but we do need to ruin kids’ fun more by assigning extra reading work so they won’t lose their progress. More homework must mean more education, even if the data doesn’t show it.

C: We should eliminate summer vacation, because during summer vacation children rediscover creativity and forget what the teachers’ password was, setting back test scores by three months and forcing us to reteach them all that each fall.

D: Same observations as Option C, except we should definitely not eliminate summer vacation.

E: Our obsession with tests has forced students to engage in cramming-style behaviors that don’t generate long term knowledge. Of course, any time spent this way is at best zero sum signaling.

F: School has turned children off of reading to the extent that they don’t even read enough to maintain their skill levels without state coercion. Something was wrong. 

G: Kids can’t retain skills or knowledge beyond what is supported by their age, developmental level and home environment. Trying to push them beyond that results at most in temporary gains. If kids lose reading skill over the summer, that means we shouldn’t have been trying to teach them that yet. 

H: It’s all fraud. At the end of the year, teachers cheat to help students score better. At the start of the new year, teachers if anything want their incoming students to score worse.

As you suspect, my prior is on a combination of D, E, F, G and H.

Bryan doesn’t focus on these types of questions, or modes of thinking, choosing other targets. Books can only be so big, there’s only so many hours in the day, and he’s trying to give the benefit of the doubt.

V

Lets reorient to Bryan’s approach. Bryan starts with the well-known fact that there exists an education premium: Those with more years of schooling earn more money. Note that even Bryan calls it the education premium rather than the schooling premium. Even he’s been hoodwinked. School is not education!

Thus, where Bryan says ‘education’ or ‘educated’ but means ‘school’ or ‘schooled’ I will write ‘school’ or ‘schooled.’

Whatever you call it, the premium is real. Some combination of things is creating that premium. By Bryan’s accounting, there are three suspects:

Human Capital is the traditional justification for most or all of the effect. School makes you smart. It teaches you the skills and values you need to succeed in life. This makes the schooled more productive than the unschooled, so they get paid more.

Signaling is Bryan’s justification for the bulk of the effect. School is a test of your intelligence, conformity and conscientiousness. The longer and more difficult schooling you complete, the more you’ve demonstrated all three skills. Employers want all three skills, so they give better pay and opportunities to the schooled, well beyond the human capital created by schooling.

Ability Bias is also present to an unknown degree. Those who sign up for more school are already smarter, more conformist, more conscientious and generally more able to succeed in today’s economy than those that don’t. The more able students also complete what schooling they start more often than the less able. Thus, they would have been paid a premium even if they hadn’t had more schooling.

The portion of the schooling premium that comes from human capital is real and positive sum – the student creates more value and gets rewarded. The portion from signaling is real and positive for the student but probably mostly zero sum for society (more on this later, as I find this less obvious than Bryan does) – the student doesn’t create more value except insofar that they get better opportunities, but gets better opportunities that probably would have gone to others, and gets paid more. The part that comes from ability bias is a statistical mirage – nothing happened at all.

There is lots of uncertainty about how much of the effect comes from each source. What is beyond obvious is that signaling and ability bias are present and important. We see lots of explicit signaling and rewarding of signaling, so that’s important. Those who go to college have obviously vastly superior economic prospects than those who don’t go to college, even before anyone attends: They are smarter, more knowledgeable, more skilled, have higher socioeconomic status, are healthier, are more conformist, are more conscientious, are less likely to have committed major crimes. You name a thing that correlates with success, with notably rare exceptions they have more of it. The same goes for those who graduate versus those who drop out, or who graduate high school versus drop out, and so on.

It would be utterly completely insane to say that ability bias wasn’t a thing.

So of course, Bryan points out that the entire field dedicated to studying this tries to deny that ability bias is substantive enough to be meaningful:

A famous review of the evidence by eminent economist David Card concludes ability bias is small, nonexistent, or even negative. I call this verdict the Card Consensus. Many, perhaps most, elite labor economists not only embrace it but rely on it for practical guidance. We see the Card Consensus in top scholarly venues like the Journal of Economic Literature. The return to an additional year of education obtained for reasons like compulsory schooling or school-building projects is more likely to be greater, than lower, than the conventionally estimated return to schooling.

What. In. The. World?

Academic labor economists, led by a professor at the University of California, Berkeley (because, of coursethink labor success comes from academics, show robust benefits from more and compulsory schooling, deny other justifications for inequality of outcomes. Recommend government intervention and mandated behaviors to help for less fortunate, and lots more money for their and other fields. Also higher status.

On the one hand, film at eleven. Bias is expected here.

On the other hand, what in the world? 

What would an Earth without ability bias look like?

This is a world in which (for example), if we select a group of random students who would normally go on to complete high school and force them to drop out of high school, they would earn no more than the average high school dropout. If we took random students who would have attended college, and prevent them from attending college, they will earn no more than the average person who never attends college.

No, really. Stop here and actually think for five minutes: What would this Earth without ability bias look like? Try to construct a toy model where ability bias is zero, and see what happens.

I’ve managed to come up with three possible worlds without ability bias. You could have a world of identical people, likely involving cloning vats. Or perhaps you could go full on Harrison Bergeron. Or as a wildcard, all the jobs are fake, robots do all the work, so no one has any ability. You could have a world where everyone is either forced to or forbidden to attend school, at random, based on nothing that measures their human capital or correlates with their future economic production. And of course, mysteriously (ominous music) no one ever fails. Then there’s a third option involving mass kidnapping, rape and enslavement. Perhaps like the Handmaid’s Tale, except for the competent instead of the fertile.

Feel free to turn them into young adult trilogies or spec scripts for The Orville.

The thinking is this: If you want to break the correlation between school attendance and ability, you have four basic choices.

You can give everyone identical abilities. That seems to be what labor economists endorse: Schooling equals education equals skill. Except that’s obviously insane.

You’d think you could also do this simply by paying people purely on the basis of their educations (and perhaps seniority), like a government or a union shop where ability isn’t relevant. The problem is you’d still need to fix that more able people more often attend, and conditional on going more often finish.

You can make people with different abilities equally likely to attend and finish school. That requires taking away their choice in whether to attend – not just with attendance requirements, but actually taking away all choice. Then you have to make sure ability doesn’t impact ability to finish.

Your third choice is to accept that ability bias is a thing, but create an equal and opposite bias in the opposite direction that cancels it out.

Wrong conclusions are wrong. What we have here is an entire economic field setting one of its most important variables to an impossible number that doesn’t stand up to the slightest logic or scrutiny. It describes a world vastly unlike our own, vastly unlike even a highly ideological, toy academic version of that world. It makes no sense. And they’re doing it in a way that happens to support the status of their ‘field’ and their ideological agendas. If you call that a consensus, then there being a consensus in your field is no longer much evidence in support of that consensus. Even the raw data gathered should be considered highly suspect, and you should put strong weight on your own priors and models.

Those same people are going around saying that while most every other demand curve slopes downward, somehow higher minimum wages don’t lead to decreased employment. Which to be fair I took seriously, and found plausible on the realistic margin in that one case. But this pattern does not inspire confidence.

What this says about other academic fields with similar motivations, structures and conclusions is left as an exercise to you. No need for me to step on that land mine.

 

 

 

 

 

 

 

 

 

 

 

 

 

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The Case Against Education

Previously: Something Was Wrong, Book Review: The Elephant in the Brain

Previously (Compass Rose): The Order of the Soul

Epistemic Status: No, seriously. Also literally.

They sentenced me to twenty years of boredom

for trying to change the system from within

I’m coming now I’m coming to reward them

First we take Manhattan, then we take Berlin

— Leonard Cohen, First We Take Manhattan

This was originally going to be my review of Bryan Caplan’s excellent new book, The Case Against Education. I was going to go over lots of interesting points where our ways of thinking differ. Instead, the introduction got a little sidetracked, so that worthy post will have to wait a bit.

First, we have the case against education.

As in: I See No Education Here.

I

What is school?

Eliezer Yudkowsky knows, but is soft peddling (from Inadequate Equilibria):

To paraphrase a commenter on Slate Star Codex: suppose that there’s a magical tower that only people with IQs of at least 100 and some amount of conscientiousness can enter, and this magical tower slices four years off your lifespan. The natural next thing that happens is that employers start to prefer prospective employees who have proved they can enter the tower, and employers offer these employees higher salaries, or even make entering the tower a condition of being employed at all.5

Anyway: the natural next thing that happens is that employers start to demand that prospective employees show a certificate saying that they’ve been inside the tower. This makes everyone want to go to the tower, which enables somebody to set up a fence around the tower and charge hundreds of thousands of dollars to let people in.6

Rick (of Rick and Morty) knows:

 

 

Nassim Talib knows (quote is from Skin in the Game):

The curse of modernity is that we are increasingly populated by a class of people who are better at explaining than understanding, or better at explaining than doing. So learning isn’t quite what we teach inmates inside the high-security prisons called schools.

Talib considers this fact – that school is a prison – so obvious he tosses it out as an off-hand remark with no explanation. He’s right. If you’re looking at a classroom, you too know. Something Was Wrong. This isn’t a playground designed to teach useful knowledge and inspire creativity. It is a prison where we learn to guess the teacher’s password and destroy creativity.

Robin Hanson knows: School is to submit. Signal submission. Submit to a life of signaling, obeying, being conscientious and conformist.

This cancer has taken our childhoods entirely. Often the rest of our lives as well. It  replaces our hopes and dreams with hopes of survival via official approval and dreams of showing up naked to algebra class. Enough school so cripples your life, between losing time and being saddled with debt, that it severely damages your ability to have children. To get our children into slightly less dystopian prisons, we bid up adjacent housing and hire coaches and tutors to fill our kids’ every hour with the explicit aim of better test and admission results rather than knowledge. Then college shows up and takes everything we have left and more, with a 100% marginal tax rate.

School takes more than all of our money.

In exchange we learn little that we retain. Little of that is useful. Most of the useful stuff – writing, reading, basic math – we would have learned anyway.

In grade school I would often fake illness to get a day of solitary confinement in my room, where I could read books and listen to public radio. Also known as getting an education. I learned far more on those days.

In high school, I went to the hardest-to-get-into school in New York City. I had a great ‘zero’ period when I would do math competitions because I enjoyed them, and a great after school because I’d run off and play games. In between was torture. Literal clock watching. I spent history class correcting the teachers. I tried to take advanced placement classes, and they wouldn’t let me because my grades at boring classes weren’t high enough. So I learned I could take the AP tests anyway, which I did.

I actually entitled my big English class project “get me out of here” and no one batted an eye. 

For college, I majored in mathematics (STEM!) at a well-respected institution. I work with numbers constantly. I have never, not once, used any of that math  for any purpose.

I was intentionally taught to write badly and read badly. I learned non-awful writing by writing online. “Appreciation” classes turned me off music, art and literature. If you compared what I got out of one statistics course (in which I mostly learned from studying a textbook) to what I learned from the rest of my college classes combinedand asked which has proven more valuable, I’m not sure which side wins.

I took one graduate math class, in analysis. The remember three things. One is that they asked us to note on our final exams if we were undergraduates, so they could pass us. The other is that the class consisted, entirely and literally, of a man with a thick, semi-understandable Russian accent copying his notes onto the board, while saying the thing he was copying onto the board.

The third thing is that it was the most valuable class I ever took, because it saved me from graduate school. Thanks, professor!

II

Is our children learning?

Bryan has the data. Ignore Bryan’s data for now. Read and actually pay attention to Scott Alexander’s recent two posts on the DC public school system.

Instead of asking Scott’s question – why are DC’s graduation rates so low? – ask the question what the hell are these things called ‘high schools’ and what are we doing to the children we put inside them?

I know what we’re not doing. Teaching them to read, write or do arithmetic. That’s clear.

Instead? Fraud. We pretend to teach, they pretend to learn. Or rather, we tried that, and they couldn’t even pretend to learn, so we resorted to massive fraud and plain old not even testing the kids at all. We pretend to teach, and we pretend they pretended to learn.

We can’t even do massive fraud and really low standards right. Massive quantities of students fail anyway, barred from earning a living. Nice system.

Pretending the kids pretended to learn doesn’t work. Why? School isn’t about learning. It’s a prison. The ‘test’ is to be in your appointed cell at the appointed time, every time. Because it’s a prison. We don’t care if the kids can read, write or add. We care if they get credit for time served.

Bizzolt writes:

DC Public Schools HS teacher here (although I’m not returning next year, as is the case with many of my colleagues). As noted, one of the biggest factors in the graduation rates is the unexcused absences–if you look at the results of our external audit and investigation here, you see that for many schools, a significant number of our seniors “Passed Despite Excessive Absences in Regular Instruction Courses Required for Graduation”–over 40% of 2017 graduates at my high school, for example.

So the attendance policy is being strictly enforced now, and you can see how from that alone, a ~30% drop in expected graduates is possible. Some more details about strictly enforcing the attendance policy though:

1: DCPS has what’s called the ’80 20′ rule: A student that is absent for at least 20% of their classes is considered absent for the whole day.
2: Most schools have 5 periods, so an absence in one class would be considered an absence for the whole day.
3: If you have 10 or more unexcused absences in a class, you automatically get an F for the term.
4: If you are over 15 minutes late for a class, that is considered an unexcused absence.
5: A majority of these absences are in first period.
6: A majority of students in my school and many others live in single parent households.
7: These students are typically responsible for making sure their younger siblings get to school, if they have any.
8: Elementary and middle schools in my neighborhood start at the exact same time as high school.
9: Their doors do not open until 5 to 10 minutes before the starting bell, presumably for safety reasons.
10: Refer to point 4.

There’s many other problems at DCPS to be sure, but this set of circumstances alone is causing the largest increase in failing grades and graduation ineligibility at my high school, and basically every other 90+% black school in the district. You could see how this accounts for quite a bit of the difference between white and black graduation rates as well. There’s a reason why across the board, DCPS schools were not strictly enforcing this policy in previous years.

Fifteen minutes late to unnaturally early class so you could take a sibling to their unnaturally early class? You missed the whole day. Do that ten times in a term? We ruin your life. For want of two and a half hours.

I have no idea how one can see this, and present a human capital model of school with a straight face.

The signaling model is optimistic. It thinks students signal to employers, rather than politicians and administrators signaling to and stealing from voters.

III

Bryan Caplan’s economist hat is permanently glued to his forehead. So he sees school not as a genocidal dystopian soul-crushing nightmare of universal incarceration, but merely a colossal waste of time and money. He looks at the economic costs and benefits,  compares signaling explanations to human capital ones, and calculates when and for whom school is worthwhile. Worthwhile for which individuals, for their private benefit? Worthwhile to what extent for society, as a public good?

Reading The Case Against Education is to watch Bryan think. Bryan goes argument by argument, consideration by consideration, to consider the true costs and benefits of formal education.

At each step, you see the questions he asks, the way he sets up the problems, examines data, considers hypothesis and reaches conclusions. He acts like someone trying to discover how things work, sorting through what he knows and considering what the world would look like if it worked in different ways. You get a book about education, but you also get an education, where it counts – the question of how to think.

Bryan lives the virtue of local validity. This is super important; when Eliezer Yudkowsky calls it the key to sanity and civilization, he’s not kidding.

Because we get to watch Bryan think, we get tons of places where he and I think very differently. Many of them are worth examining in detail. There’s a lot of data that’s difficult to interpret, and questions without clear answers. Often Bryan is extremely generous to education’s case, and shows even generous assumptions are insufficient. Other times, Bryan’s logic leads him to be overly harsh. I got the distinct sense that Bryan would have been very happy to have been proven wrong. We get a consideration of education, its pros and its cons, as Bryan sees them – an explorer, rather than an advocate.

Overall, what does Bryan find? Time and again, Bryan finds that the signaling model of education fits the facts, and the human capital argument does not fit the facts. His arguments are convincing.

Bryan concludes that if you take what you’ve read and experienced and shut up and multiply, no matter how generous you are to school’s cause, you will find that social returns to schooling are remarkably terrible.

That’s most of the human capital you get from school anyway: Reading, writing, basic math and shutting up. You get selfish returns to school by signaling conformity, conscientiousness and intelligence. To not follow the standard procedure for signaling conformity and conscientiousness is to signal their opposites, so we’re caught in an increasingly expensive signaling trap we can’t escape.

Bryan then bites quite the bullet:

Most critics of our education system complain we aren’t spending our money in the right way, or that preachers in teachers’ clothing are leading our nation’s children down dark paths. While I semi-sympathize, these critics miss what I see as our educational system’s supreme defect: there’s way too much education.

He means there’s way too much formal education. I don’t think Bryan thinks people spend too little time learning about the world or acquiring skills! He thinks they do so via other, far superior paths, where they remember what they learn and what they learn is valuable.

People don’t know things. People need skills. It’s a problem. School doesn’t solve the problem, it exacerbates it.

Bryan’s proposed remedy is the separation of school and state. At times he flirts with going farther, and taxing school, but recoils. We don’t really want to discourage school the way we discourage, say, income. Do we?

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Nice Things

Previously (not required): What Is Rationalist Berkeley’s Community Culture?

Response to (at Otium, highly recommended): Naming the Nameless

The strongest attractor is to that which attracts.

To pleasant interactions. To invisible, quiet competence. Things that ‘just work.’ Only the options you didn’t know you wanted. Where that which sounds right, and feels right, is right. A land of smiles and trust.

Nice things. They’re nice.

We can have them!

As Sarah puts it:

But for your typical consumer, the generic California/BoBo style works fine.  It signals elegance, which means, more or less, that it’s designed for educated, high-Openness, upper-middle-class, urban people.  When I enter a space or a website with this aesthetic, or buy a product with this branding, it’s shorthand for “Ahhhh, this place is run by competent professionals who know how to give me a pleasant experience. I will not feel harried or inconvenienced or confused here; I will be well taken care of.  I will easily be able to slot my existing behavior patterns into the implicit “rules” of how to use and navigate this place or device or website.”

I gotta admit it. Nice things are pretty sweet. The best part about nice? When you’re done appreciating how nice it is, you can stop paying attention. Nice becomes background. Focus advances. Life is better.

I wants them.

But, at what cost? What is the price of nice?

Two prices.

The first price, attention to detail. The quest for nice things is a sacred quest. Creation of them, even more so. It requires effort, focus, sacrifice. You have to care.

Otherwise, we can’t have nice things. Because you didn’t make them.

The second price, the equivalence of niceness and rightness. Nice defends itself by banishing the not nice. In ways not nice. It pretends not to notice.

When you can’t or won’t pay for the shields, and don’t preserve them, that too is why you can’t have nice things. Because you break them.

If one uses not nice to banish and hide not nice, what counts as nice matters quite a bit.

Anyone, anything, anywhere that can create and preserve nice things, on any level, deserves praise. I may sometimes think of Berkeley as the devil, or the enemy, but one must give him his due on aesthetics. He’s a man of wealth and taste. On this, devil delivers.

But what, then, in such a place, is nice? Is nice now an aesthetic, a style, rather than a substance? And hence, is it the aesthetic of having the aesthetic? Has the thing been banished by the symbolic representation of the thing? Does this tyranny of superficial niceness inevitably create a particular ideological cascade? It seems to. Does it banish truth, slowly pressuring all into conformity, via the Scott Alexander quote that cannot be repeated enough times, so here it is again:

Sometimes I can almost feel this happening. First I believe something is true, and say so. Then I realize it’s considered low-status and cringeworthy. Then I make a principled decision to avoid saying it – or say it only in a very careful way – in order to protect my reputation and ability to participate in society. Then when other people say it, I start looking down on them for being bad at public relations. Then I start looking down on them just for being low-status or cringeworthy. Finally the idea of “low-status” and “bad and wrong” have merged so fully in my mind that the idea seems terrible and ridiculous to me, and I only remember it’s true if I force myself to explicitly consider the question. And even then, it’s in a condescending way, where I feel like the people who say it’s true deserve low status for not being smart enough to remember not to say it. This is endemic, and I try to quash it when I notice it, but I don’t know how many times it’s slipped my notice all the way to the point where I can no longer remember the truth of the original statement.

Is GT’s Kombucha, the symbolic representation of the symbolic representation of the thing that hates symbolic representations of things, the inevitable endpoint? Inclusive symbols of exclusivity, as we come together to be intolerant of the symbolic representation of intolerance, and hence, inevitably, of actual real things?

Not only the abyss, when gazed into, also gazes into you.

 

 

 

 

 

 

 

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