Chris X Edwards

The cover of O’Reilly’s Effective Modern C++ by Scott Meyers promises "42 specific ways to improve your use of C++11 and C++14". I had a subtly different motivation for reading it: basically general improvement in my knowledge of modern C++.

I actually first learned object oriented programming by teaching myself C++. You would think that since that was in the late 1990s that my decades of C++ experience would be an asset. Turns out, not as much as one would hope. About the time I was doing some heavy duty things with C++ its creators were busy rearranging it. A couple of years ago, I was confronted with some "modern" C++ and I could barely follow along.

In theory, they had made it "easier" of course. In practice, I’m not so sure. (The N4659 C++17 standard is 1622 pages long!) For those of us who know how to use pointers, allocate memory scrupulously, and comfortably micromanage things, messy obfuscatory changes weren’t necessarily comforting. My philosophy is not far from, if you don’t understand what you’re doing, you probably shouldn’t do very much of it. But that is not the new ethos of C++!

Whatever. That’s fine. It can not be contradicted that old C++ was damn inscrutable and harsh. So much so, that I suspect it might be easier to just reimplement what C++ promises in plain old C. Regardless, I do need to be fluent in the modern C++ idioms so when I saw this book, I put it on my wishlist; when I started my new job, a copy was coincidentally lying around in my office! Yea! I figured that maybe I could get comfortable with the modern approach and feel better about the language.

That didn’t exactly happen. I did come to understand the benefits and liabilities of the language features that had been added since I first learned C++ so many years ago. But I didn’t get the feeling that everything is ideal now. Part of the problem is the unsettling tendency that the C++ standards committee will inevitably keep morphing the language making it very hard to get settled for the long term. For example, imagine you had been trying to keep an OS kernel going since 1993 to the present — C++ would have been a disaster.

By reading this book, I was able to fill out my extensive C++ Notes with all the modern bells and whistles. To put it that way is kind of misleading. The modern trappings are far from minor decorative accoutrements, but rather a profound shift in how most practitioners actually write code. I have come to believe that modern C++ programmers have bifurcated into two "classes" (ahem): experts and the non-experts. Putting it simply, the experts write libraries and the non-experts (try to) use them. The experts must know gory hideous details that make old C++ (and very old C) seem simple and charming. The non-experts are doing their best to have no idea how C++ works at all — they just want to get on with their work in some other domain.

Hence new arrivals like auto for assigning types to variables. C++ is, in theory, a strongly typed language. But if auto, in practice, eliminates the need to fastidiously plan data types, then something seems not quite ideal for Team Strong Type. The fact is that auto creates all kinds of horrendous mischief for the aforementioned experts and greatly simplifies things for the non-experts. I know about the mischief because the entire second chapter is dedicated to this topic.

My personal goal was to learn briefly everything involved in what the experts must deal with, but only so that I can make better choices as a more ordinary user of various libraries. For that this book was ideal. I could follow along with about 95% of it but I’ll remember only about 5%. I do, however, believe that my intuition is now much better about modern C++ arcana.

I almost felt sorry for the author — what a terrific intellect wasted on the minutia of this raspy programming language! But I hope he has a good job and is happy with having climbed to the top of this obscure austere intellectual mountain. The book’s organization and writing were very good. What I really appreciated was the author’s humanity. No pretentious bombast here from someone who clearly knows a lot more about a complex topic than any of us little people. The humorous deprecation he unloaded on the language from time to time definitely kept it real and let me know that he understood that someone like me would find a lot of the "simplifications" absurdly complex. If you learned C++ in the stone age like me, this book is good. If you’re one of the hard core folks who writes OpenCV or TensorFlow or something like that, knowing everything in this book probably is mandatory. If you’re simply using OpenCV or TensorFlow, you can probably skip this and muddle through.

Here are some of my favorite bits.

p97 P1 S1: "If there were an award for the most confusing new word in C++11, constexpr would probably win it."

p109: "Yes, yes, ancient history: Mesopotamia, the Shang dynasty, FORTRAN, C++98. But times have changed, and the rules for special member function generation in C++ have changed with them. It is important to be aware of the new rules, because few things are as central to effective C++ programming as knowing when compilers silently insert member functions into your classes."

p149: "But I’ve shown you C++98 code, and that reeks of a bygone millennium. It uses raw pointers and raw new and raw delete and it’s all just so… raw."

p158: "No matter how far you dig into [move and forwarding semantics], it can seem that there’s always more to uncover. Fortunately, there is a limit to their depths. This chapter [5] will take you to the bedrock."

p170: "That’s the kind of behavior that can drive callers [of member functions] to despair — possibly to violence."

p181: "This leads to behavior that’s intuitive only if you’ve spent so much time around compilers and compiler-writers, that you’ve forgotten what it’s like to be human."

p181: "That function will [do a bad thing], your compilers will throw up their hands in exasperation, possibly punishing you with long and incomprehensible error messages as an expression of their displeasure."

p191: "If you’ve never seen anything like this [code] before, count your blessings."

p195: "The resulting error message is likely to be, er, impressive. With one of the compilers I use, it’s more than 160 lines long. … The more times the universal reference is forwarded, the more baffling the error message may be when something goes wrong."

p205: "The motivation for the SSO is extensive evidence that short strings are the norm for many applications." [Good for many applications written by normal programmers?]

p219: "[You may believe] Only loser C++98 programmers use raw pointers and delete. That may be true, but it’s irrelevant because you do, in fact, use raw pointers, and they can, in fact, be deleted out from under you. It’s just that in your modern C++ programming style, there’s often little sign of it in the source code." [Some hints about the degree to which C++ hides the truth.]

p239: "When bind was unofficially added to C++ in 2005, it was a big improvement over its 1998 predecessors. The addition of lambda support to C++11 rendered std::bind all but obsolete, however, and as of C++14, there are just no good use cases for it." [That was an easy one! I missed it completely!]

p248: "Instead, you have to call a timeout-based function — a function such as wait_for. In this case, you don’t really want to wait for anything, you just want to see if the return value is [deferred], so stifle your mild disbelief at the necessary circumlocution and call wait_for with zero timeout…"

p252

[If someone told me this syntax was a joke, that would be easier to believe, but no, it’s real modern C++ — at least for programmers who wouldn’t just use 1e7.]

p263: "The first issue with this approach is what’s sometimes termed a code smell: even if the code works, something doesn’t seem quite right."

p291: "Because you’re a C++ programmer, there’s an above-average chance you’re a performance freak. If you’re not, you’re still probably sympathetic to their point of view. (If you’re not at all interested in performance, shouldn’t you be in the Python room down the hall?)"

Here is a parody image I made for my C++ notes long ago that is supposed to be humorous, a joke.

But now that I look at it, the humor is really too dry — C++ is so ridiculous that this is a very plausible book! (And my notes show an earnest attempt at starting that project.) Modern C++ is a mess. Meyers' book has shown me that my misgivings about it (which are very similar to Linus Torvalds') are not completely unrealistic. I feel that C++ is too muddled and baroque to compete with truly helpful (but generally slower) languages like Python (or even Bash) for simple prototyping or organizational tasks. I feel like it loses to C on performance by definition. For me none of the "features" of C++ make programming "easier" than programming in C. I am thankful that I had the good sense and luck to start my serious programming education by reading K&R cover to cover. To me C++ seems an unnecessary monstrosity. I think this mess is sadly shackled to (and evolving away from) the one fact that completely exonerates C++ as brilliant and sane, and the reason I’ll continue to happily use it with a smile on my face: at least it’s not Java!

I just finished the latest 900 page monster from Neal Stephenson. There may be some slight spoilers in this review, but probably nothing the dust jacket doesn’t say and it might also help make the reading more interesting. This review has turned out much longer than I expected, but if long form reading isn’t your thing, Neal Stephenson is not for you. I am a huge fan and I will always read everything this guy writes, but I have to say, I probably won’t recommend this particular book to people who are not committed fans. The reviews at the world’s largest bookstore, for example, seem rather disappointed. They basically all say stuff like, "Long time fan but, meh."

I wonder if some of the imagery went over people’s heads. For example, there’s a main character named Elmo Shepherd. Funny name right? Well, he turns into the ruler of an afterlife kind of place and they call him "El", you know, the word for god in Hebrew. And "Shepherd"? That lays it on a bit thick as I read it. And there is all kinds of religious and mythological and linguistic symbolism dripping from the pages. But do people care? Do they even get it? Having carefully read Genesis (et al), I understood a lot of it and I didn’t get the feeling that this was a style I really would like to see way more of. A lot of the dialog and prose was styled after religious texts which may not really be the best way to win popularity contests or make easy reading. My typical pace for a Stephenson book is around 250 pages a day but this one was about a quarter of that.

For me, it was worth reading and thought provoking even though I came away pretty sure the premise was faulty. Still, this was a mixed bag and there were some nice gems. As with Seveneves, Neal roughly split the book into a few main sections each with different settings and plot arcs.

I can be a cranky personality to be sure, but Neal’s frustration and rage at the modern American Idiocracy was so itellectually brutal that I can tell that he, like a lot of people, definitely needs a hug. Remember back when I figuratively kick the State of Indiana in their collective testicles for being disgusting hypocrites? (Any Hoosier reading this knows what I mean and that I’m obviously not talking about them and other people who possess sufficient literacy to actually read the Bible.) Ya, well, Neal goes on a similar rampage against his heartland boyhood home (Iowa) that makes my disgust seem quite jolly.

He actually fictionalizes a Libertarian "utopia" which is called Ameristan, exactly as if the Taiban live there. Exactly. It is populated by charactures of absurd Murican batshit insanity that would be ridiculous if it were not for the fact that we’re already half way there.

Throughout this section I couldn’t help but hum to myself this little hilarious song I composed.

(You know the tune — go ahead, "turn it up".)

Now throw in the major symbolism of part three — the God character, El, throws down the diety, Dodge/Egdod, to a place pre-industrial Christian simpletons might imagine Hell to be like. This parallels a famous character of the Bible who is cast down by God from "Heaven". Here Neal attempts full castration of Ameristanis, for Dodge, the main character who is actually the good guy hero, is basically Satan. Alrighty then.

I will say that if there is anything that can make me sympathetic to the Ameristani view that coastal elites are tedious swine, it is reading about rich people. Ug. I’m completely with Teddy Roosevelt who said…

I wish Neal would return to writing about underdogs who prevail despite their lot in life (e.g. Snowcrash, Zodiac, etc.). Writing about a guy lucky enough to make a living in the video game world is not helping me care. The fact that he’s also a billionaire who literally succeeds Yahweh makes me even more apathetic. Is this like one of those deals where Hollywood can’t make interesting movies because of (among other reasons) Chinese pressure? Maybe Neal can’t portray the richest man in the world as a villain because that guy is a personal friend of Neal’s and/or owns the world’s largest bookstore.

Despite the problems, reading this was not at all unenjoyable. My favorite memorable thing is the word "miasma" which Stephenson uses as an oh so perfect drop in replacement for "internet". I’m totally using that from now on. Another one is "din" to describe the flood of email and notifications clamoring for your attention. Another brilliant linguistic insight: the prose subtly asks the reader to consider the semantics of the modern "Submit" button. Chapeau, Neal. Nice.

In some places I felt the futurology was a little off. For example in this passage which I otherwise agreed with and loved, "Pete lowered the phone into the sweet spot of his reading spectacles and wrestled fruitlessly with its UI, which had been terrible twenty years ago." Really? We’re going to use these crap phones for 20 more years? Ya, probably; I guess we’re cursed for a long time. Sigh.

A character refers to a place like a "digital North Korea", I guess referring to the fact that North Korea is poor and poorly lit. But if this is set in the future, that’s making a big assumption about how tenaciously that country will cling to dim backwardness. Again, could happen.

Another character had a house key. Come on now. I have digital locks on my house now. Remember, house keys are utterly obsolete. Now!

The vague futurology with respect to autonomous vehicles is probably deliberate. This on page 518.

And when I read this, I was wondering about the composition of this "used market" — who wanted such obsolete tech? Whatever.

I was, however, encouraged to see (on p572) autonomous watercraft get some love — one character moves to a houseboat on a lake and, "When she was really in a hurry she could do the commute in a robot boat or robot car." Yea! I am making that happen personally!

Speaking of things I do professionally, one of the main characters is hired and given an HR category of "Weird Stuff"; I totally get it because that is exactly the department I must work in.

I was delighted when one of the tech savvy computer nerd characters does (on p457) exactly what I’ve been saying that fictional elite hackers should occasionally do for true realism: she refers to a man page! Man pages will never die!

All that stuff is the warm up. The real meat of the story is the tech nerd dream of uploading one’s brain into a computer and achieving immortality. For the record, I personally am not one of those tech nerds. And one of the main reasons I am not is because I’m just too aware of the problems. For me it’d be no less sensible to want to transmogrify myself into a sentient hovercraft full of eels. Nope don’t want that either, but we can all see that’s probably a foolishly unrealistic goal.

Neal is no dummy and ironically the best criticism of the book’s major premise is found right in the book. I was thinking about this exact problem right up until I read it described quite well on page 336.

Nice pun there at the end, Neal, but hey, what about that? I didn’t notice this major flaw ever really getting resolved. I had to just flip a "fiction override" switch in my brain at that point and carry on with disbelief sufficiently suspended.

Although that quote only hints at philosophical problems, those are definitely troublesome too. For example the afterlife basically consists of starting anew in a brain structured like the one you had while alive, but entirely ignorant of earthly life. If your brain contains memories, why would scanning selectively omit your personal identity? And then, philosophically, what’s the point of that exercise? It is functionally a twin of you, not you. Maybe some intuitions and know-how were preserved, but memories of the old world are strangely absent. If you are not going to persist, really, why bother? You know what else is a lot like you but is not you, yet often persists after your death? Progeny. Much easier.

Ok, fine. If heaven is distinct but inspired by residual ideas and imagery lurking in people’s brains when they die, why are there not more things like special forces commandos or orcs or droids or Lego minifigs or porn stars or television sets or soft drinks or automobiles, etc. Surely that stuff is weighted into people’s neural networks just as much as the Game Of Thrones imagery which seems to dominate the afterlife’s decor. Come on, let’s be real — if the brain scan picked up anything, all inhabitants of the afterlife simulation would be in constant anguish until they could be admiring and fondling a telephone.

An even bigger problem I had is that I never quite understood exactly how this brain simulation morphed into a simulation of a space shared by many brain simulations, a different data structure created initially by the first of the simulated brains. So did the necessarily exacting reproduction of the brain spontaneously start to do double duty as a platform for hosting a very complex virtual world model? Let me tell you, those things are very different! Achieving them by chance (i.e. without explicit programming) seems very unlikely. Waving the magic wand of "quantum computing" seems pretty tepid. Might as well also throw in some string theory to tie that plot together.

One thing that seemed to go completely unexplored (but feel free to chat about it at your next philosophy club meeting — free of charge) was the question of how would people’s attitudes change about the afterlife when they were presented with a plausible system for preserving human brain processes indefinitely? It sure would rob the vague normal religion mumbo jumbo of a lot of its charm. I think it would be very hard to even pretend to care about a deceased relative’s "real" soul off in "real" heaven when you can plainly see their technology-enabled soul doing the stuff they used to do when they were alive (i.e. staring at their telephone).

The final problem I’ll mention is one that seemed a pretty serious plot defect. Even if people lost their clear memories of their personal identities when their brains were scanned and simulated, why would the "real" world maintainers of the system not want to communicate with the dead? We know they can visualize the dead "soul" activities so they must know where some of those qubits are in the computing systems. Just inject some interesting Easter eggs for the citizens of heaven to find. Eventually one character manages to do this but in a really oblique overly complex way. Why not just spell something out on the ground with rocks and see if some of the Heavenites remember how to read?

And then there was the end section which was a grand D&D-style quest with lots of sword fighting and mana magic. Uh huh. I don’t mind that genre, so fine. While I was reading that I kept fondly thinking about a really good book I read that was actually quite similar but way, way better. One of my favorite novels ever in fact. Same high quality writing. Same middle ages knight fight stuff. The most epic questing ever. Cool characters (one unforgettably named "Mountain of Skulls" — how cool is that?). Superb complex intrigue. No dopey deus ex machina Hogwarts magic. And an incredible alternate universe spin on actual fascinating real history. That book was the Mongoliad, written by Neal and his pals. Damn Neal, you’re a tough act to follow! But if anyone can surpass Neal Stephenson, it is Neal Stephenson — I’ll keep giving him a chance to do that for as long as he’s willing to try.

A couple of years ago I wrote a post about how the ubiquitous machine learning metaphor of brain cells was somewhat misleading and definitely unhelpful. If I explain A by saying it’s like B, but you really have no idea about B, then that must be a worse explanation than not mentioning B. And I know that you do not know how brain cells really work because I know that nobody knows how brain cells really work. I therefore proposed trying to think of other metaphors or aids to understanding what is going on.

My idea was a physical model that people with a mechanical aptitude might like. I do realize that it might be too difficult to imagine my impractical physical models actually doing the job. I have just come across another way of thinking about machine learning networks that is more similar to what I describe than traditional Von Neumann computers chiselling away at tensor bits.

This interesting physical system involves light. By shining a light into a very specially prepared nanophotonic structure, it can get diverted and bent such that the input patterns can converge on a classification. Here’s a paper that talks about classifying numbers in this way: Nanophotonic media for artificial neural inference (Erfan Khoram, Ang Chen, Dianjing Liu, Lei Ying, Qiqi Wang, Ming Yuan, and Zongfu Yu).

This is the classic (MNIST) task that started a lot of modern interest in machine learning

The handwritten number to identify is encoded into light waves, conceivably just as it is when you read numbers with your eyes, and after those light waves go through the system, they emerge concentrated on a particular output position corresponding to a class of number, e.g. the number four. In this way, handwritten numbers which are not exactly all alike can be separated into which particular digit they’re supposed to represent. This video nicely illustrates the system and here is a helpful image from the paper.

That’s what I call very OCR!

This concept is interesting because it shows that the principles behind modern neural networks do not need to be realized only on computers. Once the machine learning has happened and training is complete, as with my hypothetical mechanical system, there need not be any more computer computation at all. Indeed I suspect a lot of clever things in biology just happen, tumbling forward through various situations, based on such previous training. That training is evolution.

In case the point of why this is interesting is not clear, let me give a hypothetical example that would make perfect sense in a science fiction novel. Currently we have light sensors that, for example, know it is night time and that we would like the driveway light to turn on. Although that is useful enough to be a product people want, it is as simple as such a system can be. Imagine instead a light detector that recognized your face (and not the faces of other people) and triggered the garage door to open. When light from the scene bounces into this system in the same way it would bounce into your eyes, the light is directed to a simple photoresistor controlling the door based on the very sophisticated ability to filter your face out of everyone else’s. Keep in mind that would take zero computational energy to do this rather clever trick.

It is nothing less than a way to give inanimate objects eternal intelligence.

I think the possibilities are quite fascinating. I expect that there will be different kinds of stock modules (e.g. nonlinearity, pooling, etc.) allowing one to compose interesting neural nets with a minimum of custom fabrication. I can imagine these kinds of systems being especially effective in aggregation, like a fly’s compound eye. I suspect that there will arise an entire field of computer science that simulates and organizes these kinds of systems. I certainly will be thinking about the concept’s potential. I wonder what other substrates "neural" networks can be encoded into. Hydraulic? Check out the fascinating MONIAC. Radio waves? RFIDs are already interesting, but I’m thinking of using the wave mechanics. Sounds could also work to create an intelligent ear. I think it should also be possible to computer cut/etch steel or other metal to make an intelligent system out of harmonic resonances. A lot of interesting potential.

It is also interesting to consider the philosophical perspective of something like a block of glass that can make intelligent decisions. Is there ever a level where it deserves "human" rights? Will there arise People for the Ethical Treatment of Intelligent Rocks?

Economics professor Bryan Caplan, an elite practitioner of formal education, has shit in the nest of formal education by writing a book excoriating almost everything about it. When it comes to formal education, I’m also an unusually harsh critic. For example, I have previously written about the futility of teaching calculus in the modern world. When I heard that someone had written a whole book calling bullshit on education, The Case Against Education was at the top of my reading list.

My years of formal "education" were painful. With decades of hindsight I am now more sure than ever that the problem was not simply my deficiencies. But go to university I did and I clearly remember sitting in my (required) economics classes and having a very profound stroke of insight: if this class is not bullshit, my time spent in it should be fungible with money. What I discovered over the years is that economics courses do not magically unlock secrets that increase personal wealth but that the magic piece of paper which these courses were required to obtain do. My degree, industrial engineering, is about bringing engineering methodology to bear on maximizing returns and minimizing investments. It didn’t seem unnatural at all to turn this ROI maximizing analysis back onto the educational process itself. It was hard not to notice the extensive room for improvement.

That there is immense room for improvement in modern education is basically the entire thesis of Caplan’s book. Like Caplan, I also have a lot to say about the topic of education and for the purpose of remembering this book I’ll say much of it here. I made a lot of notes while reading this so I apologize in advance if this is overly long and disjointed.

Rather than calling it the "The Case Against Education", a more accurate title would have been the phrase used on page 239: "The Case Against Actually Existing Education". Caplan uses "education" the way it is used in the phrase, "increased funding for education". This is the "provide schooling for" definition of education. He’s not talking about the particular dictionary definition of education that is "to develop mentally, morally, or aesthetically especially by instruction". What Caplan is arguing is that all of the ostensible goals of that second definition of education are thwarted by how the first is actually practiced.

I feel like the provocative title may actually detract from efforts to improve the situation. If people are so repulsed by the apparent argument against the idealistic notion of education as they imagine it, they may not investigate beyond the absurd sounding title. Buried in the book, Caplan does make it clear that he does truly care about real education. He makes a fuss because education humbug is actually detrimental to true education, something you could say he is making the case for. That is definitely how I feel about it.

The book asserts that current educational regimes are easier than they used to be and getting easier. Physics degrees, however, are never out of fashion because they are simply a proxy for any random instruction that is genuinely difficult. "As long as you avoid rare, demanding paths like engineering and premed in college, you bask in the warmth of a four-year vacation." As someone who completed one of those more challenging majors (some time ago) and who until recently provided engineering tutoring to computational molecular biophysics grad students professionally, I’ll have to take his word for it. He does provide data.

One damning point he correctly brings up is that the internet is the embarrassment of "education". What does formal education purport to achieve that the internet is not utterly upstaging? Here, for example, is an astonishingly good explanation of Fourier transforms which live instruction could not dream of bettering. Caplan points out that critics point out that this only serves self-motivated people. To which he says, to ask for more is petulant; I completely agree. This leads me to believe that if education were obvious, everyone would do it. I don’t just mean attend college, but also compulsively read Wikipedia, have a big library agenda, watch educational videos on-line more than TV, audit courses from MIT and Stanford, etc. But as far as I can tell from the popularity of general internet Prolefeed, most people are just not truly into education despite what they may claim.

Some problems with education seem obvious but they are far worse than you might imagine. For example, the staggering costs — if Caplan is to be believed, education costs vastly more to society to provide ($11e11) than defense ($7e11). Let that sink in. Read the book if you’re doubting the numbers. And there must certainly be similar or worse opportunity costs — students sitting there wasting potential en masse.

Part of what makes education so futile is that retention is almost nonexistent — he cites a study where 25 years after learning algebra and geometry in school, almost everybody had forgotten almost everything about them. He uses the idea that schools can’t be responsible for more than 100% of what people generally know about subjects they’ve been "taught", i.e. disturbing levels of post graduation ignorance show how sad the ultimate effects of education are.

Here is an email from my son’s math teacher (who I am sure is a hard working competent person using best practices). Note how they struggle to hold the house of cards together until they reach the safety of The Final Exam.

No mention of ensuring recall for the (basically nonexistent for most people) opportunities to apply this learning in one’s actual life. As you can see, this "education" is designed to be forgotten.

I’ve always felt that homework was an intellectual failure of the education process. It’s a bit like saying that flat pack furniture provides quality of life by giving you something to assemble. Worse, I remain unconvinced of homework’s efficacy. I am now not alone. On page 241 Caplan calls the majority of schooling "insipid busywork". I pretty much agree.

It is now easier than ever to properly criticize traditional education because there are now much better options. I hope that cost-effective, convenient (to everyone) on-line courses which are focused on functional useful skills that employers truly want employees to have (e.g.) will start to eclipse the fluff and bother of a misdirected, onerous, unpopular educational process in the traditional format that Caplan is criticizing.

Caplan’s main thesis is that education is mostly signaling. He thinks the ratio is around 80% signaling and 20% genuine "human capital", i.e. skills of value to society. He basically believes that current educational practices give kids all of the fun and joy of child labor with almost none of the productivity or practical vocational training. Kids today learn what is valuable in a perverse artificial marketplace of grades and other nonsense while kids working jobs in the past at least were educated about what society found truly valuable. That’s right, Caplan flirts with advocating for child labor and I have to say, he made a pretty good case (unless you hate children).

Caplan believes school in general is getting easier and that there is grade and degree "inflation" where students attain higher grades and degrees than in the past for the same amount of work. Here is a NYT article about how much good grades matter; short answer, they don’t. Caplan argues that this just wastes students' lives.

"Intellectual inbreeding" is Caplan’s term for the fact that professors teach what they have been taught, and "relevance" is only attended to in that academic context. Otherwise intelligent educators may be largely blind to the deficiencies of current educational practices because, as the saying goes, "It is difficult to get a man to understand something, when his salary depends upon his not understanding it!"

If most real and valuable learning is done on the job (and Caplan’s mountains of data say that is true), formal education is actually robbing us of valuable education.

Caplan really is convinced (again, mountains of data are provided) that 80% of the schooling experience is dedicated to signaling. Four days a week kids are figuratively growing peacock feathers at school.

Signalling is a zero-sum game (if I’m the best, you’re the worst) but real skill development is not (if I’m skillful and you’re very skillful, together we are even more skillful). Caplan points out, "Conventional education mostly helps students by raising their status, but average status cannot rise." That is an interesting thought.

On page 240 he reiterates exactly what I’ve said are the two essential ingredients for any effective presentation: a presenter who is genuinely interested in the material and an audience who is. Caplan adds a third essential ingredient — actual interesting content. While somewhat true, I would argue this mostly sorts itself out automatically with the other two. The important point here is that to say the typical classroom, at any level, is filled with people genuinely interested in learning (or teaching!) what is being presented is nonsensical.

Of course education does have some noticeable effects. For example, this article explores the question: is too much indoor time causing myopia? And in an astonishing and evolutionarily stupid twist, according to the book the main quantifiable result of education is to limit fertility. Yes, the truest clear actuarial thing that can be said about the way we practice education now is that if you subject your kids to it, you’ll have fewer grandchildren. Awesome.

Caplan does a pretty thorough job of thinking of ways that current education practices are deficient but I thought of some more. For example, I wonder if there is anti-signaling — normal people dumbing it down to gain status in some social strata that I am not a part of (perhaps related to this topic). Remember, some people do want grandchildren!

Another problem I easily perceive is what if you’re a generalist and want to octuple major in mechanical engineering, mechatronics, technical writing, urban planning, operations research, information theory, statistics, and computer science (with a "focus" on programming, graphics, networking, and machine learning)? Not only is the current configuration designed to not accommodate that, it is designed to eradicate any such thinking. To the education business, the idea of a generalist is literally worse than the idea of an ignorant person. Taking cues from education, how then does industry value these kinds of people — pretty much zero. (I can assure you!) Then consider the kinds of people who actually bring profound change to the world — they are often people who can fuse disparate fields like Ben Franklin, John Von Neumann, Paul Erdos, DaVinci, Bertrand Russell, Isaac Asimov, Leibniz, etc. Today any one of those guys would have been diagnosed as having a mental disorder and pumped full of magic beans to cure their ADHD. I don’t have any obvious solutions but the intense focus on a "major" with "high" achievement funnelled into absurdly specific PhD research certainly isn’t helping.

I’ve talked about the problems Caplan highlights in his book, but now let’s take a look at the problems with those problems. What are the reasonable counterarguments? First, here is an excellent critical reveiw of the book.

For me, it is too difficult to imagine that literacy is not helpful and attaining it is not important. Caplan is trying to shake such core beliefs but as a natural reader, that one is tough. But I’ve known illiterate people who got along just fine except for the stigma of illiteracy. The number of books those people read were pretty close to the national average of almost zero.

It is possible society needs to train 80% of kids to understand trig so that you can eventually produce society’s necessary 5% of engineers. Another thought I had is that since one of the best ways to learn something is to teach it, perhaps a captive audience of students is required to get grad student TAs up to the very top levels needed to sustain our technological civilization. That’s a messy trolley problem for you!

Caplan says, "And if we know anything about the future of work, we know that the demand for authors, historians, political scientists, translators, physicists, and mathematicians will stay low." I could argue for the (increasing) utility of these but let’s focus on the last two. It could be that very hard subjects like physics or math, besides signaling difficulty, are good at giving young people a practice domain that is broadly applicable. I know for certain that many very good practical programmers started out as physics and math majors. Caplan would ask, wouldn’t it be better to just have them study programming? Perhaps. However, given the programmer inbreeding problem, I could see how fresh perspectives might be valuable. Still, counting on that is tenuous.

One bonus of education that is not appreciated by the book — do not underestimate the confidence that you can do complicated stuff which comes from having done different complicated stuff in college, a relatively safe practice environment. Here’s an exact example between minute 1 and 2 of this talk. This may be borderline vocational though, which Caplan believes is perfectly valid and underappreciated.

A thought I had in defense of education was prompted by the question of whether reading itself was valuable. My readers (who are all highly literate and lovely and intelligent and good-looking and all around great people) may be shocked by the question but apparently it is very debatable. I wondered what I got out of reading. I certainly can completely forget everything about a book in a couple of years (hence reminders like this post!) but I rationalized that it might be more of a kind of neural network training than a "memorize these facts" kind of thing. Certainly you can read a humor book and find it funny and have memorized none of the gags. Reading does more broadly rewire your thinking in subtle ways that probably are beneficial. I think some of that reasoning applies to general education too. Of course some would argue that kids in school are getting their neural nets primed to submit to dull oppressive boring jobs as professional conformists.

I kind of get the feeling that the whole education circus might be a way to give natural nerds a chance to do a lot of reading and nerd stuff. But today, with near-compulsory signaling, people who do not enjoy reading (or writing long blog posts about the subtleties of education) or self-directed study of any kind are swept up in the "education" frenzy. That would be fine if it wasn’t such a futile waste of people’s lives.

A fun question I had — is Caplan trying to elucidate something with this book? Or is he merely signaling? I’ll arbitrarily give it a 80/20 split to highlight the arbitrariness of such a conclusion. ;-) Caplan has more support for his numbers, but not much more. Although I’m giving him a bit of a hard time, I did actually come to accept his 80% signaling as probably pretty close and certainly much closer to reality than 0% which is the ostensible figure. I don’t know if he properly does the math, but he certainly does quite a bit of math.

Education seems like unquestionable anti-evil magic. To just say the word puts everyone on the same page. People may quibble about how much to spend on the details of the education budget, but if cost were no object, it is taken for granted by pretty much everybody that any "education" is good education. Caplan is pretty brave to be the guy — in education no less — who thinks the matter is at least questionable. He questions it. He discovers that when looked at analytically the same way people make value propositions about most other facets of life, education comes out quite badly for both kids and society in general. He finds that taking the status quo for granted has produced muddled thinking about education and its worth. He finds that there are much better ways to invest our energies that better satisfy education’s presumed goals.

As someone who immediately suspected the same theme throughout my formal education, I am gratified to read such strong evidence that I wasn’t simply the one being petulant. Of course I am saddened by the current state of formal education which seems rote and somehow not genuine to me. I can only hope attitudes change and people start to question the true practical real-world effectiveness of schooling done in the ordinary way. The good news is that for those with an intrinsic motivation to learn who desire to be intellectually challenged thereby, there has never been a better time to be alive — despite the prevalence of schooling.

UPDATE 2019-07-16

Here’s an interesting article for people who have misgivings about school. Turns out that Steven Spielberg was rejected from two film schools despite being an obvious precocious prodigy. The reason: he simply hated school and got bad grades.

UPDATE 2019-07-22

I only read the abstract, but this paper seems to suggest there are diminishing returns to education: The Remarkable Unresponsiveness Of College Students To Nudging And What We Can Learn from It. I love the ironic "what we can learn from it" subtitle — might as well parenthetically add, "if we’re self-motivated."

I’ve now been in Buffalo for 11 months. The time has really flown by. After decades of no seasons in San Diego, having a proper one show up ever few months is quite a change, a pleasant change! Spring is quite a spectacular time of year. Living things suddenly burst into existence everywhere. Everything turns green. It’s quite a transformation.

Here are some photos that show some of what spring in western New York is like.

Here’s a snowman melting. This was April 3 and was the last snow that could have been made into a snowman. A couple weeks into April and it was safe to take my snow tires off my bicycle and car.

Here I am standing on the bridge to Tonawanda Island in the Niagara River. This is around the beginning of April. You can see big steel cylinders floating on the right. That is an ice boom and it is to protect the marina there from ice. There is a very large ice boom at the beginning of the Niagara River to keep Lake Erie ice out. It was up later than usual this year. I keep an eye on this because I don’t go boating on the river if it’s packed with ice (I go boating elsewhere).

Here’s my office. That beautiful tree reminded me of the ornamental tree in the apartment I lived in in San Diego. The reason is that it stinks! You’d expect such lovely flowers to not smell like uncleaned hamster cage, but nature is funny that way. Once the floweres dropped, it smelled fine again. To see the transformation, here’s what the office looked like in the winter.

The flowering trees were pretty spectacular all over. This is in my front yard.

After seeing Canadian geese everywhere all year long it was very fun to see how they get their start. The little goslings are everywhere and they are absurdly cute. Here they are getting swimming lessons.

Geese aren’t the only things repopulating. This is in my backyard. Here’s what this scene looked like in the winter.

Here’s the bike path behind my house. This photo is specifically composed to show the drainage problems but mostly the trail is in good shape and it’s extremely nice walking on the trails through the woods. Compare with the winter version.

Here’s another visitor to the backyard. We also put up a birdhouse that quickly became occupied.

Not just cute goslings but adorable ducklings too.

I don’t know if this is a frog or a toad, but he lives in our back yard.

A family of Canadians. Notice how they have to carry their immigration documents on their right legs at all times. It’s the law.

Sometimes the geese set up a day care where a couple of adults watch a pretty huge group of little fuzz balls while the other parents take a break.

Yes, my wife and I like watching these things, hence many photos.

There are snapping turtles in the ponds. I see them in the Erie Canal sometimes too.

Here are a couple of ducks in the forest behind my house. The leaves are just coming in here.

And if for some strange reason I want to see palm trees and spiky plants that will seriously wound you, I can always come to the botanical gardens. There they cultivate the weird plants that can survive in deserts. To us, those exotic plants looked like normal desert stuff that’s all over San Diego County. I’d rather have those dangerous plants in a plant zoo with safe ones in the wild than the other way around.

After catching the end of summer last year and experiencing autumn, winter, and spring, we’re now back to summer. It’s too hot, but at least there’s usually a breeze and plenty of interesting things to do. And most importantly, in a couple of months, we’ll be getting our cool weather clothes back out.