# Good enough is perfect, perfect is bad

Jan 8 JDN 2459953

Not too long ago, I read the book How to Keep House While Drowning by KC Davis, which I highly recommend. It offers a great deal of useful and practical advice, especially for someone neurodivergent and depressed living through an interminable pandemic (which I am, but honestly, odds are, you may be too). And to say it is a quick and easy read is actually an unfair understatement; it is explicitly designed to be readable in short bursts by people with ADHD, and it has a level of accessibility that most other books don’t even aspire to and I honestly hadn’t realized was possible. (The extreme contrast between this and academic papers is particularly apparent to me.)

At first, it sounded like nonsense; no, perfect is perfect, good enough is just good enough. But in fact there is a deep sense in which it is absolutely true.

Indeed, let me make it a bit stronger: Good enough is perfect; perfect is bad.

I doubt Davis thought of it in these terms, but this is a concise, elegant statement of the principles of bounded rationality. Sometimes it can be optimal not to optimize.

Suppose that you are trying to optimize something, but you have limited computational resources in which to do so. This is actually not a lot for you to suppose—it’s literally true of basically everyone basically every moment of every day.

But let’s make it a bit more concrete, and say that you need to find the solution to the following math problem: “What is the product of 2419 times 1137?” (Pretend you don’t have a calculator, as it would trivialize the exercise. I thought about using a problem you couldn’t do with a standard calculator, but I realized that would also make it much weirder and more obscure for my readers.)

Now, suppose that there are some quick, simple ways to get reasonably close to the correct answer, and some slow, difficult ways to actually get the answer precisely.

In this particular problem, the former is to approximate: What’s 2500 times 1000? 2,500,000. So it’s probably about 2,500,000.

Or we could approximate a bit more closely: Say 2400 times 1100, that’s about 100 times 100 times 24 times 11, which is 2 times 12 times 11 (times 10,000), which is 2 times (110 plus 22), which is 2 times 132 (times 10,000), which is 2,640,000.

Or, we could actually go through all the steps to do the full multiplication (remember I’m assuming you have no calculator), multiply, carry the 1s, add all four sums, re-check everything and probably fix it because you messed up somewhere; and then eventually you will get: 2,750,403.

So, our really fast method was only off by about 10%. Our moderately-fast method was only off by 4%. And both of them were a lot faster than getting the exact answer by hand.

Which of these methods you’d actually want to use depends on the context and the tools at hand. If you had a calculator, sure, get the exact answer. Even if you didn’t, but you were balancing the budget for a corporation, I’m pretty sure they’d care about that extra \$110,403. (Then again, they might not care about the \$403 or at least the \$3.) But just as an intellectual exercise, you really didn’t need to do anything; the optimal choice may have been to take my word for it. Or, if you were at all curious, you might be better off choosing the quick approximation rather than the precise answer. Since nothing of any real significance hinged on getting that answer, it may be simply a waste of your time to bother finding it.

This is of course a contrived example. But it’s not so far from many choices we make in real life.

Yes, if you are making a big choice—which job to take, what city to move to, whether to get married, which car or house to buy—you should get a precise answer. In fact, I make spreadsheets with formal utility calculations whenever I make a big choice, and I haven’t regretted it yet. (Did I really make a spreadsheet for getting married? You’re damn right I did; there were a lot of big financial decisions to make there—taxes, insurance, the wedding itself! I didn’t decide whom to marry that way, of course; but we always had the option of staying unmarried.)

But most of the choices we make from day to day are small choices: What should I have for lunch today? Should I vacuum the carpet now? What time should I go to bed? In the aggregate they may all add up to important things—but each one of them really won’t matter that much. If you were to construct a formal model to optimize your decision of everything to do each day, you’d spend your whole day doing nothing but constructing formal models. Perfect is bad.

In fact, even for big decisions, you can’t really get a perfect answer. There are just too many unknowns. Sometimes you can spend more effort gathering additional information—but that’s costly too, and sometimes the information you would most want simply isn’t available. (You can look up the weather in a city, visit it, ask people about it—but you can’t really know what it’s like to live there until you do.) Even those spreadsheet models I use to make big decisions contain error bars and robustness checks, and if, even after investing a lot of effort trying to get precise results, I still find two or more choices just can’t be clearly distinguished to within a good margin of error, I go with my gut. And that seems to have been the best choice for me to make. Good enough is perfect.

I think that being gifted as a child trained me to be dangerously perfectionist as an adult. (Many of you may find this familiar.) When it came to solving math problems, or answering quizzes, perfection really was an attainable goal a lot of the time.

As I got older and progressed further in my education, maybe getting every answer right was no longer feasible; but I still could get the best possible grade, and did, in most of my undergraduate classes and all of my graduate classes. To be clear, I’m not trying to brag here; if anything, I’m a little embarrassed. What it mainly shows is that I had learned the wrong priorities. In fact, one of the main reasons why I didn’t get a 4.0 average in undergrad is that I spent a lot more time back then writing novels and nonfiction books, which to this day I still consider my most important accomplishments and grieve that I’ve not (yet?) been able to get them commercially published. I did my best work when I wasn’t trying to be perfect. Good enough is perfect; perfect is bad.

Now here I am on the other side of the academic system, trying to carve out a career, and suddenly, there is no perfection. When my exam is being graded by someone else, there is a way to get the most points. When I’m the one grading the exams, there is no “correct answer” anymore. There is no one scoring me to see if I did the grading the “right way”—and so, no way to be sure I did it right.

Actually, here at Edinburgh, there are other instructors who moderate grades and often require me to revise them, which feels a bit like “getting it wrong”; but it’s really more like we had different ideas of what the grade curve should look like (not to mention US versus UK grading norms). There is no longer an objectively correct answer the way there is for, say, the derivative of x^3, the capital of France, or the definition of comparative advantage. (Or, one question I got wrong on an undergrad exam because I had zoned out of that lecture to write a book on my laptop: Whether cocaine is a dopamine reuptake inhibitor. It is. And the fact that I still remember that because I got it wrong over a decade ago tells you a lot about me.)

And then when it comes to research, it’s even worse: What even constitutes “good” research, let alone “perfect” research? What would be most scientifically rigorous isn’t what journals would be most likely to publish—and without much bigger grants, I can afford neither. I find myself longing for the research paper that will be so spectacular that top journals have to publish it, removing all risk of rejection and failure—in other words, perfect.

Yet such a paper plainly does not exist. Even if I were to do something that would win me a Nobel or a Fields Medal (this is, shall we say, unlikely), it probably wouldn’t be recognized as such immediately—a typical Nobel isn’t awarded until 20 or 30 years after the work that spawned it, and while Fields Medals are faster, they’re by no means instant or guaranteed. In fact, a lot of ground-breaking, paradigm-shifting research was originally relegated to minor journals because the top journals considered it too radical to publish.

Or I could try to do something trendy—feed into DSGE or GTFO—and try to get published that way. But I know my heart wouldn’t be in it, and so I’d be miserable the whole time. In fact, because it is neither my passion nor my expertise, I probably wouldn’t even do as good a job as someone who really buys into the core assumptions. I already have trouble speaking frequentist sometimes: Are we allowed to say “almost significant” for p = 0.06? Maximizing the likelihood is still kosher, right? Just so long as I don’t impose a prior? But speaking DSGE fluently and sincerely? I’d have an easier time speaking in Latin.

What I know—on some level at least—I ought to be doing is finding the research that I think is most worthwhile, given the resources I have available, and then getting it published wherever I can. Or, in fact, I should probably constrain a little by what I know about journals: I should do the most worthwhile research that is feasible for me and has a serious chance of getting published in a peer-reviewed journal. It’s sad that those two things aren’t the same, but they clearly aren’t. This constraint binds, and its Lagrange multiplier is measured in humanity’s future.

But one thing is very clear: By trying to find the perfect paper, I have floundered and, for the last year and a half, not written any papers at all. The right choice would surely have been to write something.

Because good enough is perfect, and perfect is bad.

# Scope neglect and the question of optimal altruism

JDN 2457090 EDT 16:15.

We’re now on Eastern Daylight Time because of this bizarre tradition of shifting our time zone forward for half of the year. It’s supposed to save energy, but a natural experiment in India suggests it actually increases energy demand. So why do we do it? Like every ridiculous tradition (have you ever tried to explain Groundhog Day to someone from another country?), we do it because we’ve always done it.
This week’s topic is scope neglect, one of the most pervasive—and pernicious—cognitive heuristics human beings face. Scope neglect raises a great many challenges not only practically but also theoretically—it raises what I call the question of optimal altruism.

The question is simple to ask yet remarkably challenging to answer: How much should we be willing to sacrifice in order to benefit others? If we think of this as a number, your solidarity coefficient (s), it is equal to the cost you are willing to pay divided by the benefit your action has for someone else: s B > C.

This is analogous to the biological concept relatedness (r), on which Hamilton’s Rule applies: r B > C. Solidarity is the psychological analogue; instead of valuing people based on their genetic similarity to you, you value them based on… well, that’s the problem.

I can easily place upper and lower bounds: The lower bound is zero: You should definitely be willing to sacrifice something to help other people—otherwise you are a psychopath. The upper bound is one: There’s no point in paying more cost than you produce in benefit, and in fact even paying the same cost to yourself as you yield in benefits for other people doesn’t make a lot of sense, because it means that your own self-interest is meaningless and the fact that you understand your own needs better than the needs of others is also irrelevant.

But beyond that, it gets a lot harder—and that may explain why we suffer scope neglect in the first place. Should it be 90%? 50%? 10%? 1%? How should it vary between friends versus family versus strangers? It’s really hard to say. And this inability to precisely decide how much other people should be worth to us may be part of why we suffer scope neglect.

Scope neglect is the fact that we are not willing to expend effort or money in direct proportion to the benefit it would have. When different groups were asked how much they would be willing to donate in order to save the lives of 2,000 birds, 20,000 birds, or 200,000 birds, the answers they gave were statistically indistinguishable—always about \$80. But however much a bird’s life is worth to you, shouldn’t 200,000 birds be worth, well, 200,000 times as much? In fact, more than that, because the marginal utility of wealth is decreasing, but I see no reason to think that the marginal utility of birds decreases nearly as fast.

But therein lies the problem: Usually we can’t pay 200,000 times as much. I’d feel like a horrible person if I weren’t willing to expend at least \$10 or an equivalent amount of effort in order to save a bird. To save 200,000 birds that means I’d owe \$2 million—and I simply don’t have \$2 million.

You can get similar results to the bird experiment if you use children—though, as one might hope, the absolute numbers are a bit bigger, usually more like \$500 to \$1000. (And this, it turns out, is actually about how much it actually costs to save a child’s life by a particularly efficient means, such as anti-malaria nets, de-worming, or direct cash transfer. So please, by all means, give \$1000 to UNICEF or the Against Malaria Foundation. If you can’t give \$1000, give \$100; if you can’t give \$100, give \$10.) It doesn’t much matter whether you say that the project will save 500 children, 5,000 children, or 50,000 children—people still will give about \$500 to \$1000. But once again, if I’m willing to spend \$1000 to save a child—and I definitely am—how much should I be willing to spend to end malaria, which kills 500,000 children a year? Apparently \$500 million, which not only do I not have, I almost certainly will not make that much money cumulatively through my entire life. (\$2 million, on the other hand, I almost certainly will make cumulatively—the median income of an economist is \$90,000 per year, so if I work for at least 22 years with that as my average income I’ll have cumulatively made \$2 million. My net wealth may never be that high—though if I get better positions, or I’m lucky enough or clever enough with the stock market it might—but my cumulative income almost certainly will. Indeed, the average gain in cumulative income from a college degree is about \$1 million. Because it takes time—time is money—and loans carry interest, this gives it a net present value of about \$300,000.)

But maybe scope neglect isn’t such a bad thing after all. There is a very serious problem with these sort of moral dilemmas: The question didn’t say I would single-handedly save 200,000 birds—and indeed, that notion seems quite ridiculous. If I knew that I could actually save 200,000 birds and I were the only one who could do it, dammit, I would try to come up with that \$2 million. I might not succeed, but I really would try as hard as I could.

And if I could single-handedly end malaria, I hereby vow that I would do anything it took to achieve that. Short of mass murder, anything I could do couldn’t be a higher cost to the world than malaria itself. I have no idea how I’d come up with \$500 million, but I’d certainly try. Bill Gates could easily come up with that \$500 million—so he did. In fact he endowed the Gates Foundation with \$28 billion, and they’ve spent \$1.3 billion of that on fighting malaria, saving hundreds of thousands of lives.

With this in mind, what is scope neglect really about? I think it’s about coordination. It’s not that people don’t care more about 200,000 birds than they do about 2,000; and it’s certainly not that they don’t care more about 50,000 children than they do about 500. Rather, the problem is that people don’t know how many other people are likely to donate, or how expensive the total project is likely to be; and we don’t know how much we should be willing to pay to save the life of a bird or a child.

Hence, what we basically do is give up; since we can’t actually assess the marginal utility of our donation dollars, we fall back on our automatic emotional response. Our mind focuses itself on visualizing that single bird covered in oil, or that single child suffering from malaria. We then hope that the representative heuristic will guide us in how much to give. Or we follow social norms, and give as much as we think others would expect us to give.

While many in the effective altruism community take this to be a failing, they never actually say what we should do—they never give us a figure for how much money we should be willing to donate to save the life of a child. Instead they retreat to abstraction, saying that whatever it is we’re willing to give to save a child, we should be willing to give 50,000 times as much to save 50,000 children.

But it’s not that simple. A bigger project may attract more supporters; if the two occur in direct proportion, then constant donation is the optimal response. Since it’s probably not actually proportional, you likely should give somewhat more to causes that affect more people; but exactly how much more is an astonishingly difficult question. I really don’t blame people—or myself—for only giving a little bit more to causes with larger impact, because actually getting the right answer is so incredibly hard. This is why it’s so important that we have institutions like GiveWell and Charity Navigator which do the hard work to research the effectiveness of charities and tell us which ones we should give to.

Yet even if we can properly prioritize which charities to give to first, that still leaves the question of how much each of us should give. 1% of our income? 5%? 10%? 20%? 50%? Should we give so much that we throw ourselves into the same poverty we are trying to save others from?

In his earlier work Peter Singer seemed to think we should give so much that it throws us into poverty ourselves; he asked us to literally compare every single purchase and ask ourselves whether a year of lattes or a nicer car is worth a child’s life. Of course even he doesn’t live that way, and in his later books Singer seems to have realized this, and now recommends the far more modest standard that everyone give at least 1% of their income. (He himself gives about 33%, but he’s also very rich so he doesn’t feel it nearly as much.) I think he may have overcompensated; while if literally everyone gave at least 1% that would be more than enough to end world hunger and solve many other problems—world nominal GDP is over \$70 trillion, so 1% of that is \$700 billion a year—we know that this won’t happen. Some will give more, others less; most will give nothing at all. Hence I think those of us who give should give more than our share; hence I lean toward figures more like 5% or 10%.

But then, why not 50% or 90%? It is very difficult for me to argue on principle why we shouldn’t be expected to give that much. Because my income is such a small proportion of the total donations, the marginal utility of each dollar I give is basically constant—and quite high; if it takes about \$1000 to save a child’s life on average, and each of these children will then live about 60 more years at about half the world average happiness, that’s about 30 QALY per \$1000, or about 30 milliQALY per dollar. Even at my current level of income (incidentally about as much as I think the US basic income should be), I’m benefiting myself only about 150 microQALY per dollar—so my money is worth about 200 times as much to those children as it is to me.

So now we have to ask ourselves the really uncomfortable question: How much do I value those children, relative to myself? If I am at all honest, the value is not 1; I’m not prepared to die for someone I’ve never met 10,000 kilometers away in a nation I’ve never even visited, nor am I prepared to give away all my possessions and throw myself into the same starvation I am hoping to save them from. I value my closest friends and family approximately the same as myself, but I have to admit that I value random strangers considerably less.

Do I really value them at less than 1%, as these figures would seem to imply? I feel like a monster saying that, but maybe it really isn’t so terrible—after all, most economists seem to think that the optimal solidarity coefficient is in fact zero. Maybe we need to become more comfortable admitting that random strangers aren’t worth that much to us, simply so that we can coherently acknowledge that they aren’t worth nothing. Very few of us actually give away all our possessions, after all.

Then again, what do we mean by worth? I can say from direct experience that a single migraine causes me vastly more pain than learning about the death of 200,000 people in an earthquake in Southeast Asia. And while I gave about \$100 to the relief efforts involved in that earthquake, I’ve spent considerably more on migraine treatments—thousands, once you include health insurance. But given the chance, would I be willing to suffer a migraine to prevent such an earthquake? Without hesitation. So the amount of pain we feel is not the same as the amount of money we pay, which is not the same as what we would be willing to sacrifice. I think the latter is more indicative of how much people’s lives are really worth to us—but then, what we pay is what has the most direct effect on the world.

It’s actually possible to justify not dying or selling all my possessions even if my solidarity coefficient is much higher—it just leads to some really questionable conclusions. Essentially the argument is this: I am an asset. I have what economists call “human capital”—my health, my intelligence, my education—that gives me the opportunity to affect the world in ways those children cannot. In my ideal imagined future (albeit improbable) in which I actually become President of the World Bank and have the authority to set global development policy, I myself could actually have a marginal impact of megaQALY—millions of person-years of better life. In the far more likely scenario in which I attain some mid-level research or advisory position, I could be one of thousands of people who together have that sort of impact—which still means my own marginal effect is on the order of kiloQALY. And clearly it’s true that if I died, or even if I sold all my possessions, these events would no longer be possible.

The problem with that reasoning is that it’s wildly implausible to say that everyone in the First World are in this same sort of position—Peter Singer can say that, and maybe I can say that, and indeed hundreds of development economists can say that—but at least 99.9% of the First World population are not development economists, nor are they physicists likely to invent cold fusion, nor biomedical engineers likely to cure HIV, nor aid workers who distribute anti-malaria nets and polio vaccines, nor politicians who set national policy, nor diplomats who influence international relations, nor authors whose bestselling books raise worldwide consciousness. Yet I am not comfortable saying that all the world’s teachers, secretaries, airline pilots and truck drivers should give away their possessions either. (Maybe all the world’s bankers and CEOs should—or at least most of them.)

Is it enough that our economy would collapse without teachers, secretaries, airline pilots and truck drivers? But this seems rather like the fact that if everyone in the world visited the same restaurant there wouldn’t be enough room. Surely we could do without any individual teacher, any individual truck driver? If everyone gave the same proportion of their income, 1% would be more than enough to end malaria and world hunger. But we know that everyone won’t give, and the job won’t get done if those of us who do give only 1%.

Perhaps we should figure out what proportion of the world’s people are likely to give, and how much we need altogether, and then assign the amount we expect from each of them based on that? The more money you ask from each, the fewer people are likely to give. This creates an optimization problem akin to setting the price of a product under monopoly—monopolies maximize profits by carefully balancing the quantity sold with the price at which they sell, and perhaps a similar balance would allow us to maximize development aid. But wouldn’t it be better if we could simply increase the number of people who give, so that we don’t have to ask so much of those who are generous? That means tax-funded foreign aid is the way to go, because it ensures coordination. And indeed I do favor increasing foreign aid to about 1% of GDP—in the US it is currently about \$50 billion, 0.3% of GDP, a little more than 1% of the Federal budget. (Most people who say we should “cut” foreign aid don’t realize how small it already is.) But foreign aid is coercive; wouldn’t it be better if people would give voluntarily?

I don’t have a simple answer. I don’t know how much other people’s lives ought to be worth to us, or what it means for our decisions once we assign that value. But I hope I’ve convinced you that this problem is an important one—and made you think a little more about scope neglect and why we have it.

# The World Development Report is on cognitive economics this year!

JDN 2457013 EST 21:01.

On a personal note, I can now proudly report that I have successfully defended my thesis “Corruption, ‘the Inequality Trap’, and ‘the 1% of the 1%’ “, and I now have completed a master’s degree in economics. I’m back home in Michigan for the holidays (hence my use of Eastern Standard Time), and then, well… I’m not entirely sure. I have a gap of about six months before PhD programs start. I have a number of job applications out, but unless I get a really good offer (such as the position at the International Food Policy Research Institute in DC) I think I may just stay in Michigan for awhile and work on my own projects, particularly publishing two of my books (my nonfiction magnum opus, The Mathematics of Tears and Joy, and my first novel, First Contact) and making some progress on a couple of research papers—ideally publishing one of them as well. But the future for me right now is quite uncertain, and that is now my major source of stress. Ironically I’d probably be less stressed if I were working full-time, because I would have a clear direction and sense of purpose. If I could have any job in the world, it would be a hard choice between a professorship at UC Berkeley or a research position at the World Bank.

Which brings me to the topic of today’s post: The people who do my dream job have just released a report showing that they basically agree with me on how it should be done.

If you have some extra time, please take a look at the World Bank World Development Report. They put one out each year, and it provides a rigorous and thorough (236 pages) but quite readable summary of the most important issues in the world economy today. It’s not exactly light summer reading, but nor is it the usual morass of arcane jargon. If you like my blog, you can probably follow most of the World Development Report. If you don’t have time to read the whole thing, you can at least skim through all the sidebars and figures to get a general sense of what it’s all about. Much of the report is written in the form of personal vignettes that make the general principles more vivid; but these are not mere anecdotes, for the report rigorously cites an enormous volume of empirical research.

The title of the 2015 report? “Mind, Society, and Behavior”. In other words, cognitive economics. The world’s foremost international economic institution has just endorsed cognitive economics and rejected neoclassical economics, and their report on the subject provides a brilliant introduction to the subject replete with direct applications to international development.

For someone like me who lives and breathes cognitive economics, the report is pure joy. It’s all there, from anchoring heuristic to social proof, corruption to discrimination. The report is broadly divided into three parts.

Part 1 explains the theory and evidence of cognitive economics, subdivided into “thinking automatically” (heuristics), “thinking socially” (social cognition), and “thinking with mental models” (bounded rationality). (If I wrote it I’d also include sections on the tribal paradigm and narrative, but of course I’ll have to publish that stuff in the actual research literature first.) Anyway the report is so amazing as it is I really can’t complain. It includes some truly brilliant deorbits on neoclassical economics, such as this one from page 47: ” In other words, the canonical model of human behavior is not supported in any society that has been studied.”

Part 2 uses cognitive economic theory to analyze and improve policy. This is the core of the report, with chapters on poverty, childhood, finance, productivity, ethnography, health, and climate change. So many different policies are analyzed I’m not sure I can summarize them with any justice, but a few particularly stuck out: First, the high cognitive demands of poverty can basically explain the whole observed difference in IQ between rich and poor people—so contrary to the right-wing belief that people are poor because they are stupid, in fact people seem stupid because they are poor. Simplifying the procedures for participation in social welfare programs (which is desperately needed, I say with a stack of incomplete Medicaid paperwork on my table—even I find these packets confusing, and I have a master’s degree in economics) not only increases their uptake but also makes people more satisfied with them—and of course a basic income could simplify social welfare programs enormously. “Are you a US citizen? Is it the first of the month? Congratulations, here’s \$670.” Another finding that I found particularly noteworthy is that productivity is in many cases enhanced by unconditional gifts more than it is by incentives that are conditional on behavior—which goes against the very core of neoclassical economic theory. (It also gives us yet another item on the enormous list of benefits of a basic income: Far from reducing work incentives by the income effect, an unconditional basic income, as a shared gift from your society, may well motivate you even more than the same payment as a wage.)

Part 3 is a particularly bold addition: It turns the tables and applies cognitive economics to economists themselves, showing that human irrationality is by no means limited to idiots or even to poor people (as the report discusses in chapter 4, there are certain biases that poor people exhibit more—but there are also some they exhibit less.); all human beings are limited by the same basic constraints, and economists are human beings. We like to think of ourselves as infallibly rational, but we are nothing of the sort. Even after years of studying cognitive economics I still sometimes catch myself making mistakes based on heuristics, particularly when I’m stressed or tired. As a long-term example, I have a number of vague notions of entrepreneurial projects I’d like to do, but none for which I have been able to muster the effort and confidence to actually seek loans or investors. Rationally, I should either commit or abandon them, yet cannot quite bring myself to do either. And then of course I’ve never met anyone who didn’t procrastinate to some extent, and actually those of us who are especially smart often seem especially prone—though we often adopt the strategy of “active procrastination”, in which you end up doing something else useful when procrastinating (my apartment becomes cleanest when I have an important project to work on), or purposefully choose to work under pressure because we are more effective that way.

And the World Bank pulled no punches here, showing experiments on World Bank economists clearly demonstrating confirmation bias, sunk-cost fallacy, and what the report calls “home team advantage”, more commonly called ingroup-outgroup bias—which is basically a form of the much more general principle that I call the tribal paradigm.

If there is one flaw in the report, it’s that it’s quite long and fairly exhausting to read, which means that many people won’t even try and many who do won’t make it all the way through. (The fact that it doesn’t seem to be available in hard copy makes it worse; it’s exhausting to read lengthy texts online.) We only have so much attention and processing power to devote to a task, after all—which is kind of the whole point, really.