Author Archives: Robin Hanson

Merkle’s Futarchy

My futarchy paper, Shall We Vote on Values But Bet on Beliefs?, made public in 2000 but officially “published” in 2013, has gotten more attention lately as some folks talk about using it to govern blockchain organizations. In particular, Ralph Merkle (co-inventor of public key cryptography) has a recent paper on using futarchy within “Decentralized Autonomous Organizations.”

I tried to design my proposal carefully to avoid many potential problems. But Merkle seems to have thrown many of my cautions to the wind. So let me explain my concerns with his variations.

First, I had conservatively left existing institutions intact for Vote on Values; we’d elect representatives to oversee the definition and measurement of a value metric. Merkle instead has each citizen each year report a number in [0,1] saying how well their life has gone that year:

Annually, all citizens are asked to rank the year just passed between 0 and 1 (inclusive). .. it is intended to provide information about one person’s state of satisfaction with the year that has just passed. .. Summed over all citizens and divided by the number of citizens, this gives us an annual numerical metric between 0 and 1 inclusive. .. An appropriately weighted sum of annual collective welfares, also extending indefinitely into the future, would then give us a “democratic collective welfare” metric. .. adopting a discount rate seems like at least a plausible heuristic. .. To treat their death: .. ask the person who died .. ask before they die. .. [this] eliminates the need to evaluate issues and candidates. The individual citizen is called upon only to determine whether the year has been good or bad for themselves. .. We’ve solved .. the need to wade through deceptive misinformation.

Yes, it could be easy to decide how your last year has gone, even if it is harder to put that on a scale from worst to best possible. But reporting that number is not your best move here! Your optimal strategy here is almost surely “bang-bang”, i.e., reporting either 0 or 1. And you’ll probably want to usually give the same consistent answer year after year. So this is basically a vote, except on “was this last year a good or a bad year?”, which in practice becomes a vote on “has my life been good or bad over the last decades.” Each voter must pick a threshold where they switch their vote from good to bad, a big binary choice that seems ripe for strong emotional distortions. That might work, but it is pretty far from what voters have done before, so a lot of voter learning is needed.

I’m much more comfortable with futarchy that uses value metrics tied to the reason an organization exists. Such as using the market price of investment to manage an investment, attendance to manage a conference, or people helped (& how much) to manage a charity.

If there are too many bills on the table at anyone one time for speculators to consider, many bad ones can slip through and have effects before bills to reverse them can be proposed and adopted. So I suggested starting with a high bar for bills, but allowing new bills to lower the bar. Merkle instead starts with a very low bar that could be raised, and I worry about all the crazy bills that might pass before the bar rises:

Initially, anyone can propose a bill. It can be submitted at any time. .. At any time, anyone can propose a new method of adopting a bill. It is evaluated and put into effect using the existing methods. .. Suppose we decided that it would improve the stability of the system if all bills had a mandatory minimum consideration period of three months before they could be adopted. Then we would pass a bill modifying the DAO to include this provision.

I worried that the basic betting process could bias the basic rules, so I set basic voting and process rules off limits from bet changes, and set an independent judiciary to judge if rules are followed. Merkle instead allows this basic bet process to change all the rules, and all the judges, which seems to me to risk self-supporting rule changes:

How the survey is conducted, and what instructions are provided, and the surrounding publicity and environment, will all have a great impact on the answer. .. The integrity of the annual polls would be protected only if, as a consequence, it threatened the lives or the well-being of the citizens. .. The simplest approach would be to appoint, as President, that person the prediction market said had the highest positive impact on the collective welfare if appointed as President. .. Similar methods could be adopted to appoint the members of the Supreme Court.

Finally, I said explicitly that when the value formula changes then all the previous definitions must continue to be calculated to pay off past bets. It isn’t clear to me that Merkle adopts this, or if he allows the bet process to change value definitions, which also seems to me to risk self-supporting changes:

We leave the policy with respect to new members, and to births, to our prediction market. .. difficult to see how we could justify refusing to adopt a policy that accepts some person, or a new born child, as a member, if the prediction market says the collective welfare of existing members will be improved by adopting such a policy. .. Of greater concern are changes to the Democratic Collective Welfare metric. Yet even here, if the conclusion reached by the prediction market is that some modification of the metric will better maximize the original metric, then it is difficult to make a case that such a change should be banned.

I’m happy to see the new interest in futarchy, but I’m also worried that sloppy design may cause failures that are blamed on the overall concept instead of on implementation details. As recently happened to the DAO concept.

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Me Soon In Bay Area, DC, NYC

Folks near New York City, Washington DC, or the California Bay Area, consider seeing an upcoming Age of Em talk. (I’ll add more specific links as I get them.)

CA Bay Area

July 9, 10a-7p, Oakland, BIL Oakland
Aug 1, 1p, Mountain View, Benghazi Tech Talk, Google
Aug 2, 5p, Mountain View, RethinkDB
Aug 3, 7p, Oakland, Oakland Futurists
Aug 5-7, Berkeley, Effective Altruism Global
Aug 8, 7p, Palo Alto, Stanford Effective Altruism

Washington DC

July 23, 8a, World Future Society
July 26, 6p, Prosperity Caucus

New York City

July 12, 4:35p, Brooklyn, TTI/Vanguard
July 13, 7p, Brooklyn, Loft67

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See A Wider View

Ross Douthat in the NYT:

From now on the great political battles will be fought between nationalists and internationalists, nativists and globalists. .. Well, maybe. But describing the division this way .. gives the elite side of the debate .. too much credit for being truly cosmopolitan.

Genuine cosmopolitanism is a rare thing. It requires comfort with real difference, with forms of life that are truly exotic relative to one’s own. .. The people who consider themselves “cosmopolitan” in today’s West, by contrast, are part of a meritocratic order that transforms difference into similarity, by plucking the best and brightest from everywhere and homogenizing them into the peculiar species that we call “global citizens.”

This species is racially diverse (within limits) and eager to assimilate the fun-seeming bits of foreign cultures — food, a touch of exotic spirituality. But no less than Brexit-voting Cornish villagers, our global citizens think and act as members of a tribe. They have their own distinctive worldview .. common educational experience, .. shared values and assumptions .. outgroups (evangelicals, Little Englanders) to fear, pity and despise. .. From London to Paris to New York, each Western “global city” .. is increasingly interchangeable, so that wherever the citizen of the world travels he already feels at home. ..

It is still possible to disappear into someone else’s culture, to leave the global-citizen bubble behind. But in my experience the people who do are exceptional or eccentric or natural outsiders to begin with .. It’s a problem that our tribe of self-styled cosmopolitans doesn’t see itself clearly as a tribe. .. They can’t see that paeans to multicultural openness can sound like self-serving cant coming from open-borders Londoners who love Afghan restaurants but would never live near an immigrant housing project.

You have values, and your culture has values. They are similar, and this isn’t a coincidence. Causation here mostly goes from culture to individual. And even if you did pick your culture, you have to admit that the young you who did was’t especially wise or well-informed. And you were unaware of many options. So you have to wonder if you’ve too easily accepted your culture’s values.

Of course your culture anticipates these doubts, and is ready with detailed stories on why your culture has the best values. Actually most stories you hear have that as a subtext. But you should wonder how well you can trust all this material.

Now, you might realize that for personal success and comfort, you have little to gain, and much to lose, by questioning your culture’s values. Your associates mostly share your culture, and are comforted more by your loyalty displays than your intellectual cleverness. Hey, everyone agrees cultures aren’t equal; someone has to be best. So why not give yours the benefit of the doubt? Isn’t that reasonable?

But if showing cleverness is really important to you, or if perhaps you really actually care about getting values right, then you should wonder what else you can do to check your culture’s value stories. And the obvious option is to immerse yourself in the lives and viewpoints of other cultures. Not just via the stories or trips your culture has set up to tell you of its superiority. But in ways that give those other cultures, and their members, a real chance. Not just slight variations on your culture, but big variations as well. Try to see a wider landscape of views, and then try to see the universe from many widely dispersed points on that landscape.

Yes if you are a big-city elite, try to see the world from Brexit or Trump fan views. But there are actually much bigger view differences out there. Try a islamic fundamentalist, or a Chinese nationalist. But even if you grow to be able to see the world as do most people in the world today, there still remain even bigger differences out there. Your distant ancestors were quite human, and yet they saw the universe very differently. Yes, they were wrong on some facts, but that hardly invalidates most of their views. Learn some ancient history, to see their views.

And if you already know some ancient history, perhaps the most alien culture you have yet to encounter is that of your human-like descendants. But we can’t possibly know anything about that yet, you say? I beg to differ. I introduce my new book with this meet-a-strange-culture rationale: Continue reading "See A Wider View" »

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The Future of Slavery

Bryan Caplan made strong, and to me incredible, claims that econ consensus predicts all ems would be fully slaves with no human personality. As he won’t explain his reasoning, but just says to read the slavery literature, I’ve done a quick lit review, which I now summarize, and then apply quickly to the future in general, and to ems in particular.

The ability to control your pain, actions, and income are distinct property rights. When someone else owns them all, you are said to be a slave, especially if they allocate these rights via something close to a “full control” package. In this package, you have little control over assets or actions. Pain is usually threatened, and often implemented, to force specific disliked but demanded actions. (Pain was used more on children than adults.) Think of rowing for a galley ship, digging up silver in a mine, picking cotton, or advancing on a simple war front line.

A second “mixed control” package allocates these rights by letting you retain control over many action details, only rarely causing pain, and letting you earn a residual income or status. This scenario was more common for domestic slaves, for slaves with better options for sabotage or escape, and for complex jobs where motivation matters more, via worker discretion, responsibility, attentiveness, pleasantness, intelligence, or creativity. By collecting a residual income, slaves might eventually buy their freedom. Free people have often sold this package of rights for short durations in traditional jobs. The main difference is your ease of changing jobs; the harder it is to change jobs, the more like this kind of slave you are.

In a third “debt” package, you must pay off a loan but are otherwise mostly free to choose your own job, location, and living arrangements. The option to impose pain is reserved for rare situations. Closely related is “share cropping” wherein the owner demands a percentage of income earned. Some combination of a fixed payment plus a percentage of income was a common scenario for slaves in southern US cities. This is also the usual way state rulers extort the locals they “own” via taxation. Many people voluntarily choose to go into debt, and sell percentages of their business income, and most legal systems reserve the right to impose pain in rare situations, a situation most people are okay with.

A fourth “ransom” approach sells these rights back to some combination of you and your associates. Often this converts these rights into debt held by someone who is better able to motivate and monitor you.

Many considerations influence the efficiency of these allocations, including costs of monitoring and restraint, losses from theft, rebellion, escape, and sabotage, individual preferences for pain, status, autonomy, and work style, effects of pain, status, and control on motivation and focus, information rents from workers being better aware of work details, complementary investments in training and capital, who knows better and has better incentives to use control rights, and signaling status, productivity, etc. to outsiders.

Historically, even when slaves were common, they were usually a minority of the population. (Beware, the term “slave” is used in different ways.) About 10% in the Roman Empire and US south. Foragers didn’t do slaves at all. About 0.3% of the world is in slavery today, mostly in forms of debt bondage.

The common existence of slavery that wasn’t converted immediately into debt or ransom does suggest that it was sometimes locally efficient as a resource allocation, ignoring larger social externalities, even given substantial costs of monitoring, enforcement, and worse motivation and allocation of skills.

Sometimes during hard times people would sell themselves or their children into slavery; better to be fed than dead. Sometimes slaves were created as collateral for loans, and freed when the loan was paid. Sometimes slavery was the contractual result of a failure to pay loans. Sometimes people sold themselves into slavery for a limited time, as with apprenticeships and indentured servitude.

But historically, slaves were mostly created in war. Drafted soldiers are slave-like. When a winning side didn’t expect to hold the territory, and feared leaving the vanquished to recover then retaliate, their remaining options were death or slavery. But slaves were only valuable when delivered to a useable location. So the worse treatment of slaves has been in transit immediately after capture.

Slave populations usually dwindled until replenished by war, probably because through most of history interest rates were too high to justify the long term investment of raising human children. Domesticated crops and animals grow much quicker. This same short term focus also often induced slave owners to work their slaves to death. A short term focus was often increased by distant ownership, as local manager’ incentives were tied more to immediate production. Workings slaves to death induced more slave revolts.

The US south was unusual in that it grew long-lived slaves from birth. Interest rates were unusually low, peace lasted long, and once US law forbad importing slaves, owners were highly motivated to preserve their big plantation industry. Slaves weren’t converted into debt perhaps because of credit market failures, or more plausibly because the full control approach was especially productive on plantations. (The sex story is overrated, as only 1-2% of slave babies were fathered by white men.)

That is, on plantations slaves plausibly produced more when threatened with pain, even if their utility was lower. The fact that humans can feel strongly disliked pain while living a long productive life and successfully reproducing does suggest that our pain signals are biologically maladaptive. But given how different is the modern world from the one where our pain signals evolved, we should expect this sort of thing sometimes.

Data on US south slave prices tells us what was valued in slaves then. For adults, age was bad, as were slaves from distant places within the US, and slaves that the owner chose to sell, as opposed to being forced to sell. New slaves imported from overseas were no more or less valued. It was good to be male, light-skinned, have artisan skills, and be guaranteed not to be sick or run away.

I didn’t find any data on slaves and docility, though I did find how docility fits into the standard five factor personality framework. Docility is lumped with “submissive, dependent, pliant” as part of “passivity”, which correlates most strongly and positively with neuroticism, but also positively with agreeableness and negatively with openness. In general only the agreeable part suggests more productivity in most jobs today; neurotic people are less productive, and the effect of openness depends more on job type.

What is there to dislike about slavery? The war and theft that cause slavery are clearly lamentable. And the possibility of slavery increases the range of possible inequality, at least if you ignore the dead. But the full control allocation package seems the main reason to dislike slavery. Other packages seem much closer to those resulting from free choices, and when they result from free choices they don’t seem strongly objectionable.

Today slavery, especially full control slavery, is discouraged not only via moral censure and political coordination, but also by stronger nation-states, few wars, better credit markets, increasing wealth, increasing vulnerability to sabotage, more automation, and more complex jobs. The only contrary factors I can think of are easier monitoring and preventing escape. If all these trends continue in the same relative proportions, we should expect a continued decline in slavery.

In the world of my book, The Age of Em, many of these trends continue. Nation-states and credit markets get stronger, and war remains rare. Automation advances, and jobs get even more complex, with motivation and sabotage mattering even more. Monitoring and preventing escape also get easier.

Individual em incomes do fall, which gives a thicker lower tail of outcomes, and in traditional societies that allowed slavery this low tail was often filled with slaves. However, ems can fall via running slower while remaining free, and this option would reduce the fraction that fall into slavery, even if slavery were allowed.

Ems are initially created via destructive scanning of high income human volunteers at the peak of their careers, in a world that forbids slavery. Soon after they are destructive scans of the most promising young children. So these volunteers do not expect to become slaves, and the world around them, being like ours, initially tries to discourage that transition.

However, since a lot changes we can’t offer much assurance that attitudes toward slavery don’t change. Also, labor supply factors matter a lot less; if even one productive em is enslaved, and slavery is allowed, then copies of it could fill a whole slave sector. What matters far more is demand, i.e., what are the more efficient ways to allocate labor? If allowed, there are probably some jobs where full control slavery is more efficient; the em world is big, with many corners. But most jobs are complex, where the full control scenario is inefficient. And the debt or mixed control allocations that are more efficient for typical jobs are probably not substantially more efficient under slavery, as slavery hurts motivation. Debt should be good enough.

So, bottom line, after a quick review of the econ of slavery literature, I still can’t find a rationale for Bryan Caplan’s claim that all ems would be fully slaves. Ancient society never got close to that state of affairs. And I see even less rationale for his claim that they would be so docile and “robot-like” as to not even have human-like personalities. Which is his main reason for saying 80% of my book is wrong. Neither the literatures on choosing employees today, nor that on choosing slaves in the past, put much emphasis on docility. And even if they did, the idea that they’d emphasize it so much as to eliminate human personality, that just sounds crazy.

So Bryan, how about actually giving an argument, instead of waving your hands in the general direction of the literature?

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Open Thread

This is a place to discuss relevant topics that have not appeared in recent posts. (Used to do this monthly; let’s see if worth reviving.)

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Once More, With Feeling

Sean Carroll’s new best-selling book The Big Picture runs the risk of preaching to the choir. To my mind, it gives a clear and effective explanation of the usual top physicists’ world view. On religion, mysticism, free will, consciousness, meaning, morality, etc. (The usual view, but an unusually readable, articulate, and careful explanation.) I don’t disagree, but then I’m very centered in this physicist view.

I read through dozens of reviews, and none of them even tried to argue against his core views! Yet I have many economist colleagues who often give me grief for presuming this usual view. And I’m pretty sure the publication of this book (or of previous similar books) won’t change their minds. Which is a sad commentary on our intellectual conversation; we mostly see different points of view marketed separately, with little conversation between proponents.

Carroll inspires me to try to make one point I think worth making, even if it is also ignored. My target is people who think philosophical zombies make sense. Zombies are supposedly just like real people in having the same physical brains, which arose the through the same causal history. The only difference is that while real people really “feel”, zombies do not. But since this state of “feeling” is presumed to have zero causal influence on behavior, zombies act exactly like real people, including being passionate and articulate about claiming they are not zombies. People who think they can conceive of such zombies see a “hard question” regarding which physical systems that claim to feel and otherwise act as if they feel actually do feel. (And which other systems feel as well.)

The one point I want to make is: if zombies are conceivable, then none of us will ever have any more relevant info than we do now about which systems actually feel. Which is pretty much zero info! You will never have any info about whether you ever really felt in the past, or will ever feel in the future. No one part of your brain ever gets any info from any other part of your brain about whether it really feels.

These claims all follow from our very standard and well-established info theory. We get info about things by interacting with them, so that our states become correlated with the states of those things. But by assumption this hypothesized extra “feeling” state never interacts with anything. The actual reason why you feel compelled to assert very confidently that you really do feel has no causal connection with whether you actually do really feel. You would have been just as likely to say it if it were not true. What could possibly be the point of hypothesizing and forming beliefs about states about which one can never get any info?

If you have learned anything about overcoming bias, you should be very suspicious of such beliefs, and eager for points of view where you don’t have to rely on possibly-false and info-free beliefs. Carroll presents such a point of view:

There’s nothing more disheartening than someone telling you that the problem you think is most important and central isn’t really a problem at all. As poetic naturalists, that’s basically what we’ll be doing. .. Philosophical zombies are simply inconceivable, because “consciousness” is a particular way of talking about the behavior of certain physical systems. The phrase “experiencing the redness of red” is part of a higher-level vocabulary we use to talk about the emergent behavior of the underlying physical system, not something separate from the physical system.

There’s not much to it, but that’s as it should be. I agree with Carroll; there literally isn’t anything to talk about here.

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Against Prestige

My life has been, in part, a series of crusades. First I just wanted to understand as much as possible. Then I focused on big problems, wondering how to fix them. Digging deeper I was persuaded by economists: our key problems are institutional. Yes we can have lamentable preferences and cultures. But it is hard to find places to stand and levers to push to move these much, or even to understand the effects of changes. Institutions, in contrast, have specific details we can change, and economics can say which changes would help.

I learned that the world shows little interest in the institutional changes economists recommend, apparently because they just don’t believe us. So I focused on an uber institutional problem: what institutions can we use to decide together what to believe? A general solution to this problem might get us to believe economists, which could get us to adopt all the other economics solutions. Or to believe whomever happens to be right, when economists are wrong. I sought one ring to rule them all.

Of course it wasn’t obvious that a general solution exists, but amazingly I did find a pretty general one: prediction markets. And it was also pretty simple. But, alas, mostly illegal. So I pursued it. Trying to explain it, looking for everyone who had said something similar. Thinking and hearing of problems, and developing fixes. Testing it in the lab, and in the field. Spreading the word. I’ve been doing this for 28 years now. (Began at age 29.)

And I will keep at it. But I gotta admit it seems even harder to interest people in this one uber solution than in more specific solutions. Which leads me to think that most who favor specific solutions probably do so for reasons other than the ones economists give; they are happy to point to economist reasons when it supports them, and ignore economists otherwise. So in addition to pursuing this uber fix, I’ve been studying human behavior, trying to understand why we seem so disinterested.

Many economist solutions share a common feature: a focus on outcomes. This feature is shared by experiments, incentive contracts, track records, and prediction markets, and people show a surprising disinterest in all of them. And now I finally think I see a common cause: an ancient human habit of strong deference to the prestigious. As I recently explained, we want to affiliate with the prestigious, and feel that an overly skeptical attitude toward them taints this affiliation. So we tend to let the prestigious in each area X decide how to run area X, which they tend to arrange more to help them signal than to be useful. This happens in school, law, medicine, finance, research, and more.

So now I enter a new crusade: I am against prestige. I don’t yet know how, but I will seek ways to help people doubt and distrust the prestigious, so they can be more open to focusing on outcomes. Not to doubt that the prestigious are more impressive, but that letting them run the show produces good outcomes. I will be happy if other competent folks join me, though I’m not especially optimistic. Yet. Yet.

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Caplan Audits Age of Em

When I showed Bryan Caplan an early draft of my book, his main concern was that I didn’t focus enough on humans, as he doesn’t think robots can be conscious. In his first critical post, he focused mainly on language and emphasis issues. But he summarized “the reasoning simply isn’t very rigorous”, and he gave 3 substantive objections:

The idea that the global economy will start doubling on a monthly basis is .. a claim with a near-zero prior probability. ..

Why wouldn’t ems’ creators use the threat of `physical hunger, exhaustion, pain, sickness, grime, hard labor, or sudden unexpected death’ to motivate the ems? .. `torturing’ ems, .. why not?” ..

Why wouldn’t ems largely be copies of the most “robot-like” humans – humble workaholics with minimal personal life, content to selflessly and uncomplainingly serve their employers?

He asked me direct questions on my moral evaluation of ems, so I asked him to estimate my overall book accuracy relative to the standard of academic consensus theories, given my assumptions. Caplan said:

The entire analysis hinges on which people get emulated, and there is absolutely no simple standard academic theory of that. If, as I’ve argued, we would copy the most robot-like people and treat them as slaves, at least 90% of Robin’s details are wrong.

Since I didn’t think how docile are ems matters that much for most of my book, I challenged him to check five random pages. Today, he reports back:

Limiting myself to his chapters on Economics, Organization, and Sociology, [half of the book’s six sections] .. After performing this exercise, I’m more inclined to say Robin’s only 80% wrong. .. My main complaint is that his premises about em motivation are implausible and crucial.

Caplan picked 23 quotes from those pages. (I don’t know how picked; I count ~35 claims.) In one of these (#22) he disputes the proper use of the word “participate”, and in one (#12) he says he can’t judge.

In two more, he seems to just misread the quotes. In #21, I say taxes can’t discourage work by retired humans, and he says but ems work. In #8 I say if most ems are in the few biggest cities, they must also be in the few biggest nations (by population). He says there isn’t time for nations to merge.

If I set aside all these, that leaves 19 evaluations, out of which I count 7 (#1,4,9,13,17,19,20) where he says agree or okay, making me only 63% wrong in his eyes. Now lets go through the 12 disagreements, which fall into five clumps.

In #6, Caplan disagrees with my claim that “well-designed computers can be secure from theft, assault, and disease.” On page 62, I had explained:

Ems may use technologies such as provably secure operating system kernels (Klein et al. 2014), and capability-based secure computing systems, which limit the powers of subsystems (Miller et al. 2003).

In #5, I had cited sources showing that in the past most innovation has come from many small innovations, instead of a few big ones. So I said we should expect that for ems too. Caplan says that should reverse because ems are more homogenous than humans. I have no idea what he is thinking here.

In #3,7, he disagrees with my applying very standard urban econ to ems:

It’s not clear what even counts as urban concentration in the relevant sense. .. Telecommuting hasn’t done much .. why think ems will lead to “much larger” em cities? .. Doesn’t being a virtual being vitiate most of the social reasons to live near others? ..

But em virtual reality makes “telecommuting” a nearly perfect substitute for in-person meetings, at least at close distances. And one page before, I had explained that “fast ems .. can suffer noticeable communication delays with city scale separations.” In addition, many ems (perhaps 20%) do physical tasks, and all are housed in hardware needing physical support.

In #2,23, Caplan disagrees with my estimating that the human fraction of income controlled slowly falls, because he says all ems must always remain absolute slaves; “humans hold 100% of wealth regardless .. ems own nothing.”

Finally, half of his disagreements (#10,11,14,15,16,18) stem from his seeing ems them as quite literally “robot-like”. If not for this, he’d score me as only 31% wrong. According to Caplan, ems are not disturbed by “life events”, only by disappointing their masters. They only group, identify, and organize as commanded, not as they prefer or choose. They have no personality “in a human sense.” They never disagree with each other, and never need to make excuses for anything.

Remember, Caplan and I agree that the key driving factor here is that a competitive em world seeks the most productive (per subjective minute) combinations of humans to scan, mental tweaks and training methods to apply, and work habits and organization to use. So our best data should be the most productive people in the world today, or that we’ve seen in history. Yet the most productive people I know are not remotely “robot-like”, at least in the sense he describes above. Can Caplan name any specific workers, or groups, he knows that fit the bill?

In writing the book I searched for literatures on work productivity, and used many dozens of articles on specific productivity correlates. But I never came across anything remotely claiming “robot-like” workers (or tortured slaves) to be the most productive in modern jobs. Remember that the scoring standard I set was not personal intuition but the consensus of the academic literature. I’ve cited many sources, but Caplan has yet to cite any.

From Caplan, I humbly request some supporting citations. But I think he and I will make only limited progress in this discussion until some other professional economists weigh in. What incantations will summon the better spirits of the Econ blogosphere?

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Why Does Software Rot?

Almost a year ago computer scientist Daniel Lemire wrote a post critical of a hypothesis I’ve favored, one I’ve used in Age of Em. On the “better late than never” principle, I’ll finally respond now. The hypothesis:

Systems that adapt to contexts tend to get more fragile and harder to readapt to new contexts.

In a 2012 post I said we see this tendency in human brains, in animal brains, in software, in product design, in species, and in individual cells. There is a related academic literature on design feature entrenchment (e.g., here, here, here, here).

Lemire’s 2015 response:

I am arguing back that the open source framework running the Internet, and serving as a foundation for companies like Google and Apple, is a counterexample. Apache, the most important web server software today, is an old piece of technology whose name is a play on words (“a patched server”) indicating that it has been massively patched. The Linux kernel itself runs much of the Internet, and has served as the basis for the Android kernel. It has been heavily updated… Linus Torvalds wrote the original Linux kernel as a tool to run Unix on 386 PCs… Modern-day Linux is thousands of times more flexible.

So we have evolved from writing everything from scratch (in the seventies) to massively reusing and updated pre-existing software. And yet, the software industry is the most flexible, fast-growing industry on the planet. .. If every start-up had to build its own database engine, its own web server… it would still cost millions of dollars to do anything. And that is exactly what would happen if old software grew inflexible: to apply Apache or MySQL to the need of your start-up, you would need to rewrite them first… a costly endeavour. ..

Oracle was not built from the ground up to run on thousands of servers in a cloud environment. So some companies are replacing Oracle with more recent alternatives. But they are not doing so because Oracle has gotten worse, or that Oracle engineers cannot keep up. When I program in Java, I use an API that dates back to 1998 if not earlier. It has been repeatedly updated and it has become more flexible as a result…

Newer programming languages are often interesting, but they are typically less flexible at first than older languages. Everything else being equal, older languages perform better and are faster. They improve over time. .. Just like writers of non-fiction still manage to write large volumes without ending with an incoherent mass, software programmers have learned to cope with very large and very complex endeavours. ..

Programmers, especially young programmers, often prefer to start from scratch. .. In part because it is much more fun to write code than to read code, while both are equally hard. That taste for fresh code is not an indication that starting from scratch is a good habit. Quite the opposite! ..
“Technical debt” .. is a scenario whereas the programmers have quickly adapted to new circumstances, but without solid testing, documentation and design. The software is known to be flawed and difficult, but it is not updated because it “works”. Brains do experience this same effect.

I have long relied on a distinction between architecture and content (see here, here, here, here, here). Content is the part of a system that it is easy to add to or change without changing the rest of the system; architecture is the other part. (Yes, there is a spectrum.) The more content that is fitted to an architecture, and the bigger is that architecture, the harder it becomes to change the architecture.

Lemire’s examples seem to be of systems which grow long and large because they don’t change their core architecture. When an architecture is well enough matched to a stable problem, systems build on it can last long, and grow large, because it is too much trouble to start a competing system from scratch. But when different approaches or environments need different architectures, then after a system grows large enough, one is mostly forced to start over from scratch to use a different enough approach, or to function in a different enough environment.

This is probably why “Some companies are replacing Oracle with more recent alternatives.” Oracle’s architecture isn’t well enough matched. I just can’t buy Lemire’s suggestion that the only reason people ever start new software systems from scratch today is the arrogance and self-indulgence of youth. It happens way far too often to explain that way.

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Beware Prestige-Based Discretion

Before the modern world, most jobs had a big physical component. And so physical ability (strength, speed, stamina, coordination, etc.) was one of the main things people tried to show off. Yes, people did try to show off physical abilities on the job. But when people got serious about showing off, they created special off-the-job contests, such as races and games.

These special contests made it much easier for observers to see small ability differences. For example, you might watch messengers all day on the job running from place to place, and though you’d get a vague idea of which ones were faster, you couldn’t see fine differences very well. But a race controls for other variation by having contestants all start at the same time on a line, and all run straight to a finish line. So even if one runner beats another by only a fraction of a second, observers can still see the difference. Other kinds of special contests also reduce noise, making it easier to see smaller ability differences.

When people can choose between competition forums with more and less noise, signaling incentives will induce them to choose forums with less noise. After all, competitors who choose forums with more noise will be seen as trying to hide their lower abilities among the noise.

So if messengers who wanted to show off their running abilities had a lot of discretion about how messenger jobs were arranged, they’d try to make their jobs look a lot like races. Which would help them show off, but would be less effective at getting messages delivered. Which is why people who hire messengers need to pay attention to how fast messages get delivered, and not just to hiring the fastest runners. Just hiring the fastest runners and letting them decide how messages get delivered is a recipe for waste.

In the rest of society, however, we often both try to hire people who seem to show off the highest related abilities, and we let those most prestigious people have a lot of discretion in how the job is structured. For example, we let the most prestigious doctors tell us how medicine should be run, the most prestigious lawyers tells us how law should be run, the most prestigious finance professionals tell us how the financial system should work, and the most prestigious academics tell us how to run schools and research.

This can go very wrong! Imagine that we wanted research progress, and that we let the most prestigious researchers pick research topics and methods. To show off their abilities, they may pick topics and methods that most reduce the noise in estimating abilities. For example, they may pick mathematical methods, and topics that are well suited to such methods. And many of them may crowd around the same few topics, like runners at a race. These choices would succeed in helping the most able researchers to show that they are in fact the most able. But the actual research that results might not be very useful at producing research progress.

Of course if we don’t really care about research progress, or students learning, or medical effectiveness, etc., if what we mainly care about is just affiliating with the most impressive folks, well then all this isn’t much of a problem. But if we do care about these things, then unthinkingly presuming that the most prestigious people are the best to tell us how to do things, that can go very very wrong.

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