Tag Archives: Work

Play Will Persist

We live in the third human era, industry, which followed the farming and foraging eras. Each era introduced innovations that we expect will persist into future eras. Yet some are skeptical. They foresee “post-apocalyptic” scenarios wherein civilization collapses, industrial machines are lost, and we revert to using animals like mules and horses for motive power. Where we lose cities and instead spread across the land. We might even lose organized law, and revert to each small band enforcing its own local law.

On the surface, the future scenario I describe in my book The Age of Em looks nothing like a civilization collapse. It has more better bigger tech, machines, cities, and organizations. Yet many worry that in it we would lose an even more ancient innovation: play. As in laughter, music, teasing, banter, stories, sports, hobbies, etc. Because the em era is a more competitive world where wages return to near subsistence levels, many fear the loss of play and related activities. All of life becomes nose-to-the-grindstone work, where souls grind into dust.

Yet the farming and foraging eras were full of play, even though they were also competitive eras with subsistence wages. Moreover, play is quite common among animals, pretty much all of whom have lived in competitive worlds near subsistence levels:

Play is .. found in a wide range of animals, including marsupials, birds, turtles, lizards, fish, and invertebrates. .. [It] is a diverse phenomenon that evolved independently and was even secondarily reduced or lost in many groups of animals. (more)

Here is where we’ve found play in the evolutionary tree:


We know roughly what kind of animals play:

Animals that play often share common traits, including active life styles, moderate to high metabolic rates, generalist ecological needs requiring behavioral flexibility or plasticity, and adequate to abundant food resources. Object play is most often found in species with carnivorous, omnivorous, or scavenging foraging modes. Locomotor play is prominent in species that navigate in three-dimensional (e.g., trees, water) or complex environments and rely on escape to avoid predation. Social play is not easily summarized, but play fighting, chasing, and wrestling are the major types recorded and occur in almost every major group of animals in which play is found. (more)

Not only are humans generalists with an active lifestyle, we have neoteny, which extends youthful features and behaviors, including play, throughout our lives. So humans have always played, a lot. Given this long robust history of play in humans and animals, why would anyone expect play to suddenly disappear with ems?

Part of the problem is that from the inside play feels like an activity without a “useful” purpose:

Playful activities can be characterized as being (1) incompletely functional in the context expressed; (2) voluntary, pleasurable, or self rewarding; (3) different structurally or temporally from related serious behavior systems; (4) expressed repeatedly during at least some part of an animal’s life span; and (5) initiated in relatively benign situations. (more)

While during serious behavior we are usually aware of some important functions our behaviors serve, in play we enter a “magic circle” wherein we feel safe, focus on pleasure, and act out a wider variety of apparently-safe behaviors. We stop play temporarily when something serious needs doing, and also for longer periods when we are very stressed, such as when depressed or starving. These help give us the impression that play is “extra”, serving no other purpose than “fun.”

But of course such a robust animal behavior must serve important functions. Many specific adaptive functions have been proposed, and while there isn’t strong agreement on their relative importance, we are pretty confident that since play has big costs, it must also give big gains:

Juveniles spend an estimated 2 to 15 percent of their daily calorie budget on play, using up calories the young animal could more profitably use for growing. Frisky playing can also be dangerous, making animals conspicuous and inattentive, more vulnerable to predators and more likely to hurt themselves as they romp and cavort. .. Harcourt witnessed 102 seal pups attacked by southern sea lions; 26 of them were killed. ‘‘Of these observed kills,’’ Harcourt reported in the British journal Animal Behaviour, ‘‘22 of the pups were playing in the shallow tidal pools immediately before the attack and appeared to be oblivious to the other animals fleeing nearby.’’ In other words, nearly 85 percent of the pups that were killed had been playing. (more)

Play can help to explore possibilities, both to learn and practice the usual ways of doing things, and also to discover new ways. In addition, play can be used to signal loyalty, develop trust and coordination, and establish relative status. And via play one can indirectly say things one doesn’t like to say directly. All of these functions should continue to be relevant for ems.

Given all this, I can’t see much doubt that ems would play, at least during the early em era, and play nearly as typical humans in history. Sure it is hard to offer much assurance that play will continue into the indefinite future. But this is mainly because it is hard to offer much assurance of anything in the indefinite future, not because we have good specific reasons to expect play to go away.

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Power Corrupts, Slavery Edition

I’ve just finished reading a 1980 book Advice Among Masters: The Ideal in Slave Management in the Old South, which mostly quotes US slave owners from the mid 1800s writing on how to manage slaves. I really like reading ordinary people describe their to-me-strange worlds in their own words, and hope to do more of it. (Suggestions?)

This book has made me rethink where the main harms from slavery may lie. I said before that slaves were most harmed during and soon after capture, and that high interest rates could induce owners to work slaves to an early death. But neither of these apply in the US South, where the main harm had seemed to me to be from using threats of pain to induce more work on simple jobs.

However, this book gives the impression that most threats of pain were not actually directed at making slaves work harder. Slaves did work long hours, but then so did most poor European workers around that time. Slave owners didn’t actually demand that much more work from those capable of more work, instead tending to demand similar hours and effort from all slaves of a similar age, gender, and health.

What seems instead to have caused more pain to US south slaves was the vast number of rules that owners imposed, most of which had little direct connection to key problems like shirking at work, stealing, or running away. Rules varied quite a bit from owner to owner, but there were rules on where and when one could travel, times to rise and sleep, who could marry and live with who, who could talk to who when, when and how to wash bodies and houses, what clothes to wear when, who can cook, who can eat what foods, who goes to what sorts of churches when, and so on. Typical rules for slaves had much in common with typical “upstanding behavior” rules widely imposed by parents on their children, and by schools and armies on students and soldiers: eat well, rise early, keep clean, say your prayers, don’t drink, stay nearby, talk respectfully, don’t fraternize with the wrong people, etc.

With so many rules that varied so much, a standard argument against letting slaves visit neighboring plantations was that they’d less accept local rules if they learned of more lenient rules nearby. And while some owners emphasized enforcing rules via scoldings, fines, or reduction of privileges, most often violations were punished with beatings.

Another big cause of pain seems to have been agency failures with overseers, i.e., those who directly managed the slaves on behalf of the slave owners. Owners of just a few slaves oversaw them directly, and many other owners insisted on personally approving any punishments. However still others gave full discretion to overseers and refused to listen to slave complaints.

Few overseers had a direct financial stake in farm profitability, and many owners understood that such stakes would tempt overseers, who changed jobs often, to overwork slaves in the short run at the expense of long run profitability. Even so, short run harvest gains were usually easier for owners to see than long run harm to slaves, tempting overseers to sacrifice the former for the latter. And even if most overseers were kept well in line, a small fraction who used their discretion to beat and rape could impose high levels of net harm.

US south slave plantations were quite literally small totalitarian governments, and the main harms to such slaves seems to parallel the main libertarian complaints about all governments. A libertarian perspective sees the following pattern: once one group is empowered to run the lives of others, they tend to over-confidently over-manage them, adding too many rules that vary too much, rules enforced with expensive punishments. And such governments tend to give their agents too much discretion, which such agents use too often to indulge personal whims and biases. Think abusive police and an excess prison population today. Such patterns might be explained by an unconscious human habit of dominance via paternalism; while dominant groups tend to justify their rules in terms of helping, they are actually more trying to display their dominance.

Now one might instead argue that the usual “good behavior” rules imposed by parents, schools, militaries, and slave owners are actually helpful on average, turning lazy good-for-nothings into upright citizens. And in practice formal rule systems are so limited that agent discretion is needed to actually get good results. And strong punishments are needed to make it work. Spare the rod, and spoil the child, conscript, or slave. From this perspective, US south slave must have led decent lives overall, and we should be glad that improving tech is making it easier for modern governments to get involved in more details of our lives.

Looking to the future, if totalitarian management of individual lives is actually efficient, a more competitive future world would see more of it, leading widely to effective if not official slavery. Mostly for our own good. (This fear was common early in the industrial revolution.) But if the libertarians are right, and most dominant groups tend to make too many overly-harsh rules at the expense of efficiency, then a more competitive future world would see less such paternalism, including fewer slave-like lives.

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Economic Singularity Review

The Economic Singularity: Artificial intelligence and the death of capitalism .. This new book from best-selling AI writer Calum Chace argues that within a few decades, most humans will not be able to work for money.

A strong claim! This book mentions me by name 15 times, especially on my review of Martin Ford’s Rise of the Robots, wherein I complain that Ford’s main evidence for saying “this time is different” is all the impressive demos he’s seen lately. Even though this was the main reason given in each previous automation boom for saying “this time is different.” This seems to be Chace’s main evidence as well:

Faster computers, the availability of large data sets, and the persistence of pioneering researchers have finally rendered [deep learning] effective this decade, leading to “all the impressive computing demos” referred to by Robin Hanson in chapter 3.3, along with some early applications. But the major applications are still waiting in the wings, poised to take the stage. ..

It’s time to answer the question: is it really different this time? Will machine intelligence automate most human jobs within the next few decades, and leave a large minority of people – perhaps a majority – unable to gain paid employment? It seems to me that you have to accept that this proposition is at least possible if you admit the following three premises: 1. It is possible to automate the cognitive and manual tasks that we carry out to do our jobs. 2. Machine intelligence is approaching or overtaking our ability to ingest, process and pass on data presented in visual form and in natural language. 3. Machine intelligence is improving at an exponential rate. This rate may or may not slow a little in the coming years, but it will continue to be very fast. No doubt it is still possible to reject one or more of these premises, but for me, the evidence assembled in this chapter makes that hard.

Well of course it is possible for this time to be different. But, um, why can’t these three statements have been true for centuries? It will eventually be possible to automate tasks, and we have been slowly but exponentially “approaching” that future point for centuries. And so we may still have centuries to go. As I recently explained, exponential tech growth is consistent with a relatively constant rate at which jobs are displaced by automation.

Chace makes a specific claim that seems to me quite wrong.

Geoff Hinton – the man whose team won the landmark 2012 ImageNet competition – went further. In May 2015 he said that he expects machines to demonstrate common sense within a decade. .. Facebook has declared its ambition to make Hinton’s prediction come true. To this end, it established a basic research unit in 2013 called Facebook Artificial Intelligence Research (FAIR) with 50 employees, separate from the 100 people in its Applied Machine Learning team. So within a decade, machines are likely to be better than humans at recognising faces and other images, better at understanding and responding to human speech, and may even be possessed of common sense. And they will be getting faster and cheaper all the time. It is hard to believe that this will not have a profound impact on the job market.

I’ll give 50-1 odds against full human level common sense AI with a decade! Chace, I offer my $5,000 against your $100. Also happy to bet on “profound” job market impact, as I mentioned in my review of Ford. Chace, to his credit, sees value in such bets:

The economist Robin Hanson thinks that machines will eventually render most humans unemployed, but that it will not happen for many decades, probably centuries. Despite this scepticism, he proposes an interesting way to watch out for the eventuality: prediction markets. People make their best estimates when they have some skin in the forecasting game. Offering people the opportunity to bet real money on when they see their own jobs or other peoples’ jobs being automated may be an effective way to improve our forecasting.

Finally, Chace repeats Ford’s error in claiming economic collapse if median wages fall:

But as more and more people become unemployed, the consequent fall in demand will overtake the price reductions enabled by greater efficiency. Economic contraction is pretty much inevitable, and it will get so serious that something will have to be done. .. A modern developed society is not sustainable if a majority of its citizens are on the bread line.

Really, an economy can do fine if average demand is high and growing, even if median demand falls. It might be ethically lamentable, and the political system may have problems, but markets can do just fine.

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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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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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Alexander on Age of Em

If I ever have an executioner, I want him to be Scott Alexander. Alexander has such a winning way with words that I and his many fans enjoy him even when we disagree. I’d hardly notice my destination as his pleasing patter entranced me while we took the long way around to the gallows.

So I am honored that Alexander wrote a long review of Age of Em (9K words, 6% as long as the book), wherein he not only likes and recommends it, he also accepts pretty much all its claims within its main focus. That is, I present my book as being expert on the topic of what would actually happen if cheap ems were our next huge social change. Where Alexander disagrees is on two auxiliary topics, which I mention but on which I claim less expertise, namely how likely is this key scenario assumption, and how valuable is the resulting civilization I describe.

On the subject of value, Alexander leans forager (i.e., liberal) on the forager vs. farmer scale. He dislikes civilization evolving away from the behaviors and values of our forager ancestors, and today he partly blames this on capitalism. He doesn’t see our increase in numbers, comfort, and lifespan as sufficient compensation. (I think he’d like the book Against Civilization.) He says:

[Nick Land’s Ascended Economy] seems to me the natural end of the economic system. Right now it needs humans only as laborers, investors, and consumers. But robot laborers are potentially more efficient, companies based around algorithmic trading are already pushing out human investors, and most consumers already aren’t individuals – they’re companies and governments and organizations. At each step you can gain efficiency by eliminating humans, until finally humans aren’t involved anywhere. .. The Age of Em is an economy in the early stages of such a transformation. Instead of being able to replace everything with literal robots, it replaces them with humans who have had some aspects of their humanity stripped away. Biological bodies. The desire and ability to have children normally. ..

I envision a spectrum between the current world of humans and Nick Land’s Ascended Economy. Somewhere on the spectrum we have ems who get leisure time. A little further on the spectrum we have ems who don’t get leisure time. But we can go further. .. I expect [greatly reduced sex desire] would happen about ten minutes after the advent of the Age of Em .. Combine that with the stimulant use mentioned above, and you can have people who will never have nor want to have any thought about anything other than working on the precise task at which they are supposed to be working at any given time. ..

I see almost no interesting difference between an em world with full use of these tweaks and an Ascended Economy world. Yes, there are things that look vaguely human in outline laboring in the one and not the other, but it’s not like there will be different thought processes or different results. I’m not even sure what it would mean for the ems to be conscious in a world like this – they’re not doing anything interesting with the consciousness. .. If we get ems after all, I expect them to be lobotomized and drugged until they become effectively inhuman, cogs in the Ascended Economy that would no more fall in love than an automobile would eat hay and whinny.

Alexander seems to strongly endorse the usual forager value of leisure over work, so much so that he can’t see people focused on their work as human, conscious, or of any moral value. Creatures only seem valuable to him to the extent that they have sex, leisure time, minds wandering away from work, and desires to do things other than work.

This seems ironic because Scott Alexander is one of the most human and productive workers I know. He has a full time job as a psychiatrist, an especially demanding job, and in addition finds time to write frequent long careful analyses of many topics. I find it hard to see where he has that much time for leisure, and doubt he would in fact be substantially more productive overall if he took drugs to make him forget sex, mentally wander less, and focus more on his immediate tasks. He is exactly the sort of person an em economy would want many copies of, pretty much just as he is. Yet if we are to believe him, he only sees value in his brief leisure hours.

I see Alexander as having too little respect for the functionality of human behaviors and mind design. Yes, maximally competitive em-era behaviors and minds won’t be exactly like current ones. But that doesn’t necessarily mean one wants to throw out most existing behaviors and brain modules wholesale and start over from scratch. As these behaviors and modules all arose because they helped our ancestors be more competitive in some prior context, it makes more sense to try to repair, reform, and repurpose them.

For example, the robust productivity gains observed from workers who take breaks don’t seem to depend much on worker motivation. Breaks aren’t just about motivation; they are a deeply entrenched part of being productive. Similarly, wandering minds may take away from the current immediate task, but they help one to search for hidden problems and opportunities. Also, workers today who focus on just doing immediate tasks often lose out to others who attend more to building and managing social relations, as well as office politics. Love and sex can be very helpful in forming and maintaining relations.

Of course I’m not trying to offer any long term assurances, and it is quite reasonable to worry about what we will lose along with what we will gain. But since today most of the people we most respect and celebrate tend to be workaholics, I just can’t buy the claim that most of us today can’t find value in similarly productive and work-focused ems. And I just can’t see thoughtless workers being the most productive in the early em era of my book.

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Lognormal Jobs

I often meet people who think that because computer tech is improving exponentially, its social impact must also be exponential. So as soon as we see any substantial social impact, watch out, because a tsunami is about to hit. But it is quite plausible to have exponential tech gains translate into only linear social impact. All we need is a lognormal distribution, as in this diagram:


Imagine that each kind of jobs that humans do requires a particular level of computing power in order for computers to replace humans on that job. And imagine that these job power levels are distributed lognormally.

In this case an exponential growth in computing power will translate into a linear rate at which computers displace humans on jobs. Of course jobs may clump along this log-computing-power axis, giving rise to bursts and lulls in the rate at which computers displace jobs. But over the long run we could see a relatively steady rate of job displacement even with exponential tech gains. Which I’d say is roughly what we do see.

Added 3am: Many things are distributed lognormally.

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Excess Turbulence?

To help me imagine how different future cultures might be, I’ve been trying to learn about typical lives of our distant ancestors. One excellent source is Montaillou: The Promised Land of Error by Emmanuel Le Roy Ladurie in 1978. Around 1300 Jacquest Fournier, who eventually became pope but was then a bishop, led an Inquisition against heretics in the small town of Montaillou in southern France, population 200. He transcribed several years worth of interviews of them, revealing great detail about ordinary life there. One tidbit:

Instability was the hallmark of a shepard’s life, as of the lives of all rural workers in Occitania: ‘Every year’, says Oliveier de Serres in his book on agriculture, ‘change your farm hands, make a clean sweep. Those that come after will put all the more heart into their work.’ The people we are concerned with did not feel this instability as some kind of oppression or alienation. On the contrary, the migrant shepard changed his master more often than his shirt! (p.114)

I’m told that even in the modern world one tends to hire new ranch hands every year.

In the farming world, people like shepards, loggers, etc. who lived furthest from concentrations of people tended to have the lowest status and be the poorest. Such jobs were almost entirely done by men, and so such men rarely married until they switched careers. All of which makes some sense. But I’m puzzled that such people typically changed jobs every year, moving many miles away to work with very different people. It is hard to understand such behaviors as productivity maximizing ways forced on people living at the edge of subsistence. This seems instead to be one of the few luxuries such men purchased, so that they could feel less bored and enjoy variety.

A related phenomena is the puzzling fact that people tend to get weary of exerting effort, and so need to take breaks and rest periodically. Not only do people need to rest and sleep at the end of a work day, but on the job mental fatigue reduces mental performance by about 0.1% per minute. Since by resting we can recover at a rate of 1% per minute, we need roughly one tenth of our workday to be break time, with the duration between breaks being not much more than an hour or two (Trougakos and Hideg 2009; Alvanchi et al. 2012). This doesn’t seem to be due to any obvious physical wear or depletion; it seems to be all in our mind.

Both of these examples, a preference for variety in work locations and associates, and a preference for periodic work breaks during the day, seem plausible functional behaviors for our forager ancestors, and also for their more distant animal ancestors. But they make less sense today. Maybe our minds have embedded the assumption that these are functional behaviors at such a deep level that we are still better off following them today. Or maybe not.

Added 25Aug: In many animal species, a single male controls a harem of females, and the other males wander between the harems, looking for a chance to tempt females for illicit trysts, or to challenge a weak harem ruler. Maybe young low status human males are expressing very ancient animal behavioral patterns.

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Light On Dark Matter

I posted recently on the question of what makes up the “dark matter” intangible assets that today are most of firm assets. Someone pointed me to a 2009 paper of answers:


[C.I. = ] Computerized information is largely composed of the NIPA series for business investment in computer software. …

[Scientific R&D] is designed to capture innovative activity built on a scientific base of knowledge. … Non-scientific R&D includes the revenues of the non-scientific commercial R&D industry … the costs of developing new motion picture films and other forms of entertainment, investments in new designs, and a crude estimate of the spending for new product development by financial services and insurance firms. …

[Brand equity] includes spending on strategic planning, spending on redesigning or reconfiguring existing products in existing markets, investments to retain or gain market share, and investments in brand names. Expenditures for advertising are a large part of the investments in brand equity, but … we estimated that only about 60 percent of total advertising expenditures were for ads that had long-lasting effects. …

Investment in firm-specific human and structural resources … includes the costs of employer-provided worker training and an estimate of management time devoted to enhancing the productivity of the firm. … business investments in firm-specific human and structural resources through strategic planning, adaptation, reorganization, and employee-skill building. (more; HT Brandon Pizzola)

According to this paper, more firm-specific resources is the biggest story, but more product development is also important. More software is third in importance.

Added 15Apr: On reflection, this seems to suggest that the main story is our vast increase in product variety. That explains the huge increase in investments in product development and firm-specific resources, relative to more generic development and resources.

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Firms Now 5/6 Dark Matter!

Scott Sumner:

We all know that the capital-intensive businesses of yesteryear like GM and US steel are an increasingly small share of the US economy. But until I saw this post by Justin Fox I had no idea how dramatic the transformation had been since 1975:


Wow. I had no idea as well. As someone who teaches graduate industrial organization, I can tell you this is HUGE. And I’ve been pondering it for the week since Scott posted the above.

Let me restate the key fact. The S&P 500 are five hundred big public firms listed on US exchanges. Imagine that you wanted to create a new firm to compete with one of these big established firms. So you wanted to duplicate that firm’s products, employees, buildings, machines, land, trucks, etc. You’d hire away some key employees and copy their business process, at least as much as you could see and were legally allowed to copy.

Forty years ago the cost to copy such a firm was about 5/6 of the total stock price of that firm. So 1/6 of that stock price represented the value of things you couldn’t easily copy, like patents, customer goodwill, employee goodwill, regulator favoritism, and hard to see features of company methods and culture. Today it costs only 1/6 of the stock price to copy all a firm’s visible items and features that you can legally copy. So today the other 5/6 of the stock price represents the value of all those things you can’t copy.

So in forty years we’ve gone from a world where it was easy to see most of what made the biggest public firms valuable, to a world where most of that value is invisible. From 1/6 dark matter to 5/6 dark matter. What can possibly have changed so much in less than four decades? Some possibilities:

Error – Anytime you focus on the most surprising number you’ve seen in a long time, you gotta wonder if you’ve selected for an error. Maybe they’ve really screwed up this calculation.

Selection – Maybe big firms used to own factories, trucks etc., but now they hire smaller and foreign firms that own those things. So if we looked at all the firms we’d see a much smaller change in intangibles. One check: over half of Wilshire 5000 firm value is also intangible.

Methods – Maybe firms previously used simple generic methods that were easy for outsiders to copy, but today firms are full of specialized methods and culture that outsiders can’t copy because insiders don’t even see or understand them very well. Maybe, but forty years ago firm methods sure seemed plenty varied and complex.

Innovation – Maybe firms are today far more innovative, with products and services that embody more special local insights, and that change faster, preventing others from profiting by copying. But this should increase growth rates, which we don’t see. And product cycles don’t seem to be faster. Total US R&D spending hasn’t changed much as a GDP fraction, though private spending is up by less than a factor of two, and public spending is down.

Patents – Maybe innovation isn’t up, but patent law now favors patent holders more, helping incumbents to better keep out competitors. Patents granted per year in US have risen from 77K in 1975 to 326K in 2014. But Patent law isn’t obviously so much more favorable. Some even say it has weakened a lot in the last fifteen years.

Regulation – Maybe regulation favoring incumbents is far stronger today. But 1975 wasn’t exact a low regulation nirvana. Could regulation really have changed so much?

Employees – Maybe employees used to jump easily from firm to firm, but are now stuck at firms because of health benefits, etc. So firms gain from being able to pay stuck employees due to less competition for them. But in fact average and median employee tenure is down since 1975.

Advertising – Maybe more ads have created more customer loyalty. But ad spending hasn’t changed much as fraction of GDP. Could ads really be that much more effective? And if they were, wouldn’t firms be spending more on them?

Brands – Maybe when we are richer we care more about the identity that products project, and so are willing to pay more for brands with favorable images. And maybe it takes a long time to make a new favorable brand image. But does it really take that long? And brand loyalty seems to actually be down.

Monopoly – Maybe product variety has increased so much that firm products are worse substitutes, giving firms more market power. But I’m not aware that any standard measures of market concentration (such as HHI) have increased a lot over this period.

Alas, I don’t see a clear answer here. The effect that we are trying to explain is so big that we’ll need a huge cause to drive it. Yes it might have several causes, but each will then have to be big. So something really big is going on. And whatever it is, it is big enough to drive many other trends that people have been puzzling over.

Added 5p: This graph gives the figure for every year from ’73 to ’07.

Added 8p: This post shows debt/equity of S&P500 firms increasing from ~28% to ~42% from ’75 to ’15 . This can explain only a small part of the increase in intangible assets. Adding debt to tangibles in the numerator and denominator gives intangibles going from 13% in ’75 to 59% in ’15.

Added 8a 6Apr: Tyler Cowen emphasizes that accountants underestimate the market value of ordinary capital like equipment, but he neither gives (nor points to) an estimate of the typical size of that effect.

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