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I haven’t yet posted much on AI as Software. But now I’ll say more, as I want to ask a question.
Someday ems may replace humans in most jobs, and my first book talks about how that might change many things. But whether or not ems are the first kind of software to replace humans wholesale in jobs, eventually non-em software may plausibly do this. Such software would replace ems if ems came first, but if not then such software would directly replace humans.
Many people suggest, implicitly or explicitly, that non-em software that takes over most jobs will differ in big ways from the software that we’ve seen over the last seventy years. But they are rarely clear on what exact differences they foresee. So the plan of my project is to just assume our past software experience is a good guide to future software. That is, to predict the future, one may 1) assume current distributions of software features will continue, or 2) project past feature trends into future changes, or 3) combine past software feature correlations with other ways we expect the future to differ.
This effort may encourage others to better clarify how they think future software will differ, and help us to estimate the consequences of such assumptions. It may also help us to more directly understand a software-dominated future, if there are many ways that future software won’t greatly change.
Today, each industry makes a kind of stuff (product or service) we want, or a kind of stuff that helps other industries to make stuff. But while such industries are often dominated by a small number of firms, the economy as a whole is not so dominated. This is mainly because there are so many different industries, and firms suffer when they try to participate in too many industries. Will this lack of concentration continue into a software dominated future?
Today each industry gets a lot of help from humans, and each industry helps to train its humans to better help that industry. In addition, a few special industries, such as schooling and parenting, change humans in more general ways, to help better in a wide range of industries. In a software dominated future, humans are replaced by software, and the schooling and parenting industries are replaced by a general software industry. Industry-independent development of software would happen in the general software industry, while specific adaptations for particular industries would happen within those industries.
If so, the new degree of producer concentration depends on two key factors: what fraction of software development is general as opposed to industry-specific, and how concentrated is this general software industry. Regarding this second factor, it is noteworthy that we now see some pretty big players in the software industry, such as Google, Apple, and Microsoft. And so a key question is the source of this concentration. That is, what exactly are the key advantages of big firms in today’s software market?
There are many possibilities, including patent pools and network effects among customers of key products. Another possibility, however, is one where I expect many of my readers to have relevant personal experience: scale economies in software production. Hence this bleg – a blog post asking a question.
If you are an experienced software professional who has worked both at a big software firm and also in other places, my key question for you is: by how much was your productive efficiency as a software developer increased (or decreased) due to working at a big software firm? That is, how much more could you get done there that wasn’t attributable to having a bigger budget to do more, or to paying more for better people, tools, or resources. Instead, I’m looking for the net increase (or decrease) in your output due to software tools, resources, security, oversight, rules, or collaborators that are more feasible and hence more common at larger firms. Ideally you answer will be in the form of a percentage, such as “I seem to be 10% more productive working at a big software firm.”
Added 3:45p: I meant “productivity” in the economic sense of the inputs required to produce a given output, holding constant the specific kind of output produced. So this kind of productivity should ignore the number of users of the software, and the revenue gained per user. But if big vs small firms tend to make different kinds of software, which have different costs to make, those differences should be taken into account. For example, one should correct for needing more man-hours to add a line of code in a larger system, or in a more secure or reliable system.
One of the most frustrating things about writing physical books is the long time delays. It has been 17 months since I mentioned my upcoming book here, and now, 8.5 months after we submitted the full book for review, & over 4 months after 7 out of 7 referees said “great book, as it is”, I can finally announce that The Elephant in the Brain: Hidden Motives in Everyday Life, coauthored with Kevin Simler, will officially be published January 1, 2018. Sigh. See summary & detailed outline at the book’s website.
A related sad fact is that the usual book publicity equilibrium adds to intellectual inequality. Since most readers want to read books about which they’ve heard much publicity lately from multiple sources, publishers try to concentrate publicity into a narrow time period around the official publication date. Which makes sense.
But to create that burst of publicity, one must circulate the book well in advance privately among “thought leaders”, who might blurb or review it, invite the authors to talk on it, or recommend it to others who might do these things. So people who plausibly fit these descriptions get to read such books long before others. This lets early readers seem to be wise judges of future popular talk directions. Not because they actually have better judgement, but because they get inside info.
Alas, I’m stuck in this same equilibrium. I have a full copy of my final book, except for minor copy-editing changes, and I can share it privately with possible publicity helpers. And when the relative cost to send an email is small relative to possible gains, a small chance may be enough. I’ll also give in to some requests based on friendship or prior help given me (as on my last book), especially when combined with promises to buy the book when it comes out.
But just as grading is the worst part of teaching, I hate being put in the role of bouncer, deciding who is cool enough to be let into my book club, or who has enough favors to trade. At least when teaching I’m expert in whatever topic I’m grading. But here I’m much less expert on deciding who can help book publicity. I’d really prefer the intellectual world to be more of an open competition without favoritism for those with inside connections. But here I am, forced to play favorites.
These are a few of the prices one pays today to publish books. But still, books remain an unparalleled way to call attention to ideas that need more space to explain than an article can offer. And for a relatively unknown author, established publishers still offer more attention than you could generate on your own. But maybe, just maybe, I can do something different with my third book, whatever that may be on.
I’ve just read five of Peter Turchin’s books: Historical Dynamics (2003), War & Peace & War (2006), Secular Cycles (2009), Ultra Society (2015), and Ages of Discord (2016). Four of them in the last week. I did this because I love careful big picture thinking, and Turchin is one of the few who does this now on the big question of historical cycles of conflict and empire. While historians today tend to dislike this sort of analysis, Turchin defies them, in part because he’s officially a biologist. I bow to honor his just defiance and careful efforts.
Different groups have different degrees of cooperation .. cohesiveness and solidarity. .. Groups with high [cohesion] arise on .. frontier .. area where an imperial boundary coincides with a fault line between two [ethnic] communities .. places where between group competition is very intense. .. Only groups possessing high levels of [cohesion] can construct large empires. ..
Stability and internal peace bring prosperity, and prosperity causes population increase .. leads to overpopulation, .. causes lower wages, higher land rents, and falling per capital incomes. At first, low wages and high rents bring unparalleled wealth to the upper class, but as their numbers and appetites grow, they also begin to suffer from falling incomes. Declining standards of life breed discontent and strife. The elites turn to the state for employment and additional income and drive up its expenditures at the same time that the tax revenue declines. .. When the state’s finances collapse, it loses the control of the army and police. Freed from all restraints, strife among the elites escalates into civili war, while the discontent among the poor explodes into popular rebellions.
The collapse of order brings .. famine, war, pestilence, and death. .. Population declines and wages increase, while rents decline. .. Fortunes of the upper classes hit bottom. .. Civil wars thin the ranks of the elites. .. Intra-elite competition subsides, allowing the restoration of order. Stability and internal peace bring prosperity, and another cycle begins. (pp.5-8 W&P&W)
Turchin (& coauthor Nefedov) collect much data to show that this is a robust farmer-era pattern, even if there are many deviations. For example, in Europe, 33 of 43 frontier situations gave rise to big empires, yet only 4 of 57 of non-frontier situations did (p.84 HD). “Secular cycles” vary in duration from one to four centuries; Western Europe saw 8 cycles in 22 centuries, while China saw 8 cycles in 21 centuries (p.306,311 SC). During the low instability part of each cycle, instability shows a rough “alternating generations” 50 year cycle of conflict.
I’ll grant that Turchin seems to have documented a reasonably broad pattern, containing most of his claimed elements. Yes, empires tend to start from frontier groups with high cohesion, and core cohesion changes slowly. First there’s war success and a growing area and population, and bigger cities. Eventually can come crowding and falling wages. Inequality also grows, with more richer elites, and this is quite robust, continuing even after wages fall.
While the amount of external war doesn’t change over the cycle, success in war falls. Many signs of social cohesion decline, and eventually there’s more elite infighting, with crime, duels, misspending state revenue, mistreatment of subordinates, and eventually civil war. Big wars can cut population, and also elite numbers and wealth. Eventually war abates and cohesion rises, though not to as high as when the empire started. A new cycle may begin; empires go through 1-3 cycles before being displaced by another empire.
Just as science fiction is often (usually?) an allegory about issues today, I suspect that historians who blame a particular fault for the fall of the Roman Empire tend to pick faults that they also want to warn against in their own era. Similarly, my main complain about Turchin is that he attributes falling cohesion mainly to increased inequality – an “overproduction” of elites who face “increased competition”. Yes, inequality is much talked about among elites today, but the (less-forager-like) ancients were less focused on it.
As Scheidel said in The Great Leveler, inequality doesn’t seem to cause civil wars, and civil wars tend to increase inequality during and after the war (p.203). External wars reduce inequality for losers and increase it for winners, without changing it much overall. It is only big mass mobilization wars of the 1900s that seem to clearly cause big falls in inequality.
In biology, over multiple generations organisms slowly accumulate genetic mutations, which reduce their fitness. But this degradation is countered by the fact that nature and mates select for better organisms, which have fewer mutations. Similarly, it seems to me that the most straightforward account of the secular cycle is to say since empire founders are selected out of a strong competition for very high cohesion, we should expect cohesion to “regress to the mean” as an empire evolves.
That is, in order to predict most of the observed elite misdeeds later in the secular cycle, all we need to assume is a random walk in cohesion that tends to fall back to typical levels. Yes, we might want to include other effects in our model. For example, civil war may allow a bit more selection for subgroups with more cohesion, and humans may have a psychological inclination to cohere more during and after a big war. But mostly we should just expect cohesion to decline from its initial extreme value, and that’s all a simple model needs.
Yes, Turchin claims that we know more about what causes cohesion declines. But while he goes to great effort to show that the data fit his story on which events happen in what order during cycles, I didn’t see him offering evidence to support his claim that inequality causes less cohesion. He just repeatedly gives examples where inequality happened, and then instability happened, as if that proves that the one caused the other.
We already have good reasons to expect new empires to start with a small area, population, and inequality. And this by itself is enough to predict growing population, which eventually crowds to cut wages, and increasing inequality, which should happen consistently in a very wide range of situations. I don’t see a need for, or data support for, the additional hypothesis that inequality cuts cohesion. We may of course discover more things that influence cohesion, and if so we can add them to our basic secular cycle model. But we don’t need such additions to predict most of the cycle features that Turchin describes.
In his latest book, Turchin points out many U.S. signs today of rising inequality and declining social cohesion, and at the end asks “Will we be capable of taking collective action to avoid the worst of the impending democratic -structural crisis? I hope so.” But I worry that his focus on inequality leads people to think they need to fight harder to cut inequality. In contrast, what we mostly need is just to fight less. The main way that inequality threatens to destroy us is that we are tempted to fight over it. Instead, let us try more to see ourselves as an “us” contrasted with a “them”, an us that needs to stick together, in part via chilling and compromising, especially regarding divisive topics like inequality.
I just finished reading Walter Scheidel’s The Great Leveler: Violence and the History of Inequality from the Stone Age to the Twenty-First Century, and found myself agreeing with Scheidel against his critics. Scheidel is a historian who says that inequality has mainly risen in history when income increased, making more inequality physically possible, and when scale and complexity increased, creating more and bigger chokepoints (e.g., CEO, king) whose controllers can demand more rents.
Big falls in inequality have mainly come from big collapses, such as big wars, revolutions, plagues, and state collapses, which are usually associated with violence. This suggests that a big inequality fall is unlikely anytime soon, and we shouldn’t wish for it, as it would likely come from vast destruction and violence. All of which I find very plausible.
While usually big wars via mass mobilization didn’t change inequality much, in the mid 1900s such wars seemed to have gone along with a big taste for redistribution and revolution. This happened to a lesser extent in Ancient Greece and Rome, and fits a story wherein more forager-like cultures care more about redistribution, especially when primed by visible mass sacrifice.
I noticed one puzzling pattern, however. Income in the world goes to owners of capital, to owners of labor, and to those who can take without contributing to production. As the rich usually get more of their income from capital, compared to labor, one thing that can cause less inequality is a change that makes capital earn a smaller share of total income. The puzzling pattern I noticed is that even though big plagues and big wars should have opposite affects on the capital share, both of them seem to have cut inequality, and both apparently in part via cutting the capital share of income! Let me explain.
Big plagues cut the number of workers without doing much to capital, while big wars like WWI & WWII destroy a much larger fraction of capital than they do of labor. Which event, big plague or big war, reduces the share that capital earns? The answer depends on whether capital and labor are complements or substitutes. If they are substitutes, then destroying capital should cut the capital share of income. But when they are complements, it is destroying labor that should cut the capital share.
The simple middle position between complements and substitutes is the power law (a.k.a. “Cobb-Douglas”) production function, where output Y = La*K1-a, for Labor L, capital K, and constant a in (0,1). (Partial derivatives set wages w = dY/dL and capital rent r = dY/dK.) In this situation, the capital share of income r*K/(r*K+w*L) = 1-a, and so never changes.
If, for example, labor L falls by a factor of 2, while capital K stays the same, then wages rise by the factor 21-a while rents fall by the factor 2a, with the product of these factors being 2. Compared to this simple middle position, if labor and capital are instead complements, then in this example wages would rise and rents would fall by larger factors. If labor and capital are instead substitutes, the factors would be smaller.
Economic papers based on data over the last century usually find labor and capital to be complements, though there are notable exceptions such as Thomas Pietty’s blockbuster book. That fits with data on the Black Death. In the century from 1330 to 1430, Europe’s population fell roughly in half, wages doubled, and rents fell a lot. In England, wages tripled. Similar behavior is seen in other large ancient plagues – wages rose by a factor of four in Mexico! This looks more like what you’d see with complementarity than with a simple power law.
World War I (WWI) killed about 1% of the world population, while the concurrent 1918 flu killed about 4%. World War II (WWII) killed about 3%. But capital was cut much more. The ratio of private wealth to national income fell by a factor of two world wide, and by even larger factors in the main warring nations (source):
Now for the puzzle. If capital and labor were still complements during WWI & WWII, then destroying a lot more capital than labor should have resulted in rents on capital rising by a factor so big that product of the two factors increases the capital share of income. Is that what happened? Consider Japan, where 5% of the population died:
Real [Japanese] farm rents fell by four-fifths between 1941 and 1945, and from 4.4% of national income in the mid 1930s to 0.3% in 1946. .. By September 1945, a quarter of the country’s physical capital stock had been wiped out. Japan lost 80% of its merchant ships, 25% of all buildings, 21% of household furnishings and personal effects, 34% of factory equipment, and 24% of finished products. The number of factories in operations and the size of the workforce they employed nearly halved during the final year of the war. p.121
Gains from capital almost disappeared during the war years: the share of rent and interest income in total national income fell from a sixth in the mid-1930s to only 3% in 1946. In 1938, dividends, interest, and rental income together had accounted for about a third of the income of the top 1%, with the remainder divided between business and employment income. By 1945, the share of capital income had dropped to less than an eighth and that of wages to a tenth; business income was the only significant revenue source left to the (formerly) wealthy. p.122
In 1946, real GNP was 45% lower than it had been in 1937. p.124
The sharp drop in top income shares .. were caused above all by a decline in the return on capital. .. Most of these changes occurred during the war itself. p.128
Consider also France and Germany (which lost 2% & 11% of people in WWII, respectively):
During WWI, .. a third of the French capital stock was destroyed, the share of capital income in national household income fell by a third, and GDP contracted by the same proportion. ..In WWII, .. two-thirds of the capital stock was wiped out. .. real rents fell by 90% between 1913 and 1950. p.147
[German] rentiers lost the most: their share of national income plummeted from 15% to 3% even as entrepreneurs were able to maintain their share .. real national income was a quarter to a third lower in 1923 than it had been in 1913. p.152
Maybe I’m missing something, but I don’t see how this is remotely consistent with labor and capital being complements. Yet complementarity seems a good fit to big ancient plagues and more recent empirical studies. What gives?
We each feel a deep strong need to love others, and to be loved by others. (Self-love doesn’t satisfy these needs.) You might think we could pair up and all be very satisfied. But this doesn’t happen for two main reasons:
So even if you are my best source for getting love, the love I get from you may be far less than the love you are giving out, or than I’m giving out. And a few exceptional people (many of them imaginary) get far more love than most people need or can enjoy.
This seems an essential tragedy of the human condition. You might claim that love isn’t a limited resource, that the more people each of us love, the more love we each have to give out. So there is no conflict between loving popular and imaginary people and loving the rest of us. But while this might be true at some low scales of how many people we love, at the actual scales of love this just doesn’t seem right to me. Love instead seems scarce at the margin.
Can we do anything about this problem? Well one obvious fact is that we don’t love people we’ve never heard of. And we can control many things about who we hear of. So we could in principle arrange who we hear about, in order to get love spread out more evenly. But we don’t do this, nor do we seem much inclined to do anything like this. We instead all devote a great deal of time and effort to hearing about as many popular and fictional people as possible. And to trying to be as popular as we can.
I don’t have great ideas for how to solve this. But I am convinced it is one of our essential problems, and it is far from obvious that we’ve given it all the careful thought we might. Please, someone thoughtful and clever, figure out how we might all be much loved.
Many animal species are organized into harems, wherein a single male dominates a group of females and their children. When males become adult, they must leave home and wander singly or in small male groups hoping to tempt harem females into liaisons or to start new harems.
I’ve heard that polygamous sects are often run this way today, with older men kicking out young men when they come of age. But re-reading Montaillou on rural 1300 France makes me realize that humanity has long has related harem-like gender patterns.
Back in 1300 France, centrality gave status. The biggest cities were at the top, above towns and then villages. At the bottom were woodcutters and shepards, all male, who spent most of their time wandering far from villages or towns. Along with soldiers and sailors, these men lived dangerous low-status high-mobility lives in sparse areas. They sometimes tempted women into liaisons, or made it rich enough to start a family in a village. Such mating strategies may explain why such men moved so often even they were poor and moving is expensive.
Back in the high status centers, there remained a few high status men and women, many low status women, but fewer low status men. The lower status women were often servants to high status males, and often had affairs with them.
In the US today, the states with the most men relative to women are Alaska, Wyoming, North Dakota, Nevada, Utah, and Montana — mostly harsher low density areas. In contrast, the states with the most women relative to men are District of Columbia, Rhode Island, Maryland, Massachusetts, New York, near some of our biggest high status cities. Most big US cities have more women than men. The exceptions are San Jose, San Francisco, Las Vegas, Honolulu, Austin, Seattle, San Diego, places with new booming, mostly tech, industries. Men are more willing to move to try new often-harsher industries and places.
We hear college-educated women complain today that there aren’t enough college-educated men to go around, either during college itself or afterward. Of course there are plenty of other men around, but these women mostly consider such men beneath them. Seems to me this isn’t that different from 1300 France; women are more eager to locate near high status people. They focus on high status men, and lament there aren’t enough to go around.
Sometimes people fear today that low status men unhappy from being unable to find women will cause havoc. But in the past men avoided such feelings successfully by just avoiding women. By rarely seeing women they less often felt the envy that might cause havoc. If there’s a bigger problem today it might be because low status men more often come into contact with attractive but unavailable women. From this perspective, maybe low status men avoiding women via male-oriented video games isn’t such a bad thing?
Added 5July: Birds are like this too.
Some people like murder mystery novels. I much prefer intellectual mysteries like that in Garett Jones’ new book Hive Mind: How Your Nation’s IQ Matters So Much More Than Your Own:
Over a decade ago I began my research into how IQ matters for nations. I soon found that the strong link between average IQ and national productivity couldn’t be explained with just the conventional finding that IQ predicts higher wages. IQ apparently mattered far more for nations than for individuals. In my early work, I estimated that IQ mattered about six times more for nations than for individuals: your nation’s IQ mattered so much more than your own. That puzzle, that paradox of IQ, is what set me on my intellectual journey. …
I’ll lay out five major channels for how IQ can pay off more for nations than for you as an individual: Continue reading "Hive Mind" »
Noble gentlemen and ladies in [Japan’s] Heian period (794-1185) were often remarkably promiscuous. … “Heian society was on the whole governed by style rather than by any moral principles, and good looks tended to take the place of virtue.” … It was, as all this suggests, a rather effete culture. The aristocratic ideal of male beauty—highly perfumed, moon-faced, smooth-skinned, extravagantly dressed—was close to the feminine ideal. A distinct air of decadence during the peak of the Heian period also suggests the approaching end of a regime, a world, in Genji’s words, “where everything seems to be in a state of decline.”
Less than two hundred years later, the self-obsessed nobility of the Heian court, distracted by the rituals and refinements of palace politics, oblivious of the world outside the capital, and mostly bored out of their minds, were overwhelmed by more vigorous provincial clans, notably the samurai, with their warrior codes and martial ideals. But in Genji’s time, the early eleventh century, the imperial capital (today’s Kyoto) still held sway; anyone unlucky enough to live in the provinces was considered too uncouth to be taken seriously. (more)
This seems a familiar history story, that elite self-indulgence and moral decadence causes social decay and displacement. It contributes to the Hunger Games stories, for example. It also seems a common foundation of conservative thought. But, is it true? I ask because I actually do not know. Has anyone done statistical tests on systematic historical datasets to see if decadence actually causes decay and displacement? I could imagine counter arguments, such as that decadence promotes peace instead of destructive war-mongering. So I’d prefer not to have to rely only on a few anecdotes and plausible intuitions.
I’m in the last few weeks of finishing my book The Age of Em: Work, Love, and Life When Robots Rule The Earth, about social outcomes in a world dominated by brain emulations. As a teaser, let me share some hopefully non-obvious results about redistribution in the em world.
There are many kinds of inequality. Inequality exists between different species, between generations born at different times, and between nations of the world at a time. Within a nation at a time, there is inequality both between families and within families. There is also inequality across the moments of the life of each person. In all of these cases, there is not only financial inequality, but also inequality in status, prestige, pleasure, lifespan, happiness, and more. There is also inequality between the size of families, firms, cities, or nations, even when individuals within those groupings are equal.
Today, we have relatively little intentional redistribution between generations or between nations. Redistribution within the moments of a person’s life happens, but that is mostly left to that person to choose and to fund. Similarly, redistribution between siblings is mostly achieved via differential treatment by parents. Instead, most concern today about inequality, and most debate about redistribution to address inequality, focuses on one very particular “standard” kind of inequality.
This standard inequality looks at differences in average individual financial incomes between the families of a nation, all at a given time. This type of inequality is actually one of the smallest. For example, in the U.S. today financial inequality between families is only one third the size of that inequality between siblings within families, and even that is much less than the inequality between individuals from different nations. We may focus our redistribution feelings on this standard inequality because it seems to us the most analogous to the inequality that forager sharing norms addressed. Alternatively, perhaps it is the most profitable type of redistribution for opportunistic rent-seekers.
This history suggests that the em world will have little redistribution between em generations or city states, and also that each clan is mostly in charge of deciding how to address inequality within that clan. After all, em clan members are more similar and closer to each other than are human siblings, even if they may sometimes be more distant from each other than are typical human life moments. Also, clan members have rather complex relations with each other, making it hard pick a natural sub-clan unit to be the standard basis for counting inequality. So that leaves ems with comparing inequality between clans.
A set of em clans can be unequal in two different ways. One way focuses on individual incomes, or perhaps individual happiness or respect, and says that a clan is better off if its individuals are on average better off. The other way focuses on the overall size and success of a clan. Here a clan is better off if it has more members, resources, or respect. Historically, most redistribution efforts have focused on average individual outcomes. For example, we have seen very little efforts to redistribute between human family clans based on family size. That is, we almost never take from families with many descendants in order to give to families that have few descendants. Nor do we take much from big nations, cities, or firms to give to smaller ones.
Because most em wages are near subsistence levels, unregulated wages have less inequality than do wages today. So em clans naturally have less inequality of the standard sort that is the focus of today’s redistribution. In contrast, em clans have enormous inequality in clan size, resources, and respect. However, history gives little reason to expect much redistribution to address this inequality. It is not very analogous to forager sharing, nor does it lend itself to profitable rent-seeking.
Thus the main kind of redistribution that we have reason to expect in the em era is between the clans of a city, based on differences of average within-clan individual income. But we expect less inequality of this sort in the em world, and so expect less redistribution on this basis.
Income taxes are today one of our main mechanisms for reducing the standard inequality that compares individual incomes between families within a nation. Over the last two centuries, big increases in the top marginal tax rates have mostly followed wars where over two percent of the population served in the military. For example, in the U.S. the top marginal tax rate jumped from 15% to 67% in 1917, during World War I. Controlling for this effect, top tax increases have not been correlated with wealth, democracy, or the political ideology of the party running the government. This weakly suggests that the local degree of individual income redistribution between the clans of an em city may depend on the local frequency of large expensive em wars.
If ordinary humans are included straightforwardly in the redistribution systems of the em world, then the simple result to expect is transfers, not only away from richer humans, but also from humans to ems overall. After all, in purely financial terms typical ems are poorer than the poorest humans. Redistribution systems may perhaps correct for the fact that em subsistence levels are much lower than are human subsistence levels. But if so such systems may also encourage or even require recipients of aid to switch from being a human to being an em, in order to lower costs.
During the em era, humans typically have industrial era incomes, which are much higher than subsistence level incomes. While many and perhaps most humans may pay to create a few ems, they tend to endow them with much higher than subsistence incomes. In contrast, a small number of successful humans manage to give rise to large em clans, and within these clans most members have near subsistence incomes. Thus transfers based on individual income inequality take from the descendants of less successful humans and give to descendants of more successful humans.