Caplan Debate Status

In this post I summarize my recent disagreement with Bryan Caplan. In the next post, I’ll dive into details of what I see as the key issue.

I recently said:

If you imagine religions, governments, and criminals not getting too far out of control, and a basically capitalist world, then your main future fears are probably going to be about for-profit firms, especially regarding how they treat workers. You’ll fear firms enslaving workers, or drugging them into submission, or just tricking them with ideology.

Because of this, I’m not so surprised by the deep terror many non-economists hold of future competition. For example, Scott Alexander (see also his review):

I agree with Robin Hanson. This is the dream time .. where we are unusually safe from multipolar traps, and as such weird things like art and science and philosophy and love can flourish. As technological advance increases, .. new opportunities to throw values under the bus for increased competitiveness will arise. .. Capitalism and democracy, previously our protectors, will figure out ways to route around their inconvenient dependence on human values. And our coordination power will not be nearly up to the task, assuming something much more powerful than all of us combined doesn’t show up and crush our combined efforts with a wave of its paw.

But I was honestly surprised to see my libertarian economist colleague Bryan Caplan also holding a similarly dark view of competition. As you may recall, Caplan had many complaints about my language and emphasis in my book, but in terms of the key evaluation criteria that I care about, namely how well I applied standard academic consensus to my scenario assumptions, he had three main points.

First, he called my estimate of an em economic growth doubling time of one month my “single craziest claim.” He seems to agree that standard economic growth models can predict far faster growth when substitutes for human labor can be made in factories, and that we have twice before seen economic growth rates jump by more than a factor of fifty in a less than previous doubling time. Even so, he can’t see economic growth rates even doubling, because of “bottlenecks”:

Politically, something as simple as zoning could do the trick. .. the most favorable political environments on earth still have plenty of regulatory hurdles .. we should expect bottlenecks for key natural resources, location, and so on. .. Personally, I’d be amazed if an em economy doubled the global economy’s annual growth rate.

His other two points are that competition would lead to ems being very docile slaves. I responded that slavery has been rare in history, and that docility and slavery aren’t especially productive today. But he called the example of Soviet nuclear scientists “powerful” even though “Soviet and Nazi slaves’ productivity was normally low.” He rejected the relevance of our large literatures on productivity correlates and how to motive workers, as little of that explicitly includes slaves. He concluded:

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.

As I didn’t think the docility of ems mattered that much for most of my book, I challenged him to audit five random pages. He reported “Robin’s only 80% wrong”, though I count only 63% from his particulars, and half of those come from his seeing ems as very literally “robot-like”. For example, he says 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.

Caplan offered no citations with specific support for these claims, instead pointing me to the literature on the economics of slavery. So I took the time to read up on that and posted a 1600 summary, concluding:

I still can’t find a rationale for Bryan Caplan’s claim that all ems would be fully slaves. .. even less .. that they would be so docile and “robot-like” as to not even have human-like personalities.

Yesterday, he briefly “clarified” his reasoning. He says ems would start out as slaves since few humans see them as having moral value:

1. Most human beings wouldn’t see ems as “human,” so neither would their legal systems. .. 2. At the dawn of the Age of Em, humans will initially control (a) which brains they copy, and (b) the circumstances into which these copies emerge. In the absence of moral or legal barriers, pure self-interest will guide creators’ choices – and slavery will be an available option.

Now I’ve repeatedly pointed out that the first scans would be destructive, so either the first scanned humans see ems as “human” and expect to not be treated badly, or they are killed against their will. But I want to focus instead on the core issue: like Scott Alexander and many others, Caplan sees a robust tendency of future competition to devolve into hell, held at bay only by contingent circumstances such as strong moral feelings. Today the very limited supply of substitutes for human workers keeps wages high, but if that supply were to greatly increase then Caplan expects that without strong moral resistance capitalist competition eventually turns everyone into docile inhuman slaves, because that arrangment robustly wins productivity competitions.

In my next post I’ll address that productivity issue.

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World Basic Income

Joseph said .. Let Pharaoh .. appoint officers over the land, and take up the fifth part of the land of Egypt in the seven plenteous years. .. And that food shall be for store to the land against the seven years of famine, which shall be in the land of Egypt; that the land perish not through the famine. And the thing was good in the eyes of Pharaoh. (Genesis 38)

[Medieval Europe] public authorities were doubly interested in the problem of food supplies; first, for humanitarian reasons and for good administration; second, for reasons of political stability because hunger was the most frequent cause of popular revolts and insurrections. In 1549 the Venetian officer Bernardo Navagero wrote to the Venetian senate: “I do not esteem that there is anything more important to the government of cities than this, namely the stocking of grains, because fortresses cannot be held if there are not victuals and because most revolts and seditions originate from hunger. (p42, Cipolla, Before the Industrial Revolution)

63% of Americans don’t have enough saved to cover even a $500 financial setback. (more)

Even in traditional societies with small governments, protecting citizens from starvation was considered a proper of role of the state. Both to improve welfare, and to prevent revolt. Today it could be more efficient if people used modern insurance institutions to protect themselves. But I can see many failing to do that, and so can see governments trying to insure their citizens against big disasters.

Of course rich nations today face little risk of famine. But as I discuss in my book, eventually when human level artificial intelligence (HLAI) can do almost all tasks cheaper, biological humans will lose pretty much all their jobs, and be forced to retire. While collectively humans will start out owning almost all the robot economy, and thus get rich fast, many individuals may own so little as to be at risk of starving, if not for individual or collective charity.

Yes, this sort of transition is a long way off; “this time isn’t different” yet. There may be centuries still to go. And if we first achieve HLAI via the relatively steady accumulation of better software, as we have been doing for seventy years, we may get plenty of warning about such a transition. However, if we instead first achieve HLAI via ems, as elaborated in my book, we may get much less warning; only five years might elapse between seeing visible effects and all jobs lost. Given how slowly our political systems typically changes state redistribution and insurance arrangements, it might be wiser to just set up a system far in advance that could deal with such problems if and when they appear. (A system also flexible enough to last over this long time scale.)

The ideal solution is global insurance. Buy insurance for citizens that pays off only when most biological humans lose their jobs, and have this insurance pay enough so these people don’t starve. Pay premiums well in advance, and use a stable insurance supplier with sufficient reinsurance. Don’t trust local assets to be sufficient to support local self-insurance; the economic gains from an HLAI economy may be very concentrated in a few dense cities of unknown locations.

Alas, political systems are even worse at preparing for problems that seem unlikely anytime soon. Which raises the question: should those who want to push for state HLAI insurance ally with folks focused on other issues? And that brings us to “universal basic income” (UBI), a topic in the news lately, and about which many have asked me in relation to my book.

Yes, there are many difficult issues with UBI, such as how strongly the public would favor it relative to traditional poverty programs, whether it would replace or add onto those other programs, and if replacing how much that could cut administrative costs and reduce poverty targeting. But in this post, I want to focus on how UBI might help to insure against job loss from relatively sudden unexpected HLAI.

Imagine a small “demonstration level” UBI, just big enough to one side to say “okay we started a UBI, now it is your turn to lower other poverty programs, before we raise UBI more.” Even such a small UBI might be enough to deal with HLAI, if its basic income level were tied to the average income level. After all, an HLAI economy could grow very fast, allowing very fast growth in the incomes that biological human gain from owning most of the capital in this new economy. Soon only a small fraction of that income could cover a low but starvation-averting UBI.

For example, a UBI set to x% of average income can be funded via a less than x% tax on all income over this UBI level. Since average US income per person is now $50K, a 10% version gives a UBI of $5K. While this might not let one live in an expensive city, a year ago I visited a 90-adult rural Virginia commune where this was actually their average income. Once freed from regulations, we might see more innovations like this in how to spend UBI.

However, I do see one big problem. Most UBI proposals are funded out of local general tax revenue, while the income of a HLAI economy might be quite unevenly distributed around the globe. The smaller the political unit considering a UBI, the worse this problem gets. Better insurance would come from a UBI that is funded out of a diversified global investment portfolio. But that isn’t usually how governments fund things. What to do?

A solution that occurs to me is to push for a World Basic Income (WBI). That is, try to create and grow a coalition of nations that implement a common basic income level, supported by a shared set of assets and contributions. I’m not sure how to set up the details, but citizens in any of these nations should get the same untaxed basic income, even if they face differing taxes on incomes above this level. And this alliance of nations would commit somehow to sharing some pool of assets and revenue to pay for this common basic income, so that everyone could expect to continue to receive their WBI even after an uneven disruptive HLAI revolution.

Yes, richer member nations of this alliance could achieve less local poverty reduction, as the shared WBI level couldn’t be above what the poor member nations could afford. But a common basic income should make it easier to let citizens move within this set of nations. You’d less have to worry about poor folks moving to your nation to take advantage of your poverty programs. And the more that poverty reduction were implemented via WBI, the bigger would be this advantage.

Yes, this seems a tall order, probably too tall. Probably nations won’t prepare, and will then respond to a HLAI transition slowly, and only with what ever resources they have at their disposal, which in some places will be too little. Which is why I recommend that individuals and smaller groups try to arrange their own assets, insurance, and sharing. Yes, it won’t be needed for a while, but if you wait until the signs of something big soon are clear, it might then be too late.

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Community Watchers

In my youth, I was skeptical of things I could not see. Like community social health. Not just physical health, but social health, and not just of individuals, but of communities. But now that I am older and can see more, I am convinced: communities exist, and matter. Not just very visible things like jobs, parks, houses, and stores. But harder to see coalitions, cultures, and norms that influence how people feel about and treat each other.

In some places people more often see when someone is hurting, and try to help. Or stop predators on the prowl. Or see other big changes for mutual gain, and coordinate to achieve them. In other places, these happen less. This sort of community health varies not just from city to city, or firm to firm, but from block to block, and from one cubicle row to cubicle row.

If you live in a place for a while, and you are mature enough to see the local social fabric, then you may see your local social health. And while you might want government to help with this, distant government officials managed by and via formal rules can’t do much. Sincere competent local community activists can do more. But while some can choose to become these, it can be hard for others to tell who they are, to support them. What else can we do?

Many people like to travel, and wish somehow to combine travel with doing good. Many also like the idea of secret societies, especially ones devoted to noble causes. I see an opening here for a secret society of travelers devoted to improving community social health.

The idea is simple: a secret society evaluates the local health of communities they visit, and combines these ratings into a public map. If this map came to be seen as reliable, it could shame poor communities into doing more to improve their health. With residents preferring to move to better communities, land owners would gain stronger incentives to promote improvements.

This would not be easy. Society members must be socially perceptive, stay long enough at each place to evaluate well, overcome temptations to push various other agendas and biases in their evaluations, and avoid detection. And they must find ways to collect new similarly virtuous members, even after their society becomes prestigious. This is a tall order.

But the payoff could be huge: healthier communities. If you try to create this, my only advice is: first collect a big enough map in secret and then test it in many ways for accuracy before going public. It isn’t enough that you hope you will be able to do this; wait until you have actually done it.

From a July 14 conversation with Pete Bertine and Andrew Lockhart.

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Grace-Hanson Podcasts

Katja Grace and I recorded two more podcasts:

This adds to our nine previous podcasts:

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AI As Software Grant

While I’ve been part of grants before, and had research support, I’ve never had support for my futurist work, including the years I spent writing Age of Em. That now changes:

The Open Philanthropy Project awarded a grant of $264,525 over three years to Robin Hanson (Associate Professor of Economics, George Mason University) to analyze potential scenarios in the future development of artificial intelligence (AI). Professor Hanson plans to focus on scenarios in which AI is developed through the steady accumulation of individual pieces of software and leads to a “multipolar” outcome. .. This grant falls within our work on potential risks from advanced artificial intelligence, one of our focus areas within global catastrophic risks. (more)

Who is Open Philanthropy? From their summary:

Good Ventures is a philanthropic foundation whose mission is to help humanity thrive. Good Ventures was created by Dustin Moskovitz (co-founder of Facebook and Asana) and Cari Tuna, who have pledged to give the majority of their wealth to charity. .. GiveWell is a nonprofit that finds outstanding giving opportunities and publishes the full details of its analysis to help donors decide where to give. .. The Open Philanthropy Project is a collaboration between Good Ventures and GiveWell in which we identify outstanding giving opportunities, make grants, follow the results, and publish our findings.

A key paragraph from my proposal:

Robin Hanson proposes to take three years to conduct a broad positive analysis of the multipolar scenario wherein AI results from relatively steady accumulation of software tools. That is, he proposes to assume that human level AI will result mainly from the continued accumulation of software tools and packages, with distributions of cost and value correlations similar to those seen so far in software practice, in an environment where no one actor dominates the process of creating or fielding such software. He will attempt a mostly positive analysis of the social consequences of these assumptions, both during and after a transition to a world dominated by AI. While this is hardly the universe of all desired analyses, it does seem to cover a non-trivial fraction of interesting cases.

I and they see value in such an analysis even if AI software ends up differing systematically from the software we’ve seen so far:

While we do not believe that the class of scenarios that Professor Hanson will be analyzing is necessarily the most likely way for future AI development to play out, we expect his research to contribute a significant amount of useful data collection and analysis that might be valuable to our thinking about AI more generally, as well as provide a model for other people to follow when performing similar analyses of other AI scenarios of interest.

My idea is to extract from our decades of experience with software a more detailed description of the basic economics of software production and use. To distinguish, as time allows, many different kinds of inputs to production, styles of production, parts of produced products, and types of uses. And then to sketch out different rough “production functions” appropriate to different cases. That is, to begin to translate basic software engineering insight into economics language.

The simple assumption that software doesn’t fundamentally change in the future is the baseline scenario, to be fed into standard economic models to see what happens when such a more richly described software sector slowly grows to take over the economy. But a richer more detailed description of software economics can also give people a vocabulary for describing their alternative hypotheses about how software will change. And then this analysis framework can be adjusted to explore such alternative hypotheses.

So right from the start I’d like to offer this challenge:

Do you believe that the software that will let machines eventually do pretty much all jobs better than humans (or ems) will differ in foreseeable systematic ways from the software we have seen in the last seventy years of software practice? If so, please express your difference hypothesis as clearly as possible in terminology that would be understandable and familiar to software engineers and/or economists.

I will try to stretch the economic descriptions of software that I develop in the direction of encompassing the most common such hypotheses I find.

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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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