Tag Archives: Inequality

Rich Is Far

By Robin Hanson · March 27, 2013 10:45 am · Comments (16)

[We hypothesized that] reminders of (a great deal of) money facilitate global, abstract mental construals … [while] reminders of expenditure or a little money should trigger more concrete mental representations. … Participants were primed with money or money-unrelated concepts. Money primes caused a preference for abstract over concrete action identifications (experiment 1), instigated the formation of broader categories (experiment 2), and facilitated the identification of global (vs. local) aspects of visual patterns (experiment 3). This effect extended to consumer judgments: money primes caused a focus on central (vs. peripheral) aspects of products (experiment 4) and increased the influence of quality of parent brands in evaluations of brand extensions. Priming with a little money (experiment 3) or expenditures (experiment 5) did not trigger abstract construals, indicating that the association between money and resources drives the effect. (more)

We’ve long known that power tends to induce far mode. So now we can say that the rich and powerful tend to think in a more far mode. That includes the entire world, since the world has been getting richer and more powerful. This plausibly explains why our “moral circles” have continued to widen over time, and helps us see why our era’s thinking is an especially deluded “dreamtime.”

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Wanted: Elite Crowds

By Robin Hanson · November 6, 2012 8:45 am · Comments (3)

This weekend I was in a AAAI (Association for the Advancement of Artificial Intelligence) Fall Symposium on Machine Aggregation of Human Judgment. It was my job to give a short summary about our symposium to the eight co-located symposia. Here is what I said.

In most of AI, data is input, and judgements are output. But here humans turn data into judgements, and then machines and institutions combine those judgements. This work is often inspired by a “wisdom of crowds” idea that we often rely too much on arrogant over-rated experts instead of the under-rated insight of everyone else. Boo elites; rah ordinary folks!

Many of the symposium folks are part of the IARPA ACE project, which is structured as a competition between four teams, each of which must collect several hundred participants to answer the same real-time intelligence questions, with roughly a hundred active questions at any one time. Each team uses a different approach. The two most common ways are to ask many people for estimates, and then average them somehow, or to have people trade in speculative betting markets. ACE is now in its second of four years. So, what have we learned?

First, we’ve learned that it helps to transform probability estimates into log-odds before averaging them. Weights can then correct well for predictable over- or under-confidence. We’ve also learned better ways to elicit estimates. For example, instead of asking for a 90% confidence interval on a number, it is better to ask for an interval, and then for a probability. It works even better to ask about an interval someone else picked. Also, instead of asking people directly for their confidence, it is better to ask them how much their opinion would change if they knew what others know.

Our DAGGRE team is trying to improve accuracy by breaking down questions into a set of related correlated questions. ACE has also learned how to make people better at estimating, both by training them in basic probability theory, and by having them work together in teams.

But the biggest thing we’ve learned is that people are unequal – the best way to get good crowd wisdom is to have a good crowd. Contributions that most improve accuracy are more extreme, more recent, by those who contribute more often, and come with more confidence. In our DAGGRE system, most value comes from a few dozen of our thousands of participants. True, these elites might not be the same folks you’d have picked via resumes, and tracking success may give better incentives. But still, what we’ve most learned about the wisdom of crowds is that it is best to have an elite “crowd.”

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Inequality /=> Revolt

By Robin Hanson · September 21, 2012 11:10 am · Comments (21)

Famous historical revolutions were not consistently caused by high or rising income inequality:

[French income] inequality during the eighteenth century was large but decreased during the revolutionary period (1790-1815). … When industrialisation began about 1830, inequality increased until sometime in the 1860s. (more)

In 1904, on the eve of military defeat and the 1905 Revolution, Russian income inequality was middling by the standards of that era, and less severe than inequality has become today in such countries as China, the United States, and Russia itself. (more)

In 1774 the American colonies had average incomes exceeding those of the Mother Country, even when slave households are included in the aggregate. … American colonists had much more equal incomes than did households in England and Wales around 1774. Indeed, New England and the Middle Colonies appear to have been more egalitarian than anywhere else in the measureable world. Income inequality rose dramatically between 1774 and 1860, especially in the South. (more)

So why do most people so confidently believe that revolutions were caused by high or rising inequality? I’d guess its because it feels like a nice way to affirm your support for the standard forager value of more equality.

Added 24Sept: OK, I see that the French data isn’t so relevant to my point.

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Inequality Is Diversity

By Robin Hanson · April 17, 2012 11:20 pm · Comments (18)

The Cambrian explosion … was the relatively rapid appearance, around 530 million years ago, of most major animal phyla, as demonstrated in the fossil record, accompanied by major diversification of organisms including animals, phytoplankton, and calcimicrobes. Before about 580 million years ago, most organisms were simple, composed of individual cells occasionally organized into colonies. Over the following 70 or 80 million years the rate of evolution accelerated by an order of magnitude (as defined in terms of the extinction and origination rate of species[4]) and the diversity of life began to resemble that of today. (more)

Now that humans have pioneered powerful innovations in law, tech, and organization, the obvious long-term future to expect is a diversity in use of those innovations: our descendants will radiate out in feature space to fill a wide range of niches, not only on Earth, but under and above it as well. Just as Cambrian explosion descendants shared common cell tech and structures, our descendants may mostly preserve some key features of human minds and societies far into the coming explosion. But that still leaves room for a vast diversity.

Since our society tends to give lip service to celebrating diversity, it can also give lip service to celebrating this future diversity. But humans also tend to be wary of inequality. Foragers were especially vigilant to prevent some of them from overtly dominating others, and while farming and industry cultures have led us to tolerate more inequalities, we aren’t especially happy about it.

This is a problem because it is very hard to imagine a Cambrian explosion level of diversity among our descendants without a lot more inequality. For plants or animals today, pick most any dimension along which you want to call some “better” than others, and you’ll find a wide variation — some are a lot better than others. Pretty much the only dimension in which all existing species are near “equal” is survival – all have survived. But of course they are a tiny fraction of winners vastly outnumbered by all the dead loser species.

Thus our descendants are likely to differ greatly from one another on most all imaginable dimensions, including dimensions of value, where some are called “better”. The only ways to prevent that is either to destroy all descendants, or for a central power to seize control of this process and impose a concept of equality favored by those who control it. And if you supported an attempt to seize central control on this basis, you’d risk folks with other agendas seizing control of this central power base.

While such a central control attempt might make sense someday, when we have learned better ways to coordinate, for now I think we have to accept that the future will come with both great diversity and great inequality – and that we can’t really have much diversity without a lot of inequality as well.

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Em Need For Speed

By Robin Hanson · April 16, 2012 1:35 pm · Comments (18)

I recently found fault with Keith Henson’s assumption that sexual competition would induce ems to run as fast as physically possible. So how fast do I think ems would run? Here is my current analysis:

Em speeds should intersect supply and demand. Speed supply comes from how em hardware (e.g., device, energy, and cooling) costs vary with speed. Since human brains use a very parallel design with cells whose signals change far slower than electronic circuits, the cost of em hardware should be roughly linear in em speed across a wide range, to a very fast max, perhaps a million times faster than humans. In this range, thinking twice as fast costs about twice as much.

Above that linear regime, a 1% speedup will add more than 1% to costs, with this speed premium approaching infinity at a maximum feasible speedup, perhaps a factor of a billion. Very slow ems should also suffer a cost premium, as they’d still need to store a mental state.

With compatible hardware, brief speed increases might be cheap if em brains have substantial heat capacity. Longer but still temporary speed changes might be made by swapping into different brain hardware, though this could have substantial switching costs.

On the demand for em speed, I see seven relevant factors:

  1. When physical systems have natural resonance periods, managing those systems suggets em response times near the shortest of those periods. For example, since small moveable human body parts have resonance periods of a fraction of a second, human brains have reaction times on that time scale – reacting faster might help sometimes, but costs too much. Ems with smaller human-like bodies would want faster brains to match their shorter periods.
  2. Ems that talk often would benefit from having similar mind speeds. This would create a tendency for em speeds to clump at common standard speeds. Ems that talk often to humans would have near human speeds. Ems with highly mismatched speeds could talk naturally if the slow one temporarily moved to faster mental hardware.
  3. It is awkward for ems to talk when there are substantial communication delays. For any given distance to em conversation partners, there is some max speed above which delays are noticeable and hence costly.
  4. It is tempting to use faster ems to speed up any project whose duration might take a substantial fraction of the economy’s doubling time, or where there is a race with competing projects. Of course project durations may be limited by factors other than em thinking speeds.
  5. The more important is a negotiation or argument between ems, the more private gains can come from having a faster em mind, to out-think the other ems. So in hierarchical organizations, higher level leaders would have faster minds.
  6. When it is useful to coordinate two different tasks, one could either have two ems do the two tasks and talk periodically, or have a single faster em do both tasks. A single em doing both tasks probably has skills less well matched to those tasks, and would pay extra costs to switch between tasks. But when task coordination is important enough, these can be prices worth paying.
  7. When it is important to minimize the time a worker is away from their tasks at leisure and sleep, it will be tempting to run those non-work activities very fast. This could allow near continuous time coverage of a task.

Thus while some ems will have speeds to match the physical systems they manage, and ems would be faster at sleep, leisure, on thinking-dominated projects, and at high organization levels. The speed of other ems would be set more by how important is coordination for their tasks, and em speeds would tend to clump.

Coordination seems especially important in key design tasks, and in management. For example, it would be especially tempting to have all the parts of a large intricate software project written by the same very fast em. It would also be tempting to have the top thousand or more manager roles in a big organizations all be filled by a single very fast em.

Faster ems would naturally tend to be richer ems, if nothing else because they’d have some discretion in how they used their time, and that time is worth more. Thus a single very fast boss could afford to own more of a firm, reducing owner vs. manager conflicts.

If faster ems tend to be richer, win arguments, and fill key design and management roles, they would naturally be treated as higher status, at least by our status cues. Ems would also likely see them as higher status.

Social roles can often be usefully divided into roles that deal more with insiders, vs. roles that deal more with outsiders. For example, in a family, childcare is an inside role, while working for money is an outside role. In a hierarchical organization, managers have a more outside role – they deal more with outsiders. We care more about openness and helpfulness in inside roles, but more about opacity and toughness in outside roles.

When ems of different speeds meet, the slower em would naturally be more transparent and the faster one more opaque. It seems that faster ems would tend more to take on outside roles, which will be associated with higher status. In hierarchical organizations, subordinates might be expected to be open, such as via allowing direct hardware access to their emotional expressions, while bosses might typically hide their feelings from subordinates.

The overall picture here seems to be of even more inequality than I had imagined when I just considered wealth inequality among a larger future population whose lifespans vary more. Each em firm may have one very fast rich dominant boss who personally owns a lot of the firm. All front line managers might report to this one super boss, in meetings where they temporarily run at boss speeds, and are expected to be emotionally open to boss inspection. Sir, yes sir!

All else equal, an increase in the spatial extent of a firm or city would tend to reduce the speed of ems that might notice substantial communication delays. If em firms and cities tend to naturally grow larger over time, they’d also tend to naturally become slower, at least at their peak speeds. The gains that the would have otherwise achieved from faster speeds would be compensated by being able to interact naturally with a wider range of ems.

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You Are Panem’s Capitol

By Robin Hanson · March 23, 2012 5:30 pm · Comments (56)

A reporter asked me how the world would be different if people took a year of leisure after each seven years of work, instead of retiring at 65, as I suggested in Why Retire? I guessed that young people would have more interesting stories to tell about what they did with their year off. More interesting at least than the typical retiree story of another year of golfing or organizing photo albums. As people get older they get more comfortable with set patterns, and less eager for adventure.

This might be good for their near needs, but less fits our far ideals about how we should live our lives. This is also probably why people tend to like marriage more than you might think from their youthful inclinations.

I thought of this while watching The Hunger Games. The book and movie express a strong sincere class and urban/rural envy and hatred. People from the heroine’s poor starving coal-mining District 12 are not allowed to leave or choose their laws, and are forcibly humiliated by the Capitol region, where folks live in lazy shallow luxury.

You might think this echoes your 99%er hatred of the 1%, but not only is the anti-urban-elite element strong here, on a cosmic scale you are more like Panem’s Capitol than District 12. Because unless humanity creates a strong permanent central government to control fertility, far future folk will return to very slow growth, and thus to near subsistence incomes. And you might consider what this vast horde will think of your rich ways.

Yes, you didn’t choose to live now, and you may have a right to spend your wealth any way you want. But future folk may have a right to hate or despise you, if they think you have mostly squandered the gift of living in our rare age of luxury. District 12 folks despise Capitol folk not just because their riches seem stolen, but also because they seem weak, shallow, selfish, and self-indulgent, with little sense of or contribution to larger possibilities. Future folk may think the same about you.

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Haves And Have-Nots

By Robin Hanson · March 20, 2012 11:20 pm · Comments (44)

I often ask my students to predict the social effects of particular new products or technologies. And a common error is that they expect every new thing to increase inequality. Their argument is that any new thing costs money, which rich people can better afford. So the rich must more gain advantage from each new product. A similar argument is given for a new kind of job – those better suited to that kind of job will do that job, and gain an advantage over people with other jobs, increasing the job induced inequality.

An obvious flaw in this argument is that it works way too well – it applies to pretty much anything new. Yet the net effect of all the new things that we’ve ever seen has been at most a modest increase in inequality. Thus the average inequality produced by each new thing must be pretty small. Also, there have been eras when inequality has decreased – but how could that happen if each new innovation increases inequality?

Students are often tempted to imagine an extreme division of society into haves and have-nots, like the Eloi and Morlocks of H.G.Well’s novel The Time Machine. The imagined groups are entirely distinct and separate, with little variation within each group. And of course these groups are in a moral struggle, to the death. This seems an obvious consequences of thinking about the future in a far mental mode – which leans one toward fewer categories with more uniform members, more moralizing, and less moral compromise.

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Rah Power Laws

By Robin Hanson · February 14, 2012 1:15 pm · Comments (13)

The latest Science has an article by Michael Stumpf and Mason Porter, complaining that people aren’t careful enough about fitting power laws. It mentions that a sum of heavy-tail-distributed things generically becomes has a power law tail in the sum limit. And it claims:

Although power laws have been reported in areas ranging from finance and molecular
biology to geophysics and the Internet, the data are typically insufficient and the mechanistic insights are almost always too limited for the identification of power-law behavior to be scientifically useful … Examination (15) of the statistical support for numerous reported power laws has revealed that the overwhelming majority of them failed statistical testing (sometimes rather epically).

Yet in reference 15, where Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman looked carefully at 25 data sets that others had claimed fit power laws, only for 3 did they find less than moderate support for a power law fit, and in none of those cases was any other specific model significantly favored over a power law! It this is the best criticism they’ve got, this seems to me resounding support for power laws.

Here are the phenomena where the power is less than one, meaning the few biggest items get most of the weight:

intensity of wars 0.7(2); solar flare intensity 0.79(2); religious followers 0.8(1); count of word use 0.95(2)

The number is the power and the digit in parens is the uncertainty of the last digit shown. Here are the phenomena where the power is greater than one, meaning most weight goes to many small items:

telephone calls received 1.09(1); bird species sightings 1.1(2); Internet degree 1.12(9); blackouts 1.3(3); population of cities 1.37(8); terrorist attack severity 1.4(2); species per genus 1.4(2); freq. of surnames 1.5(2); protein interaction degree 2.1(3); citations to papers 2.16(6); email address books size 2.5(6); sales of books 2.7(3); papers authored 3.3(1)

For quake intensity they give power 0.64(4), but say a better fit is a different power (unspecified) and a cutoff. For net worth (of the US richest 400) they give power 1.3(1), but say a power-law doesn’t fit, though no other model tried fits better.

On catastrophic risk, I wrote in ’07:

We should worry more about disasters with lower powers, such as forest fires (area power of 0.66), hurricanes (dollar loss power of 0.98, death power of 0.58), earthquakes (energy power of 1, dollar loss and death powers of 0.41), wars (death power of 0.41), and plagues (death power of 0.26 for Whooping Cough and Measles).

So the above study suggests we worry most about wars, quakes, religions, and solar flares. I hadn’t been worried about solar flares so much before; now I am. On city inequality, I think I trust that other paper more.

Added 4p: Cosma Shalizi says:

In ten of the twelve cases we looked at, the only way to save the idea of a power-law at all is to include this exponential cut-off. But that exponentially-shrinking factor is precisely what squelches the WTF, X IS ELEVENTY TIMES LARGER THAN EVER! THE BIG ONE IS IN OUR BASE KILLING OUR DOODZ!!!!1!! mega-events.

I’m happy to admit that worse case fears are reduced by the fact that <1 power law data tend to be better fit by a tail cutoff. Good news! I don’t want to believe in disaster, but I do think we must consider that possibility.

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Housing Envy

By Robin Hanson · February 10, 2012 10:35 am · Comments (19)

Envy is real, but people claim to care more than they do about the size of their neighbor’s houses:

Unlike much of the stated preference literature, the results of this paper indicate that a increase in absolute house size is valued more than an increase in relative house size, suggesting that individuals value their absolute well-being more than their relative status if all parties are handed an equal increase. More specically, for the case of Columbus, the willingness to pay for an increase in own house size by 100 square feet from the mean is found to be $1,103 while the willingness to pay for a decrease in neighbor house size by 100 square feet from the mean is $400. (more)

Since envy looks ugly, why do people do out of their way to appear more envious than they are? Most likely because opposing wealth inequality is an ancient forager norm.

Note that this level of envy could justify taxing house size relative to some other category of consumption where envy is weaker, if such categories could be identified.

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Inequality Market Failure?

By Robin Hanson · February 5, 2012 5:20 pm · Comments (92)

In ordinary talk, you often hear arguments like:

  • There aren’t enough Jazz stations – government should subsidize them.
  • Too many kids today let their pants hanging low – that should be illegal.
  • Not enough kids want to be scientists – schools should push that earlier.

But to an economist, it is not enough to note that you do or don’t like something, to justify a policy to encourage or discourage it. We instead hold ourselves to a higher analysis standard – is there a net market failure sufficient to justify an intervention?

Except, alas, on (national at-a-time between-family) income and wealth inequality. There, most economists think it sufficient to just note that a policy influences inequality – they rarely feel a need to identity an associated market failure. For example, Christina Romer:

A successful argument for a government manufacturing policy has to go beyond the feeling that it’s better to produce “real things” than services. … The economic rationales for a policy aimed specifically at shoring up manufacturing largely fall into three categories. None are completely convincing:

MARKET FAILURES Government intervention can be justified on efficiency grounds if the free market won’t work well. … The market can malfunction if there are positive externalities across companies. … But large clustering effects have been hard to find. … A study of the semiconductor industry found that although learning by doing was substantial, most of the rewards went to companies doing the early investing. … We need a strong manufacturing base in case of war. … But it still doesn’t follow that all manufacturing deserves special treatment. …

JOBS A key argument for encouraging manufacturing is to create jobs and reduce unemployment. Unfortunately, those effects are probably small. … Today, we face a profound shortfall of demand. That truly is a terrible market failure, and it warrants government intervention. …

INCOME DISTRIBUTION A final argument for supporting manufacturing is distributional. Manufacturing jobs are seen as one of the few sources of well-paying jobs for less-educated workers. … But that is much less true today. … If increasing income equality is the goal, it might be wiser to put money into infrastructure than to subsidize manufacturing. …

Public policy needs to go beyond sentiment and history. It should be based on hard evidence of market failures, and reliable data on the proposals’ impact on jobs and income inequality. (more; HT Tyler)

Note that she even uses market failure to justify pushing jobs. But not for income equality – that is just obviously bad. I see the same thing over and over – only economists wary of equality-promoting policies talk market failures, and then they mainly ask what they are. For example Charles Lane:

Americans may never agree on an optimal distribution of income, either morally or practically. But they probably could agree that, to the extent possible, government should limit its interventions to bona fide cases of market failure. (more)

Well, no, Americans probably don’t agree on that. But you might hope economists would. Tyler Cowen has an article where he says there are market failures in the finance sector that increase inequality, and recommends fixing them. Which of course makes sense, but we’d want to fix those problems even if they reduced inequality.

The closest I could find to a market failure argument for reducing inequality was Ian Ayres and Aaron Edlin:

The progressive reformer and eminent jurist Louis D. Brandeis once said, “We may have democracy, or we may have wealth concentrated in the hands of a few, but we cannot have both.” (more)

But that is quite a stretch – there is no evidence that wealth concentration is threatening to stop our nation from being a democracy. And it is far from obvious that not being a democracy is a market failure.

As Obama has decided to make reducing inequality a central issue in his reelection campaign, we are going to hear a lot about it between now and November, including from economists. Could economists who support policies to reduce inequality please identify their market failure arguments?!  Why lower our usual standards for this topic?

(I argued here that a poverty insurance market failure seems implausible.)

Added 2p: In case it is not clear, this post is directed to economists, in their role as economists. I’m not saying market failure is the only consideration anyone uses to decide policy, but I am suggesting that it is the main consideration that economists use in their role as holders of economic expertise. Economists don’t have much expert to say about whether we have too much or too little inequality, outside of their expert ability to discern and fix market failures.

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