Tag Archives: Ems

The Future Of Inequality

By Robin Hanson · January 29, 2012 10:35 pm · Comments (11)

A few (3.6) years ago I wrote about the inequality over time induced by the big transitions, such as from primates to foragers to farmers to industry:

Advantages do accrue to early adopters of new growth modes, but these gains seem to have gotten smaller with each new [transition]. … 1. The number of generations per growth doubling time has decreased. … 2. … As we get better at sharing info in other ways, the first insight-holders displace others less. 3. Independent competitors can more easily displace each another than interdependent ones.

Earlier today I wrote about the inequality at each point in time, in the eras between transitions:

The number of species per genera and individuals per families has long declined with size as a tail power of two. After the farming revolution, cities and nations could have correlated internal successes and larger feasible sizes, giving a thicker tail of big items. In the industry era, firms could also get very large. Today, nations, cities, and firms are all distributed with a tail power of one, above threshold scales of (three) million, thousand, and one, thresholds that have been rising with time.

So, the unequal success that comes from some moving sooner in a big transition between growth eras has declined in more recent transitions. Yet the within-era inequality at a moment in time between groups like nations, cities, and firms has increased over time. As larger groups have become feasible, with more internal correlation in their success, the high tails of very large groups has gotten thicker, until they are now Zipf distributed evenly across many size scales. And in such Zipf distributions, typical group size increases with the both minimum efficient scale and total population, both of which have been increasing.

“But that is not all, no that is not all!” (Said the Cat in the Hat.) Continue reading "The Future Of Inequality" »

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Future Wealth Inequity

By Robin Hanson · January 13, 2012 11:00 pm · Comments (22)

My last two posts described inequality in firm and city sizes, and in individual wealth. Today, firms and cities are quite unequal, following a Zipf distribution, with a tail power near one (giving a very thick tail.) Individual wealth is a bit more equal, with a bigger power of ~1.4 (and hence a thinner tail).

This distribution of firms and cities seems to result from their being tolerably effective across a wide range of sizes, having long unequal lifetimes, having little net local growth, and holding a roughly fixed total number of people. In contrast, individuals have more equal lifespans, are psychologically inclined to spend more as they get richer, and have spending habits that correlate only weakly across generations. (“Rags to rags in three generations.”)

How might these change in the future? In the em era, I expect firm distributions to stay similar, but expect city and individual wealth distributions to change. I’ve talked before about how I suspect strong gains to em concentration, as they suffer less from travel congestion, leading perhaps to most being in a few dense cities. In this post, let me talk about em wealth.

Since em lifespans should be limited mainly by em wealth, em lifetimes can vary a lot more than human lifetimes, and ems can have more long-term spending consistency. While some ems will spend their wealth on more copies, others will hoard their wealth. Some may even manage to consistently reinvest most of their wealth via something like a Kelly criteria. This seems likely to make future em wealth evolution more akin to today’s firm and city evolution. I thus expect a near Zipf distribution for the high tail of em wealth.

This change in tail power should make em wealth distributions more unequal. Under a tail power of ~1.4, today’s richest person has about $75B, which is about 0.04% of the world’s $200T wealth. Under a power of ~1, the richest person might be about a hundred times richer, holding ~4% of the world’s wealth, or $7.5T.

Since a Zipf distribution has an unbounded expected value, its inequality also depends on the total population size (which follows it). The following table shows this dependence:

The “% of Richest” column says what fraction of the total wealth is held by the one richest person. The “MidW %” column shows the (smallest) fraction of the population that holds half of the total wealth. And the “MidW/ave” column shows how much richer is the mid-wealth person (for whom half of all wealth is held by richer folks) than the average person.

For a Zipf wealth distribution, as the population gets larger wealth gets more concentrated. Even so, the very richest person holds a smaller fraction of the total wealth. The same should apply to firms and cities if they retain a Zipf distribution — the firm and cities that hold most people will get larger, even though the largest firm or city would be a smaller fraction of the total.

In sum, as the population gets larger, I expect firms and cities to get larger.  And for “immortal” ems, I also expect a more unequal distribution of wealth. Even so, as population increases the very largest firms, cities, and rich folks should hold smaller fractions of their respective totals.

Added 11p 14Jan: This post has now been up for a whole day, with zero comments and one vote. Which has to be some sort of record for reader disinterest. This is especially noteworthy, given that I’m especially proud of this post, culminating several days work trying to understand something important about the future. Alas that I  sometimes bore readers, but I’m writing this blog mainly for me, so I’ll continue to write about what most interests me, even if past responses suggest readers won’t be as interested.

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Hurry Or Delay Ems?

By Robin Hanson · December 17, 2011 9:10 pm · Comments (57)

My best guess for the next big enormous thing, on the scale of the arrival of humans, farming, or industry, is the arrival of whole brain emulations, or “ems.” This raises the obvious question of whether we should try to hurry or delay the techs that would enable this change.

I see seven relevant considerations:

  1. Some think subsistence-wage ems an abomination, and so prefer to delay or prevent them. Conversely, others think that vast em numbers times lives worth living makes the em world a good well worth hurrying.
  2. Some want to delay the em transition, to give more time for its serious consideration. Others want visible em efforts to start sooner, fearing that serious consideration won’t start before then, and expect an earlier start to give a better total discussion. Still others think that, as with nanotech, early public anticipation of such events tends to make them go worse.
  3. The richer and more capable our civilization gets, the lower seem its chance of being extinguished by most disasters. Ems would make us richer faster, and ems survive biological disaster especially well.
  4. During the em transition our civilization is especially vulnerable to collapse, or to a central power grab. This transition is less disruptive when the last tech to mature is computing power, and most disruptive when that last tech is cell-modeling. This argues for hurrying scan and cell-model tech, relative to computing tech.
  5. Many fear that a single self-improving AI will suddenly grow vastly in power and take over the world. Some want to delay this event until they see how to pre-provably control such an AI. So such folks want to delay most other AI tech advances, including ems.
  6. Assuming pre-provable control is infeasible, on-the-fly control seems better when the people controlling are many and fast relative to the controlled AI. Since ems can be much faster and numerous than humans, this argues for hurrying ems.
  7. Great filter and anthropic selection considerations greatly raise our estimates of existential risks that could leave the universe empty. These do not much raise AI risk estimates, however.

On #1, I confidently estimate em lives to be numerous and worth living. On #2, I weakly estimate little benefit from delay or early publicity. Points #3,4 are the strongest I think, especially #4, and both argue for speedup. Since I think a single machine suddenly taking over the world is pretty unlikely, I give #5,6 less weight, especially when taking #7 into account. So on net I favor hurrying em cell-modeling tech most, em scan tech less, and weakly favor delaying em computing tech.

Added 11a: More considerations from the comments:

  1. Future people may evolve to differ from us via competition and changed circumstances. Some hope Earth will soon collectively organize to regulate to prevent such change, and so want to minimize change and competition before then. Since ems give more faster change, they prefer to delay ems.
  2. It seems humans can live on as ems, and non-poor ems need never die. Not dying is good, suggesting we hurry ems. Conversely, if uploading really kills humans, perhaps we should delay ems.
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Em City By Combo Auction

By Robin Hanson · December 1, 2011 3:00 pm · Comments (13)

Yesterday I outlined how combinatorial auctions could help our cities better coordinate their land use and utility capacity, without granting great discretion to a central power. But I ended with:

It would be very hard to get agreement to change to this system from today’s system of property rights and regulatory restrictions. I despair of it happening in our comfortable and change-averse cities. So we might have to wait until a big disruption creates lots of other change. (more)

Two years ago I pointed to a big-enough future disruption:

Rich stable nations … feel little inclination to consider big disruptive changes. … This frustrates rich-nation would-be-rebels like me who see our business, legal, political, etc. institutions as far from optimal. … If you long to say “come the revolution,” you might wait three to fifteen decades for the “em rev“, the whole brain emulation revolution. …

Rapid [em] growth will require huge rapid changes in economic organization, and supporting changes to business, legal, and political institutions. … Locations vying to be one of those [first em] centers may be open to big institutional change. … So if you have a favorite radical change you’d like the world to consider, you might give some thought to how your change could support a local em rev. (more)

The first em cities may be especially open to change regarding how cities are run. How might combinatorial auctions help them?

Here are my best guesses about (mid-em-era) em cities. City centers would mainly house computers, mostly running brains, and supporting infrastructure, e.g., power, cooling, structural support, part swapping paths, security, leakage containment, etc.

City centers would mostly house ems in virtual bodies doing office work, meeting often with other city workers. In most meetings, brains would stay put and just send signals; physical movement would be much rarer. Em minds would be sped-up relative to human minds as far as possible, until doubling an em’s mental speed much more than doubled its computing costs.

Outside of city centers there would be more ems in physical bodies, mostly small, helping with physical activities such as mining, harvesting, manufacturing, transportation, dumping, etc. Air cooling in the periphery would give way to water cooling closer in, and perhaps molten salt cooling very close.

All this would put a huge premium on inner city computer speed, density, and bandwidth. Cities would be very 3D, and city center computers would likely have very small physical structures generating lots of heat, making cooling crucial. Also important would be power sources, and physical paths for the replacement of devices and parts.

Today big computing centers are centrally planned, mostly with uniform parts and regular structures. But this level or coordination is may be infeasible for large cities, where diverse organizations make coordination expensive and change hodge-podge. In such a context, combinatorial auction might help improve coordination.

In am em city combinatorial auction, bids for locations could specify:

  1. spatial volume, shape, and orientation
  2. part swapping portal locations and sizes
  3. line of sight to outside, or to specific parties
  4. surface temperature and chemical corrosively limits
  5. amount and form of power and cooling, with price limits
  6. specific chemicals piped in, fluid garbage piped out
  7. communication distance from other particular residents
  8. time delay and expense to move hardware out and in
  9. support force tensors (including weight) get, support can give
  10. max stress-strain to support during earthquake
  11. limits on incoming, outgoing vibration distributions
  12. chances of incoming, limits on outgoing, leakage
  13. chance of explosive destruction, correlation with distant backups
  14. legal rules covering disputes with neighbors
  15. time commitments on each of these, and penalties for violations

As with cities today, winning allocations would say who gets what spaces with what supporting utilities, limits, etc. Competitive utility suppliers could also bid their prices to use particular spaces to supply particular utility amounts to particular locations. and futures markets about future winning bids might help estimate opportunity costs of commitment. Auction revenue could pay for utility fixed costs and repay city investors, and futarchy might choose the basic auction rules.

Yes, there’s a lot we don’t know about the future, and I could get some things wrong here. Even so, it seems worth thinking about what the future might be like, and when big institutional changes might be feasible.

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Kurzweil Rejects Ems

By Robin Hanson · October 23, 2011 3:00 pm · Comments (2)

I posted recently on Allen & Greaves criticizing “the whole brain emulation argument that we can simulate a brain without understanding it.” Ray Kurzweil responds that while he is far more optimistic on AI progress, he doesn’t believe in emulation without understanding either:

Allen mischaracterizes my proposal to learn about the brain from scanning the brain to understand its fine structure. It is not my proposal to simulate an entire brain “bottom up” without understanding the information processing functions. We do need to understand in detail how individual types of neurons work, and then gather information about how functional modules are connected. The functional methods that are derived from this type of analysis can then guide the development of intelligent systems. Basically, we are looking for biologically inspired methods that can accelerate work in AI.

It makes sense that since Kurzweil is so optimistic about rapid progress in so many technologies, such as life extension, he’d be optimistic about rapid progress in modeling the higher level organization of brains. Ems seem more likely to pessimists like myself — although we think emulation should be possible with far less than quantum chemistry detail, since the brain is a robust signal processing system, we estimate that the rate of progress to date suggests a long slow road to understanding brain organization.

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The Future Of Cities

By Robin Hanson · October 18, 2011 11:10 pm · Comments (20)

What sets city size? That is, what determines how many people all cluster together in an urban area? On the one hand, city size increases with feasible building height and with the gains to people and businesses from interacting closely with many others. On the other hand, city size decreases with how much space folks want, and with costs to transport people and goods within a city and from outlying regions. City size increases with more and cheaper nearby non-city economic activity.

Policy also matters; poor governance and positive externalities of density reduce city size, while being the center of government for a surrounding area increases city size. The size of big cities should be limited by the reluctance of nations to let their city activity be absorbed into big nearby foreign cities. And sunk costs and coordination failures can long delay the adaptation of city sizes and locations to changing circumstances.

In the farming era, cities held only a small fraction of the population, and so their size and locations were determined mainly by nearby farming activity. However, when most folks live in cities, then nearby non-city activity matters less, and decreasing transport costs make bigger cities more economical.

So how well have today’s city size and locations adapted to industry era tradeoffs? That is, how well do cities today trade the gains from more interaction in bigger cities for the added costs of transport and reduced personal space? While we expect optimal industry era cities to be more concentrated, i.e., fewer and larger, we also expect inertia, coordination failures, density externalities, and city mismanagement to slow the transition from an ideal farming era distribution of cities to an ideal industry era distribution. So cities today are probably too many and small. But how far off are they?

One clue – alas one that that is hard to interpret – is that today (log) city size follows a normal distribution, and (log) size changes follow a random walk. Another more informative clue is that in many large nations, a big (but not too big) fraction of the urban population is in the largest city. For example: South Korea 53%, Japan 44%, Egypt 43%, Argentina 37%, Bangladesh 34%, Philippines 28%, Mexico 24% (sources here, here). This weakly suggests that such cities might be running up against a political limit – the reluctance of neighboring nations to let these cities absorb their city activity.

How should we expect cities to change in a future em era, where trillions of human emulations live in virtual reality or in tiny android bodies? Since ems are easier to transport, require less space, and interact less with rural areas, optimal em cities should be even more concentrated than industry cities. Especially if ems learn to better subsidize density, to internalize today’s density externality. And since ems require quite different infrastructure from humans, and need large and rapid changes that most cities will initially be unwilling to allow, existing industry era cities may less constrain the size and location of em cities.

Together these suggest that em cities might be quite a bit more concentrated than our industry cities. Most ems might live within a half dozen or fewer really huge cities. Which would imply that only a half dozen nations would have substantial political power, allowing for easier global coordination.

If optimal em city concentration is really high, most ems might even live in just one biggest city. An analogy in the history of brains seems apt. Some of the first brains were spread out all over animal bodies, but then brains evolved to concentrate in one small region, to minimize signal delays within the brain.

Of course one big em city could be vulnerable to bad governance, so perhaps the biggest city would change as biggest cities became badly managed. Especially if ems had better ways (e.g. prediction markets) to coordinate their city switching activities. Creates an interesting picture of a competitive world government – at any one time most world economic activity might be under a single central city government, and yet cities might compete to offer the best world governance.

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A Theory Of Status

By Robin Hanson · October 14, 2011 8:00 am · Comments (10)

A few days ago I asked for a theory of status, to help predict how status will change in a rather different future. Today let me offer such a theory.

Here are our main clues about status:

  1. Status is a socially shared way to evaluate and rank people
  2. Status seems mostly relative; you can’t raise everyone’s status
  3. Human status has two main parts: dominance and prestige
  4. Most animals have dominance, which is who would win a pairwise conflict
  5. Prestige status seems to not exist in animals with simple social relations.
  6. Unlike other shared rankings, like sexiness or dominance, we seem unaware of what exactly prestige ranks.

So what is prestige? That is, what sort of ranking would be useful for human-like primates to track about each other, but also be something illicit, so that foragers would be reluctant to admit its true function? One obvious candidate stands out to me: one’s value as an ally in coalition politics. That is, how much better off is a typical coalition with this person as an ally, relative to not having them as an ally. This is clearly an important concept, well worth tracking. It only makes sense in groups with complex coalition politics, and foragers have norms against overtly engaging in such politics.

Since an ability to win pairwise contests is useful to coalitions, we expect dominance to add to prestige. But humans and similar primates can also add value to a coalition by having skills that make them useful associates, and by being on good terms with other good-ally-material folks. And both skills and associations also seem to make important contributions to human prestige. Note that this theory predicts that other primates with complex coalition politics, like chimps, will also have a prestige status distinct from dominance status.

If prestige is about one’s value in coalition politics, what does that predict about em prestige? Of the list I gave, items 2,5,7,12,16, should be substantially related to prestige.

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Allen & Greaves On Ems

By Robin Hanson · October 13, 2011 4:50 pm · Comments (29)

Paul Allen and Mark Greaves say the “singularity” is over a century away:

This prior need to understand the basic science of cognition is where the “singularity is near” arguments fail to persuade us. …. A fine-grained understanding of the neural structure of the brain … has not shown itself to be the kind of area in which we can make exponentially accelerating progress. … By the end of the century, we believe, we will still be wondering if the singularity is near.

But what about the whole brain emulation argument that we can simulate a brain without understanding it? They say:

For example, if we wanted to build software to simulate a bird’s ability to fly in various conditions, simply having a complete diagram of bird anatomy isn’t sufficient. To fully simulate the flight of an actual bird, we also need to know how everything functions together. In neuroscience, there is a parallel situation. Hundreds of attempts have been made (using many different organisms) to chain together simulations of different neurons along with their chemical environment. The uniform result of these attempts is that in order to create an adequate simulation of the real ongoing neural activity of an organism, you also need a vast amount of knowledge about the functional role that these neurons play, how their connection patterns evolve, how they are structured into groups to turn raw stimuli into information, and how neural information processing ultimately affects an organism’s behavior. Without this information, it has proven impossible to construct effective computer-based simulation models.

This seems confused. No doubt a detailed enough emulation of bird body motions would in fact fly. It is true that a century ago our ability to create detailed bird body simulations was far less than our ability to infer abstract principles of flight. So we abstracted, and built planes, not bird emulations. But this hardly implies that brains must be understood abstractly before they can be emulated.

Yes you need to understand a system well in order to know what details you can safely leave out and still achieve the same overall functions. But if you can afford to leave in all the details, you don’t have to understand what is safe to leave out. We apply this principle every time we play a song or movie. Since we know that a song or movie recording contains enough detail to reproduce a full sound or visual experience, we don’t have to understand a song or movie in order to be able to replay it for someone, and achieve most of the relevant artistic experience.

Projecting trends like Moore’s law suggests that our ability to simulate low level brain processes should increase by fantastic factors within a century. These factors seem plenty sufficient to model entire brains at low levels of detail. So if we have not understood brains well enough by then to know what details we can safely leave out, we should be able to reproduce their behavior via brute-force simulation of lots of raw detail.

Added 10p: As I explained in January:

We should expect brain emulation to be feasible because brains function to process signals, and the decoupling of signal dimensions from other system dimensions is central to achieving the function of a signal processor.

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What Status Ems?

By Robin Hanson · October 12, 2011 6:50 pm · Comments (16)

While many things count for status in our society, most of us have a rough idea of their relative weight, at least for common evaluations. But we understand the origins of these weights poorly. This ignorance seems especially clear when we consider how status might change in the future. For example, I’ve been pondering the scenario of a future world dominated by ems (whole brain emulations), and realize that it seems especially unclear what would count more for status among ems. Some possibilities:

  1. Pure physical size or power
  2. Impressiveness in conversation or verbal sparring
  3. How well its personality embodies the ideals of its age
  4. How mental, complex, or abstract is its job
  5. # other statusful ems this em commands or controls
  6. The accomplishments of this copy, since its last split.
  7. # other high status ems know it personally
  8. Political influence of this em in local disputes
  9. Personal em wealth
  10. Current daily wages
  11. Current daily profit, of wages minus cost to exist
  12. The status its human had in the pre-em world
  13. Total time this mind has experienced subjectively
  14. Time expected until em forced to retire/archive
  15. # active copies expected of this em at a future date
  16. # active “clan” copies, all of the same pre-em human
  17. # active copies expected of this clan at a future date
  18. The total accomplishments of the entire copy clan
  19. # other high status ems know anyone in clan
  20. Total wealth of its copy clan
  21. Total potential political influence of its copy clan

Of course if we had a good theory of status, we could use that to predict future status. For example, if status were a measure of future evolutionary success, then #15 would make sense. But if status were instead a measure of the value of an ally in local coalition politics, then #8 would make more sense.

Many of these measures (e.g., #14) could produce an abrupt change in status when a new copy is created. Do abrupt status changes make sense when others’ opinions about you haven’t changed?

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Shulman On Superorgs

By Robin Hanson · October 4, 2011 9:45 pm · Comments (15)

It has come to my attention that some think that by now I should have commented on Carl Shulman’s em paper Whole Brain Emulation and the Evolution of Superorganisms. I’ll comment now in this (long) post.

The undated paper is posted at the Singularity Institute, my ex-co-blogger Eliezer Yudkowsky’s organization dedicated to the proposition that the world will soon be ruled by a single powerful mind (with well integrated beliefs, values, and actions), so we need to quick figure out how to design values for a mind we’d like. The main argument is that someone will soon design an architecture to let an artificial mind quickly grow from seriously stupid to super wicked smart. (Yudkowsky and I debated that recently.) Shulman’s paper offers an auxiliary argument, that whole brain emulations would also quickly lead to one or a few such powerful integrated “superorganisms.”

It seems to me that Shulman actually offers two somewhat different arguments, 1) an abstract argument that future evolution generically leads to superorganisms, because their costs are generally less than their benefits, and 2) a more concrete argument, that emulations in particular have especially low costs and high benefits. Continue reading "Shulman On Superorgs" »

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