Economics of the Singularity

8/3/2019 Economics of the Singularity

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O

ur global economy would stupey a Roman

merchant as much as the Roman economy would

have conounded a caveman. But we would be sim-

ilarly amazed to see the economy that awaits our

randchildren, or I expect it to ollow a societal

discontinuity more dramatic than those brouht on by the ar icultural and industrial revolutions. The key, o course, is

technolog. A revolutionary speedup in economic rowth requires

an unprecedented and remarkable enablin tool. Machine intelli-

ence on a human level, i not hiher, would do nicely. Its arrival

could produce a sinularity—an overwhelmin departure rom

prior trends, with uneven and dizzyinly rapid chane thereater.

A uture shock to end uture shocks.

Stuffed into SkyScraperS by the billion,brainy bugbotS will be the knowledge workerSof the future by robin hanSon

Eoos OTe St

36 int • ieee Spectrum • ju ne 2008 www.SpEcTrum.iEEE.Org june 2008 • ieee Spectrum • in twww.SpEcTrum.iEEE.Org

Yes, this theory o mine is a social and

economic one, and thereore not as unail-inly accurate or testable as one in the

physical sciences. Nevertheless, social sci-

entists routinely make short-term orecasts

that hit the mark, and economists oten

oer insihtul orecasts about unprece-dented situations.

So indule me as I outline how we econ-

omists view technoloical chane. In sodoin, I hope to explain why it’s reasonable

to view past history as a series o abrupt,

seeminly unheralded transitions rom

one economic era to another, transitionsmarked by the sudden and drastic increase

in the rate o economic rowth. I will then

show why another sinularity is perhaps

just around the corner. Finally, I will out-

line its possible consequences.A complex device, like a tractor or a build-

in, can have thousands o parts, and each

part can rely on dozens o technoloies. Yet

in most cases even a spectacular ain in

the quality o one part bestows at best onlya small improvement on the whole. Keep

improvin a part in successive increments

o equal deree and you’ll et ever smallerains to the whole. This is the law o dimin-

ishin returns, and it applies not only to

devices and oranizations but to entire in-

dustries. Consider your personal computer:every couple o years its power-to-cost ratio

has doubled, and yet as you o rom one en-

eration to the next, you probably notice only

b r y a n c hr i s t i e d e s i gn

Proof #4 5/12/08 @ 11:16 am INT COLOR



a small improvement as you plu away on

your word processors and spreadsheets.

It turns out that most o these small,innovative ains come not rom research

labs but rom hands-on builders and

users. So the more a thin ets used,

the more it tends to improve. It doesn’tmatter whether that thin is a physical

device, such as a car, or a social orani-

zation, such as a corporation.

I any lare system o interactinparts tends to improve by smooth ra-

dations, then we should expect systems

o systems, with their larer number o

components and interactions, to improve

even more smoothly. By this reason-in, the world economy should improve

most smoothly o all. The world econ-

omy consists o the larest number o interactin parts o any man-made sys-

tem, and everyone not stranded on an

uncharted island contributes to the

improvements in all those parts by usinthem. Finally, in each economic era the

question o whether rowth speeds up

or slows down depends on two compet-

in actors. Deceleration typically ensues

as innovators exhaust the easy ideas—

the low-hanin ruit. But accelerationalso ensues as the economy, by ettin

larer, enables its members to explore an

ever-increasin number o innovations.

We have the tools to measure the

world’s economic product not only ortoday—it’s about US $50 trillion per year—

but also or times lon past. A ew years

ao Anus Maddison, an economic his-torian at the University o Groninen, in

the Netherlands, plotted a raph o world

economic product—basically everythin

o value produced lobally: bananas, sub-marines, maazine articles, you name it.

It shows that rom 1950 to 2003, rowth

was relatively steady. Durin that time,

despite enormous technical chane, noparticular technolog let much o a n-

erprint on the data; no short-term accel-

erations in rowth could be attributed to

this or that technoloical development.Also, Maddison’s data oer little support

or the idea that innovation and rowth

have been acceleratin recently.Now look at the data or world product

over the past 7,000 years, estimated by

Bradord DeLon, an economic historian at

the University o Caliornia, Berkeley. The

data here tell a somewhat dierent story.For most o that time, rowth proceeded at

a relatively steady exponential rate, with a

doublin o output about every 900 years.

But within the past ew centuries, some-thin dramatic happened: output bean

doublin aster and aster, approachin a

new steady doublin time o about 15 years.

That’s about 60 times as ast as it had beenin the previous seven millennia.

W

e call this transition

the Industrial Revolu-

tion, but that does notmean we understand it

well or even know pre-

cisely how and why it arose. But what-ever the Industrial Revolution was,

clearly it was an event worthy o the

name “sinularity.”

I we look urther back, we see whatappears to be at least one previous

sinularity—the transition to an econ-

omy based on ariculture. And slow as

economic rowth durin the aricul-

tural era may seem in the atermath o

the Industrial Revolution, it was actu-ally lihtnin ast compared with that o

the economic era that came beore, which

was based on huntin and atherin.

In the rouhly 2 million years our

ancestors lived as hunters and ath-erers, the population rose rom about

10 000 protohumans to about 4 million

modern humans. I, as we believe, therowth pattern durin this era was

airly steady, then the population must

have doubled about every quarter mil-

lion years, on averae. Then, beinninabout 10 000 years ao, a ew o those

4 million humans bean to settle down

and live as armers. The resultin com-

munities rew so ast that they quicklyaccounted or most o the world popula-

tion. From that time on, the armin pop-

ulation doubled about every 900 years—

some 250 times as ast as beore.Our understandin o the existence,

nature, and relevance o these transi-

tions clearly becomes more specula-tive the urther back we look in time[see sidebar, “How Many Sinularities

Have There Been?”]. There may well

have been two earlier sinularities that

started eras o this sort, althouh ourability to identiy them and weih their

relevance is very speculative. I suest

an era dened by the rowth o the brain

rom the emerence o animal li e to theirst protohumans and perhaps an ear-

lier era dened by the rowth o the u ni-

verse rom a time shortly ater the bi

ban to the rst animals.So we have perhaps ve eras durin

which the thin whose rowth is at issue—

the universe, brains, the huntin economy,

the armin economy, and the industrial

economy—doubled in size at xed inter-vals. Each era o rowth beore now, how-

ever, has eventually switched suddenly to

a new era havin a rowth rate that was between 60 and 250 times as ast. Each

switch was completed in much less time

than it had taken the previous reime to

double—rom a ew millennia or the ari-cultural revolution to a ew centuries or

the industrial one. These switches consti-

tuted sinularities.

Whatever may have been the key

innovations behind these transitions, it is

clear that they were ar more potent thansuch amiliar textbook examples o reat

innovations as re, writin, computers, or

plastics. Most innovations happen within

a iven rowth era and do not chane its basic nature, includin its basic rowth

rate. A ew exceedinly rare innovations,

however, do suddenly chane everythin.

One such innovation led to ariculture;another led to industry.

Thereore, we must admit that another

sinularity—at least the third one, and

perhaps the th, dependin on how you

count—could lie ahead. Furthermore,data on these previous apparently simi-

lar sinularities are some o the ew con-

crete uides available to what such a tran-sition miht look like. We would be ools

i we condently expected all patterns to

continue. But it strikes me as pretty ool-

ish to inore the patterns we see.I a new transition were to show the

same pattern as the past two, then rowth

would quickly speed up by between

60- and 250 -old. The world economy,which now doubles in 15 years or so, would

soon double in somewhere rom a week

to a month. I the new transition were

as radual (in power-law terms) as theIndustrial Revolution was, then within

three years o a noticeable departure

rom typical uctuations, it would beinto double annually, and within two moreyears, it miht row a mil lion-old. I the

new transition were as rapid as the ari-

cultural revolution seems to have been,

chane would be even more sudden.Thouh such rowth may seem pre-

posterous, consider that in the era o

huntin and atherin, the economy dou-

bled nine times; in the era o armin, itdoubled seven times; and in the cur-

rent era o industry, it has so ar doubled

10 times. I, or some as yet unknown

reason, the number o doublins is sim-ilar across these three eras, then we

seem already overdue or another tran-

sition. I we instead compare our era

with the era o brain rowth, which dou-

bled 16 times beore humans appeared,we would expect the next transition by

around 2075.

What innovation could possiblyinduce so abulous a speedup in economic

rowth? It is easier to say what could not.

Because o diminishin returns, no chane

that improved just one small sector o theeconomy could do the trick. In advanced

countries today, armin, minin, energ,

communications, transportation, and

construction each account or only a small

percentae o economic activity. Even so

extraordinary an innovation as radicalnanotechnolog would do no more than

dramatically lower the cost o capital or

manuacturin, which now makes up less

than 10 percent o U.S. GDP.No, the next radical jump in economic

rowth seems more likely to come rom

somethin that has a proound eect

on everythin, because it addresses theone permanent shortae in our entire

economy: human time and attention.

They are by ar the most productive

components o today’s economy. About

two-thirds o all income in the rich coun-tries is paid directly or waes, and much

o the remainin third represents indi-

rect costs o labor. (For example, corpo-rate income larely reects earlier eorts

by entrepreneurs.) So any innovation that

could replace or dramatically improve

human labor would be a very bi deal.

One of the pillars o

the modern sinularity

hypothesis in its manyorms is that intellience

is a eneral elixir, able to

cure many i not all economic ailments.

Typically, this belie is expressed in theorm o an arument that the arrival o

very intellient machines will produce

the next sinularity. Some people hopethis arrival will ollow a new Einstein,who will discover a powerul eneral

theory o intellience applicable to those

machines. Others envision an “intelli-

ence explosion” via a series o poweruldesin innovations, beinnin with one

that would make machines smart enouh

to help us quickly nd a second innova-

tion, allowin even smarter machines,and so on. A ew even imaine innova-

tions so unprecedentedly potent that a

sinle machine embodyin the rst inno-

vation could o throuh the entire inno-vation series by itsel, unnoticed, within a

week, and then take over the world.

There are many views on how intel-

lience miht arise in a machine. One

arument holds that hardware is thecritical limitin actor and predicts that

human-level machine intellience will

come soon ater we have computer hard-ware whose perormance is comparable

with that o the human brain.

Another arument ocuses on knowl-

ede as the true limitin actor. Thisview is behind several hue artiicial-

intellience database projects, includ-

in Cyc, under construction or 23 years

38 int • ieee Spectrum • june 2008 www.SpEcTrum.iEEE.Org june 2008 • ieee Spectrum • intwww.SpEcTrum.iEEE.Org

Te o eoo, oobes 15 es, o sooobe eek to ot

ExpErT ViEw:

J CsWHO HE ISSenior Research Scholar,the International Instituteor Applied Systems Analysis,in Laxenburg, Austria, andcoounder o the Kenos Circle,a Vienna-based society orexploration o the uture.Builds computer simulationso complex human systems,like the stock market,highway trac, and theinsurance industry. Author opopular books about science,both ction and nonction,including The CambridgeQuintet, a ctional account oa dinner-party conversationabout the creation o athinking machine.

SINGULARITYWILL OCCURWithin 70 years

MACHINECONSCIOUSNESSWILL OCCURQuestionable

MOORE’S LAWWILL CONTINUE FOR20 more years withcurrent technology

THOUGHTS“I think it’s scientically andphilosophically on soundooting. The only real issueor me is the time rameover which the singularitywill unold. [The singularityrepresents] the end o thesupremacy o Homo sapiens as the dominant species onplanet Earth. At that pointa new species appears, andhumans and machines willgo their separate ways, notmerge one with the other. I donot believe this necessarilyimplies a malevolentmachine takeover; rather,machines will become

increasingly uninterested inhuman afairs just as we areuninterested in the afairso ants or bees. But in myview it’s more likely thannot that the two species willcomortably and more or lesspeaceully coexist—unlesshuman interests startto interere with those othe machines.”

J ohn c a s t i

How ManySingularities HaveThere Been?

ThE TwO SOlidly dEmOnSTraTEd

stes, te t st

evotos, e t tte .

wee tee stes beoe

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te te, e eve soe

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te te eeee o s

soe 500 o es ee, te est

bs obe sze o eve

30 o es—ess t 1 eet o te

ot te o bs.

look te bk, t s t to

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o te eeee o s. St,

t s teest to ote tt te voe o

o e 14 bo-e-o vese s

bee e eoet e to

steos “k ee,” t ob

te o 3 bo es—bot 1 eet te

ot te o b s ze.

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teo s vos ot oes

tstos so be ete,

stes betee te be e

oee. Bt te o osttte

eeets, o te so tt vst es

e see ovet. —r.h.

t h e

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and now at Cycorp in Austin, Texas. Cyc

now possesses millions o pieces o com-

monsense knowlede, added mostly by

hand. Eventually, Cyc may know enouhto bein to read and assimilate all writ-

ten knowlede, and the more it knows,

the aster it should be able to learn. Soit is possible, thouh hardly inevitable,that Cyc will eventually undero a rapid

knowlede explosion.

I nd those scenarios interestin but

unlikely to come to pass anytime soon.Reardin advanced machine intelli-

ence, my uess is that our best chance

o achievin it within a century is to

put aside the attempt to understand themind, at least or now, and instead sim-

ply ocus on copyin the brain.

This approach, known as whole

brain emulation, starts with a realhuman brain, scanned in enouh detail

to see the exact location and type o each

part o each neuron, such as dendrites,

axons, and synapses. Then, usin mod-

els o how each o these neuronal com-ponents turns input sinals into output

sinals, you would construct a computer

model o this specic brain. With accu-rate enouh models and scans, the nal

simulation should have the same input-

output behavior as the oriinal brain.

It would, in a sense, be the “uploadedmind” o whoever served as the template.

Whether the emulation indeed consti-

tutes a person and whether that person

in achievement, but it is not imme-

diately obvious that it would launch a

new era o much aster rowth, withdoublin times measured in months

or less. Ater all, more and more capa-

ble machines have been replacin and

aidin humans or centuries with-out sparkin such an explosion. To

answer that objection, we’ve ot to

start with the undamentals: what eco-

nomic theory says about rowth rates.

T

o keep a modern economy

thrivin, we must accomplish

many mental tasks. Some peo-

ple (we call them enineers)have to desin new products,

systems, and services. Other people have

to build, market, transport, distribute, andmaintain them, and so on. These myriad

tasks are mostly complements, so that

doin one task better increases the value

o doin other tasks well. But or each task,humans and machines may also be substi-

tutes; it can be a wasted eort to have them

both do the same task.

The relative advantaes o humansand machines vary rom one task to the

next. Imaine a chart resemblin a top-

oraphic cross section, with the tasks

that are “most human” ormin a humanadvantae curve on the hiher round.

Here you nd chores best done by humans,

like ourmet cookin or elite hairdressin.Then there is a “shore” consistin o tasksthat humans and machines are equally

able to perorm and, beyond them an

“ocean” o tasks best done by machines.

When machines et cheaper or smarteror both, the water level rises, as it were,

and the shore moves inland.

This sea chane has two eects. First,

machines will substitute or humans bytakin over newly “ooded” tasks. Second,

doin machine tasks better complements

human tasks, raisin the value o doin

them well. Human waes may rise or all,dependin on which eect is stroner.

For example, in the 1920s, when the

mass-produced automobile came alon,

it was produced larely by machines,

with human help. So machines domi-nated that unction—the assembly o cars.

The resultin prolieration o machine-

assembled cars raised the value o relatedhuman tasks, such as desinin those

cars, because the inancial stakes were

now much hiher. Sure enouh, auto-

mobiles raised the waes o machinistsand desiners—in these cases, the com-

plementary eect dominated. At the same

time, the automobile industry lowered the

pay o saddle makers and stable hands, an

example o the substitution eect.

So ar, machines have displaced rel-atively ew human workers, and when

they have done so, they have in most

cases reatly raised the incomes o other

workers. That is, the complementaryeect has outweihed the substitution

eect—but this trend need not continue.

In our raph o machines and humans,

imaine that the ocean o machine tasksreached a wide plateau. This would

happen i, or instance, machines were

almost capable enouh to take on a vast

array o human jobs. For example, it

miht occur i machines were on the verycusp o human-level conition. In this

situation, a small additional rise in sea

level would ood that plateau and pushthe shoreline so ar inland that a hue

number o important tasks ormerly in

the human realm were now achievable

with machines. We’d expect such a wideplateau i the cheapest smart machines

were whole-brain emulations whose rel-

ative abilities on most tasks should be

close to those o human beins.In such a scenario, the economy would

start rowin much aster, or three rea-

sons. First, we could create capable

machines in much less time than it takesto breed, rear, and educate new human

workers. Bein able to make and retire

machine workers as ast as needed couldeasily double or quadruple rowth rates.

Second, the cost o computin has lon

been allin much aster than the econ-

omy has been rowin. When the work-

orce is larely composed o computers,the cost o makin workers will there-

ore all at that aster rate, with all that

this entails or economic rowth.

Third, as the economy beins rowinaster, computer usae and the resources

devoted to developin computers will

also row aster. And because innova-

tion is aster when more people use andstudy somethin, we should expect com-

puter perormance to improve even aster

than in the past.

Toether these eects seem quite

capable o producin economic doublin times much shorter than anythin

the world has ever seen. And note that

this orecast does not depend on therate at which we achieve machine intel-

lience capabilities or the rate at which

the intellience o machines increases.

Merely havin computer-like machinesable to do most important mental tasks

as well as humans do seems sufcient to

produce very rapid rowth.

An emulation o a brain could merely

do what that brain can already do,

althouh i done in suiciently power-

ul hardware, the conition miht occuraster. Still, even i all we were able to

achieve was a computer with the men-

tal powers o a particular human, thatwould be more than just interestin—it would also be incredibly useul.

Thouh it miht cost many billions o

dollars to build one such machine, the

rst copy miht cost only millions andthe millionth copy perhaps thousands

or less. Mass production could then sup-

ply what has so ar been the one actor o

production that has remained criticallyscarce throuhout human history: intel-

lient, hihly trained labor.

Okay, so miht these machines beconscious, with wills o their own, and

i so, could they be selsh, even malevo-

lent? Yes, yes, yes, and yes. More on that

later; or now, let’s et back to the eco-nomic arument.

Creatin human-level intellect

in a machine would be an astound-

5000 B.C.

W o r l d p r o d u c t ( b i l l i o n s o f 1 9 9 0 U S d o l l a r s )

Year4000 B.C.

1

10

100

1,000

10 000

100 000

2000 B.C.3000 B.C. 1000 B.C. 0 A.D. 1000 A.D. 2000

Agricultural era

Industrial eraSource: Bradford DeLong,economics professor,UniversityofCalifornia,Berkeley

Spot the

tranSition:

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40 int • ieee Spectrum • ju ne 2008 www.SpEcTrum.iEEE.Org june 2008 • ieee Spectrum • in twww.SpEcTrum.iEEE.Org

has rihts is another story, to which I

will return later.

I current trends continue, we should

have computer hardware and brainscans ast and cheap enouh to support

this scenario in a ew decades. What may

well take loner are input-output modelsin sufcient detail or every relevant typeo human neuron part. But I think those

details will accrue in time. We already

have suicient models or some types

o neuronal components, athered ateronly a modest eort. And we have no rea-

son to expect the other types to be harder.

Project Blue Brain, a joint eort by IBM

and the Ecole Polytechnique Fédéralede Lausanne, in Switzerland, has made

some impressive proress: in December

2006, the project nished mappin andmodelin the 10 000-odd neurons and

30 million synapses in a rat’s neocortical

column. Similarly impressive, in 2004 a

Stockholm University team observedrealistic behavior in a simulation o

8 million neurons and 4 billion synapses.

But we still have ar to o.

ExpErT ViEw:

t.J. rdgsWHO HE ISFounder and CEO o CypressSemiconductor Corp., in SanJose, Cali., known or hisbrash opinions about the

business world and politics.Owner o the Clos de la Techwinery and vineyards, inCaliornia, where he’s tryingto make the best Americanpinot noir.

SINGULARITYWILL OCCURNever

THOUGHTS“I don’t believe intechnological singularities.It’s like extraterrestriallie—i it were there,we would have seen itby now. However, I dobelieve in somethingthat is more powerulbecause it is real—namely,exponential learning. Anexponential unction hasthe property that its slopeis proportional to its value.

The more we know, theaster we can learn.

“Technological transitionsare required to maintainan exponential rate olearning. The rst airplaneswere certainly not asgood as well-appointedtrains in moving massescomortably, but thetransition later provedessential to maintainingour progress in humanmobility. Gene splicing is abreakthrough technologybut has not yet done (orbeen allowed to do) a lot ormankind. That will change.

“I don’t believe in the goodold days. We will be reer,more well-educated andeven smarter in the uture—but exponentially so, not asa result o some singularity.”

c y p r e s s s e mi c ond u c t or

B eto o stete “oe ” o oeveseve s te tete

t h e

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42 int • ieee Spectrum • june 2008 www.SpEcTrum.iEEE.Org june 2008 • ieee Spectrum • intwww.SpEcTrum.iEEE.Org

Life in a robot economy would

not be merely a sped-up ver-

sion o our lives today. WhenI apply basic economic theory

and some common sense to this

scenario, I conclude that humans would

probably be neither the immortal, all-powerul ods that some hope or nor the

hated and hunted prey that some ear.

Yes, robot-human wars would be

possible, but it is important to remem- ber that ew dierences between

humans ever lead to war. We do not

ear that the short will conspire to mur-

der the tall in their sleep, nor that the

riht-handed will exterminate the let-handed. Short, tall, let-handed, and

riht-handed people all trade with,

beriend, and marry one another withabandon, makin such wars almost

unthinkable. Instead, wars today hap-

pen between larely separate nations

and ethnic roups. Similarly, robotswell-interated into our economy would

be unlikely to exterminate us.

Would robots be slaves? Laws could

conceivably ban robots or only allow

robots “born” with enouh wealth to

aord a lie o leisure. But without lobaland draconian enorcement o such laws,

the vast wealth that cheap robots oer

would quickly induce a sprawlin, unruly

black market. Realistically, since modestenorcement could maintain only modest

restrictions, hue numbers o cheap (and

thus poor) robots would probably exist;

only their leal status would be in question.

Dependin on local politics, cheap robotscould be “undocumented” illeals, leal

slaves o their creators or owners, “ree”

minds rentin their bodies and servicesand subject to “eviction” or nonpayment,

or ree minds saddled with debts and sub-

ject to “repossession” or nonpayment.

The ollowin conclusions do not muchdepend on which o these cases is more

common. For example, in any o these

cases human waes would rise or all rap-

idly, dependin on the shape o the human

advantae landscape. Ater the ood o the

plateau, there miht still be some moun-tain peaks o human tasks let. Some rich

people miht still want to be served and

entertained by real human beins. So or

those jobs, human waes could rise. But i in the end the machine ocean completely

inundated all o Task-Land, then waes

would all so ar that most humans would

not, throuh their labor alone, be able tolive on them, thouh they miht work or

other reasons.

In either case, human labor would no

loner earn most income. Owners o real

estate or o businesses that build, main-tain, or supply machines would see their

wealth row at a abulous rate—about as

ast as the economy rows. Interest rateswould be similarly reat. Any small part

o this wealth should allow humans to

live comortably somewhere, even i not

as all-powerul ods.Because copyin a machine mind

would be cheap, trainin and education

would cost no more than a sotware update.

Instead o lon years to train each worker,a ew machines would be trained i ntensely,

and then many copies would be made o

the very best trainees. Presumably, stron

security would prevent bootle copies.Oranizational decision cycles

would shorten, avorin streamlined,

decentralized processes run by ast

machine minds in key positions o

authority. Fast minds could be whole- brain emulations sped up relative to

human brains. This scenario would

marinalize slow bureaucratic human

committees, reulators, and the like.Fast rowth rates would likely discour-

ae slow lon-distance transport and

encourae local production.

Some robots responsible or admin-

istration, research, law, and other coni-tive work miht live and work entirely in

virtual environments. For others, crude

calculations suest that tiny bodies aew millimeters tall, with sped-up minds

to match their aster body motions, miht

allow insectlike urban densities, with

many billions livin in the volume o acurrent skyscraper, payin astronomical

rents that would exclude most humans.

As emulations o humans, these crea-

tures would do the same sorts o thins

in their virtual realities and skyscrapers

that humans have done or hundreds o thousands o years: orm communities

and coalitions, all in love, ossip, arue,

make art, commit crimes, et work done,

innovate, and have un. Just as arminwas more alien to our human nature than

huntin and atherin, and industry was

more alien still, their world would be even

more distant rom human oriins. Buthuman nature seems exible enouh to

accommodate such chanes.

The population o smart machines

would explode even aster than the

economy. So even thouh total wealthwould increase very rapidly, wealth per

machine would all rapidly. I these smart

machines are considered “people,” thenmost people would be machines, and per-

person wealth and waes would quickly

all to machine-subsistence levels, which

would be ar below human-subsistencelevels. Salaries would probably be just

hih enouh to cover the rent on a tiny

body, a ew cubic centimeters o space, the

odd spare part, a ew watts o energ andheat dumpin, and a Net connection.

While copyin would make robot

immortality easible in principle, ew

robots would be able to aord it. Andwhen reproduction via copyin domi-

nates, ew robots would be able to aord

robot versions o human children.While whole-brain-emulation robotswould be copies o particular humans,

we should expect vast inequality in copy

rates. Investors who paid the hih costs

or scannin a human brain would care-ully select the ew humans most likely

to be lexible, cooperative, and produc-

tive workers, even while livin a short,

hardscrabble, childless, and alien lie inrobotic bodies or virtual ofces. Investors

who paid or copyin existin machine

minds would select robots with a track

record o achievin this ideal. As a result,there would be lare rst-mover advan-

taes and wi nner-take-all eects. For

example, i docile minds turned out to be

the most productive, then the robot world

miht consist mainly o trillions o copieseach o a ew very docile human minds.

In this case, the meek would indeed

inherit the Earth. o

TO PROBE FURTHER For additional

resources on reconstructing the deep economic

past, speculations on a rapid intelligenceexplosion, and the likely effects of machine

intelligence on economic growth, see http://

spectrum.ieee.org/jun08/singularityprobe.

Wes o so tt ost so ot ve o te

t h e

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Economics of the Singularity