the lights in the tunnel
TRANSCRIPT
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THE LIGHTS IN
THE TUNNEL
AUTOMATION,ACCELERATINGTECHNOLOGYANDTHEECONOMYOFTHEFUTURE
MartinFord
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Copyright2009byMartinR.FordAllRightsReserved,includingtherightofreproductioninwholeorinpartinanyform.
PublishedintheUnitedStatesbyAcculantPublishing.LibraryofCongressCataloging-in-PublicationDataFord,MartinR.TheLightsintheTunnel:Automation,AcceleratingTechnologyand
theEconomyoftheFuture/MartinFordp.cm.IncludesbibliographicalreferencesISBN-101-4486-5981-7ISBN-13978-1-4486-5981-41.EconomicsFutureTrends2.EconomicsImpactofAdvancedTechnologyon3.ArtificialIntelligenceandRobotics4.ComputerTechnologyandCivilization5.TechnologicalUnemploymentI.Title
This book is available for purchase or download inpaper and electronic formats at:www.TheLightsintheTunnel.com
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CONTENTS
Introduction 1
Chapter 1: The Tunnel 7
The Mass Market 10
Visualizing the Mass Market 11
Automation Comes to the Tunnel 17
A Reality Check 21
Summarizing 24
Chapter 2: Acceleration 27
The Rich Get Richer 28
World Computational Capability 39
Grid and Cloud Computing 41
Meltdown 43
Diminishing Returns 47
Offshoring and Drive-Through Banking 54
Short Lived Jobs 57
Traditional Jobs: The Average Lights in the Tunnel 58
A Tale of Two Jobs 63
Software Jobs and Artificial Intelligence 67
Automation, Offshoring and Small Business 74
Hardware Jobs and Robotics 75
Interface Jobs 80
The Next Killer App 81
Military Robotics 85
Robotics and Offshoring 86
Nanotechnology and its Impact on Employment 87The Future of College Education 90
Econometrics: Looking Backward 93
The Luddite Fallacy 95
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A More Ambitious View of Future
Technological Progress: The Singularity 100
A War on Technology 103
Chapter 3: Danger 107
The Predictive Nature of Markets 107
The 2008-2009 Recession 110
Offshoring and Factory Migration 113
Reconsidering Conventional Views about the Future 115
The China Fallacy 117
The Future of Manufacturing 124
India and Offshoring 127
Economic and National Security Implications
for the United States 128
Solutions 131
Labor and Capital Intensive Industries:
The Tipping Point 131
The Average Worker and the Average Machine 135
Capital Intensive Industries are Free Riders 138
The Problem with Payroll Taxes 140
The Workerless Payroll Tax 142
Progressive Wage Deductions 144
Defeating the Lobbyists 146A More Conventional View of the Future 149
The Risk of Inaction 152
Chapter 4: Transition 156
The Basis of the Free Market Economy: Incentives 158
Preserving the Market 159
Recapturing Wages 162Positive Aspects of Jobs 168
The Power of Inequality 169
Where the Free Market Fails: Externalities 170
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Contents / vii
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Creating a Virtual Job 172
Smoothing the Business Cycle and Reducing
Economic Risk 179The Market Economy of the Future 180
An International View 183
Transitioning to the New Model 185
Keynesian Grandchildren 189
Transition in the Tunnel 192
Chapter 5: The Green Light 194
Attacking Poverty 196
Fundamental Economic Constraints 201
Removing the Constraints 202
The Evolution toward Consumption 204
The Green Light 207
Appendix / Final Thoughts 209
Are the ideas presented in this book WRONG?
(Opposing arguments with responses) 210
Two Questions Worth Thinking About 223
Where are we now? Four Possible Cases 224
The Next 10-20 years: Some Indicators to Watch for 227
Outsmarting Marx 237The Technology Paradox 239
Machine Intelligence and the Turing Test 241
About / Contacting the Author 246 Notes
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INTRODUCTION
Likemostpeople, Ihavebeengivinga lotof thoughttotheeconomicsituationasthemostseriouscrisissincetheGreatDepressionhascontinuedtounfold.SinceIdevel-opsoftwareandrunahigh techbusiness,Ialsospendagreat deal of time thinking about computer technology,
andsoIbegantofocusonhoweconomicsandtechnolo-gy intertwine. The current crisis has been perceived asprimarilyfinancialinorigin,butisitpossiblethateverad-vancingtechnologyisanunseenforcethathascontributedsignificantlytotheseverityofthedownturn?Moreimpor-tantly,what economic impactwill technologicalaccelera-
tionhaveasweanticipate recovery from thecurrent cri-sisand in the years and decades ahead?Whatwill theeconomyofthefuturelooklike?
Among people whowork in the field of computertechnology, itisfairlyroutinetospeculateaboutthelike-lihoodthatcomputerswillsomedayapproach,orpossibly
evenexceed,humanbeingsingeneralcapabilityandintel-ligence. Speaking at an industry conference in 2007,Google co-founder Larry Page said, We have somepeopleatGoogle[who]arereallytryingtobuildartificial
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intelligenceandtodoitonalargescale.Itsnotasfaroffaspeople think.1 RayKurzweil, awell-known inventor,
author and futurist, states quite categorically that he ex-pects computers to become at least as intelligent ashu-mansbytheyear2029.2Whileotherexpertsarefarmoreconservative about the prospect for machines that canachievegenuineintelligence, therecanbelittledoubtthatcomputers and robots are going to becomedramatically
more capable and flexible in the coming years and dec-ades.
What is the likely economic impact ofmachines orcomputersthatbegintocatchupwithandmaybeevensurpassthe average persons capability to do a typicaljob?Clearly,theemploymentmarketwouldbeoneofthe
firstareastofeel that influence.Putyourself in theposi-tionofabusinessownerandthinkofalltheproblemsthatare associated with human employees: vacation, safetyrules, sick time, payroll taxes, poor perfor-mancematernityleave.Ifanaffordablemachinecandonearly any routine job as well as a humanworker, thenwhatbusinessmanagerinhisorherrightmindwouldhireaworker?
Even if computers never become truly intelligent,surelymachinesare likely tobecomefarmorecapable intermsoftheirabilitytoperformarelativelynarrowrangeof tasks. The reality is that a substantial fraction of theroutine, specialized jobs held by average people
including many peoplewith college degreessimply donotreallyrequirethe full intellectualbreadthof ahumanbeing.This is the reason thata lotof jobsareboring. If
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computerscan alreadybeat thebestchessplayers in theworld,isntitlikelythattheywillalsosoonbeabletoper-
formmany routine jobs? In fact, I think there are goodreasons to expect thatmachinesmay begin to approachthismore specialized levelof intelligencewithinadec-adeortwo.
Sincemanyofthepeoplewhoworkinfieldslikear-tificialintelligenceandroboticsaretalkingaboutthefuture
prospectsforthesetechnologiesonafairlyregularbasis,Iassumedthatasimilardiscussionmustbegoingonamongeconomists.Surely, theeconomistsare thinkingahead. Ifmachines suddenly get smarter and start doingmany ofourjobs,thentheeconomistswillhaveaplaninplace.Atleast they will have thought about it; theyll have some
goodsuggestions.Right?Well,no.Itturnsoutthatwhiletechnologistsareac-tivelythinkingabout,andwritingbooksabout, intelligentmachines,theideathattechnologywillevertrulyreplacealargefractionofthehumanworkforceandleadtoperma-nent, structural unemployment is, for the majority ofeconomists, almost unthinkable. For mainstream econo-mists,at leastinthelongrun,technologicaladvancementalways leads tomore prosperity and more jobs. This isseen almost asaneconomic law.Anyonewhochallengesthislawofeconomicsiscalledaneo-Luddite.Thisisnotacompliment.(WelltalkaboutLudditesandtheasso-ciatedLudditefallacyinsomedetailinChapter2ofthis
book.)While most economists dismiss the question com-
pletely,thetechnicalpeopleseemtobeentirelycaughtup
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in the excitement of the technology itself and what itmightpotentiallypromise.Thereissomediscussionofthe
fact that artificial intelligencemighthaveserious impactson society,butmuchof this is focusedon the threatoftruly advanced or even sentient machines in some waytakingover.There is little attentiongiven to themoremundaneandimmediatethreatstothejobmarketandtheoverall economy. Perhaps the technologists just assume
that once the technology comes along, theeconomic is-sueswillsomehowworkthemselvesout.
Now that isanunsupportable assumption. Itwouldprobablybereasonabletoassumethattechnicalproblemswillsortthemselvesout.Technologyusuallyseemstofinda way. But economic policy and political issues? Think
back to1993.BillClintonhad justbeenelectedandhadpromised to reform the health care system. As we allknow, that effort failed. Themajor issues back in 1993wereverysimilartowhatwecontinuetofacein2009.Asthisisbeingwritten,Congressisonceagaintakinguptheissueofcomprehensivehealthcarereform.Ithastakenafull16yearstogettothispoint,andstilltheoutcomeisbynomeanscertain.
Butwhathappenedwithtechnology?In1993,hardlyanyonehadheardof the Internet: itwassomething thatpeople in government and at universities used primarilyfor work-related email. Some people had primitive cellphones. Microsoft had just introduced Windows 3.1,
whichfor the first timebroughtausablegraphical inter-face to IBM PC-compatible computers. The evidence isprettyclear:aracebetweentechnologyandourabilityto
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reformourpoliticalandeconomicsystemsisreallynoraceatall.Soifwecanforeseethattechnologyislikelytohave
ahighlydisruptiveimpactonoureconomyinthecomingyears and decades, thenwe really need to start thinkingaboutthatwellinadvance.
Thedisintegrationof theSovietUnionin1991dem-onstratedquiteconclusivelythatthereisnogoodalterna-tive to the freemarket system.Other economic systems
simplycannotcompete.Infact,itsprobablyreasonabletosay that the free market economy is one of mankindsgreatest inventionsranking right up there with thewheel.Thewealthandprogressthatweenjoyintheindu-strializedworldwouldnothavecomeintobeingwithouttheunderlyinglogicofcapitalism.Historically,technology
andthemarketeconomyhaveworkedtogethertomakeusallmorewealthy.Will this alwaysbe true? Is it simply amatterofleavingthesystemwehaveinplace?
Therealityisthatthefreemarketeconomy,asweun-derstandittoday,simplycannotworkwithoutaviablela-bor market. Jobs are the primary mechanism throughwhichincomeand,therefore,purchasingpowerisdis-tributedtothepeoplewhoconsumeeverythingtheecon-omy produces. If at some point,machines are likely topermanentlytakeoveragreatdealof theworknowper-formedbyhumanbeings,thenthatwillbeathreattothevery foundation of our economic system. This is notsomethingthatwilljustworkitselfout.Thisissomething
that we need to begin thinking aboutand that is theprimarysubjectofthisbook.
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Onceyouidentifyandbegin tothinkabouttheeco-nomic ramificationsofadvancing technology, itbecomes
clearthatthesetrendsarealreadywellestablishedandmayevenunderlie thecurrent crisis to a significant extent. Ifyou make some very logical, and even conservative, as-sumptionsaboutwheretechnologyislikelyto leadinthecoming years, much of the conventional wisdom aboutwhat the futurewilllook likebecomesunsupportable. In
particular, important trends such as globalization simplymaynotplayoutinthewaywehavebeenledtoexpect.Ifwedonotrecognizetheseissuesandadapttothechangestheyimply,itwillbeverydifficultperhapsimpossibleto achieve a sustainable recovery that will lead to long-termprosperityintheyearsanddecadestocome.
Aswewillsee,technologyisnotjustadvancinggrad-ually: it isaccelerating.Asaresult, the impactmaycomelongbeforeweexpect itand longbeforeweare ready.Andyet,thisissueissimplynotontheradar.Ifafterread-ing this book, youare concerned about the issues raisedhere,thenIhopeyouwillconsiderspeakingout.Perhapsif enough people start to discuss these issues, even theeconomistswilltakenotice.
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Chapter 1
THE TUNNEL
What if technologyprogressesto thepointwherea sub-stantialfractionofthejobsnowperformedbypeopleareinsteadperformedautonomouslybymachinesorcomput-
ers?Isthatlikely,orevenpossible?Andif itis,whataretheimplicationsforoureconomy?Inthisbook,wearegoingtoexplorewhatincreasing
technologicaladvancement, andinparticularjobautoma-tion,couldmeantotheeconomiesofdevelopedcountriesliketheUnitedStatesandalsototheworldeconomyasawhole.Todothis,wearegoingtostartbycreatinganim-
aginary simulation (or mental video game) that shouldprovidesomeveryusefulinsightintowhatwecanexpectinthefuture.
Aswe all know, in recentyears the practice of off-shoring,oroutsourcingjobstocountrieslikeIndiawherewagesarelower,hasattractedagreatdealofcontroversy.
Many people in a variety of jobs and professions in theU.S. and other developed countries are now very con-cernedthattheirjobsmighteventuallybemovedoverseas.
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Whileoffshoringseemstogetmostoftheattentionatthemoment, we also know that automationthe complete
replacementofhumanjobsbymachinescontinuestogooninavarietyofindustries.
Therearecertainconventionalviewsthatmostofusacceptregardingthesepractices.Forexample,wearetoldthatalthoughautomationandoffshoringmayresultinsig-nificant job losses in certain industries, types of jobs, or
geographicregions,thisispartof thenormalfunctioningofthefreemarketeconomy.Asjobsareeliminatedinonearea,economicgrowthandinnovationcreatenewoppor-tunities.Asaresult,newproductsandservicesaredevel-oped,newbusinessesariseandnewjobsarecreated.
We also know that practices like the offshoring of
jobs and the relocation of manufacturing to low wagecountries like China are creating new opportunities forworkers in those countries. As a result, a massive newmiddle class in being created. As those newly wealthypeople enter theworldmarket, they createdramaticnewworldwide demand for consumer products and services.Businessesincountriesthroughouttheworldwillthusen-joyaccesstonewmarkets,andasaresult,newjobswillbecreatedeverywhere.Inshort,thegeneralbeliefisthatthetrends toward globalization and automation may createtemporary displacements and pockets of unemployment,butultimately,technologicalprogresscreatesnewjobsandmakesallofusmorewealthy.
Inthischapter,wearegoingtostartoffbycreatingamentalsimulationthat rejects theseconventionalwisdoms.Weareinsteadgoingtomakethefollowingassumption:
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Atsomepointinthefutureitmightbemanyyearsordecadesfromnowmachineswillbeabletodothejobsofalargepercentageofthe
averagepeopleinourpopulation,andthesepeoplewillnotbeabletofindnewjobs.
Many people might disagree with this assumption;theymayfeelstronglythatinoureconomy,newjobswillalways be created. Lets leave that aside for themoment;welldiscussitingreatdetailinthenextchapter.Fornow,
lets justgoaheadanduse thisassumption.After all, itsonlyasimulation.
Who are theseaverage peoplewhose jobswearegoingto simulateaway?Wesimplymeanthebulkof theworkingpeopleinourpopulation.Letssayatleast50 to60percentoftheemployedpopulation.Thesearejusttyp-
icalpeopledoingtypicaljobs.IntheUnitedStates,about28percent3 of the adultpopulationhasa collegedegree.Somanyoftheseaveragepeoplemayhavegonetocollegeorevengraduateschool,butmosthavenot.Theyarethepeoplewhodrivetrucks,fixcars,andworkindepartmentstores,supermarketsandalltypesofofficesandfactories.
Theyprobablyarenotneurosurgeons,andtheymostlikelydonothaveaPhDfromMIT.Theyworkontheloadingdock, sell insurance or real estate or laptop computers,work in customer service, or accounting, in a variety ofsmallbusinessesoratthepostoffice.Theyarewhatweallthinkofasregularpeople.
Soourassumptionisgoingtobethat,atsomepointdown the line,machines or computerswill take over agreatmanyofthesepeoplesjobs.Notallofthem,buta
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lot. Maybe 40 percent. Maybe half. The exact numberdoesntreallymatter.
We are also assuming that, although these peoplemight try very hard, they simplywill not be able to findanother job. Perhaps another job is created somewhereelseintheeconomy,butmaybethatjobrequiresveryad-vancedorspecificeducation,skillsortraining,sothatwecanthaveany reasonableexpectation that thisaverage
personcanfillthatjob.Orthenagain,maybenonewjobiscreated.Maybethenewjobjustgetsautomatedrightaway.
Beforewegetstartedwithoursimulation,letslookattheideaoftheworldmassmarket.
The Mass Market
Eachofus, ifweareluckyenough tolive inoneof theadvanced nations of theworld, enjoys access to an im-mense variety of products and services. As you walkthroughoneofthelargeconsumerelectronicsretailstores,youareconfrontedwitha seemingly limitlessnumberofdifferentproducts inavarietyofpriceranges.Similarlyifyouenteralargebookstore,youllbepresentedwithliter-ally thousandsof differentbooks,musicCDsandmovieDVDs.
Thistremendousselectionofproducts,andalsoser-vices,whichwenowtakeforgranted,isunprecedentedinhumanhistory.Neverbeforehassuchavarietybeenavail-ableandcertainlynottothetypicalpeoplewhocom-
prise themajority of the population. All these productsowetheirexistencetothemassmarket.Intodaysworld,abusiness that sellsmp3players, cellphones, laptopcom-
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puters, personal financial services, or automobiles sees apotentialmarketcomprisedoftensor,insomecases,even
hundreds of millions of potential buyers. It is this see-mingly limitless ocean of good customer prospects thatmakesveryhighvolumeproductionandmarketingpossi-ble.
Whenabusinesscreatesproductsorservicesathighvolume,itrealizeseconomiesofscale,andthat,ofcourse,
resultsinlowerprices.Inaddition,however,highvolumeproductionalsomakesitpossibleforthebusinesstoadoptstatisticalqualitycontroltechniquesandtoimproveover-all consistency and precision in the production process.The result is not just cheaper productsbut better andmorereliableproducts.
Becauseofthemassmarket,weenjoyaseeminglyin-finitevarietyofchoices,andwealsohavecometoexpectproducts and services of consistently high quality. Formostofus,thebenefitsofthemassmarkethavehadsuchadeepimpact,thatinaveryrealsense,theyhavebecomeintegrated into ourculture andnowgovern the expecta-tionsthatwehaveforthequalityofourdailylives.
Visualizing the Mass Market
So thatwe can better understand how themassmarketworks, lets now create ourmental simulation or videogame of themarket. Once we can visualize aworkingsimulation,we can return to ouroriginal question about
theimpactofautomationandseewhatmighthappen.Before we start, I should mention that in order to
keep things simple,weare thinking in termsof a single
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worldwidemassmarket. In fact, weknow that differentregions and countries actually have distinct but highly
connectedmarkets. Themarkets are currentlykept sepa-rateby things likegeographic distance, languagebarriers,incompatibilities(manyU.S.cellphoneswontworkelse-whereforexample),andculturaldifferences.However,weknowthatcontinuingforcessuchasglobalizationandtheInternethavecaused themarkets tobecomemuchmore
closely linked than in the past. For this reason, we cansafelyuseasimpleone-marketmodelforoursimulation.
*****Tovisualizethemassmarket,thinkof avasttunnel.
The tunnel is dark, but streaming though the tunnel arecountlesspointsofwhitelight.Thelightsfloatalongata
somewhatleisurelypaceliketinymovingstars.Eachlightrepresentsasingleperson(orconsumer)whoparticipatesintheworldmassmarket.
Thenumberoflightsseemslimitless,butinfacttheyrepresentonlyasmall fractionof theworldspopulation.ThelightsincludethepeopleoftheUnitedStates,Canada,
WesternEurope,Japan,Australia,NewZealand,andoth-er developednations.Also among the lights arewealthypeople from throughout theworld and the fast-growingmiddle classes in developing countries like China, India,RussiaandBrazil.All told, thereareperhapssomewherearoundabillionlightsinthetunnel.
Thebrightnessofeachlightrepresentsthepurchasingpower(ordiscretionaryincome)ofeachperson. Inordertoenter thetunnelandparticipatein themassmarket,a
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personmustmeetacertainthresholdofpurchasingpow-er.
Ifwecouldgooutsidethetunnel,wewouldfindoverfivebillionbarelyperceptiblelights.Thesedimlylitlightsrepresenttheworldspoor: theapproximately80percentof thepopulation that lives on less than ten dollars perday.4Theselightsare,ofcourse,eagertoenterthetunnel.However,theyarepreventedfromenteringuntiltheycan
achieve the necessary threshold of brightness.Nonethe-less,attheentrancetothetunnel,wecanseethataconti-nuous stream of lights suddenly begin to shine morebrightlyandarethusabletoenterthemassmarket.Aswehavesaid, theseare thegrowingmiddleclassesofChina,Indiaandothernations.Thenumberoflightsinthetun-
nelisconstantlygrowing.Aswewatchthelightsfloatpast,wenotice that thevastmajority shinewith a medium range of brightness.Thesearetheaverage(ortypical)peoplewhomakeupthemiddleclasspopulationsoftheworld.
Lookingclosely,wecanseethattherearealsoasig-nificant number of much dimmer lights. These are themarginalparticipantsinthemassmarketpeoplewhojustmeet the threshold for remaining in the tunnel. Thesepeopleeitherholdtheverylowestpayingjobs,orinmanycases,theysubsistongovernmenttransferpayments,suchaswelfareorunemployment insurance.Manyof thedimlightsstaythatwayonlyforashorttime.Theymaybeun-
employedforawhilebutthenfindanewjobandquicklybegin to shinemore brightly.Manyothers, however, arecaughtinthecycleofpovertyandremaindimindefinitely.
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Thesepeoplemustconstantlyfighttostayabovethethre-sholdof brightnessthat keepsthem in the tunnel. Some
willfail.EvenintheUnitedStates,therearepeople,suchasthehomeless,whohavebeencastoutfromthetunnel.
Finally,weseethatthereareafewernumberoflightswhichshinemuchmorebrightly thantherest.Thesearewealthypeople.Manyofthesepeoplehaveadvancededu-cationsorspecializedskillsand,asaresult,earnahighin-
come.Wecanseethatamongthesebright lightsthereisalsoarangeofbrightness.Wenoticethatthebrighterthelights, the fewer theyare innumber.At theextreme,wecanveryoccasionallyseeanintenselybrightlight,shininglikeaminiaturesun.Thesearethetrulyrichpeopleoftheworld: peoplewho through inheritance or entrepreneur-
shiporothermeanshaveacquiredvastamountsofwealth.Still,aswewatchthesceneinsidethetunnel,itistheoverwhelming number of the average lights that truly captivatesus.Wecanfeelinstinctivelythat itis theseaveragelightsthatcollectivelyrepresentthetruepowerofthemassmar-ket.
Nowletschangeourperspectivesothatweareinsidethetunnelwiththelights.Lookingaroundus,weseethatthewallsofthetunnelarealivewithacontinuousmosaicofcolorandmotion.Thetunnelwallsaretiledwiththou-sandsuponthousandsofflatpaneldisplays.Eachdisplayrunsacontinuousadvertisement foraproductorservicethat is offered for sale in themassmarket.Thesepanels
varygreatlyinsizeandarrangement.Some panels are huge and are arranged in clusters,
each advertising a specific product. These are the large
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corporations that have become household names. Al-though the large companies stand out, we can see that
hugeareasofthetunnelwallsarecoveredinapatchworkofmanythousandsofmuchsmallerpanels.Thesearetheproductsandservicesofferedbysmallbusinessesthatalsocatertothemassmarket.*
Aswecontinuetowatch thelights,wecannowseethattheyareattractedtothevariouspanels.Wewatchas
thousandsof lightssteamtowarda largeautomakerspa-nels,softlymakecontactandthenbouncebacktowardthecenterofthetunnel.Asthelightstouchthepanel,weno-ticethattheydimslightlywhilethepanelitselfpulseswithnewenergy.Newcarshavebeenpurchased,andatransferofwealthhastakenplace.
Weknowthatanaturalcycleexistswithinthetunnel.Almostinstantly,wecanseethatmanythousandsoflightsscattered randomly throughout the tunnel shine a littlemorebrightly.Thesearetheemployeesoftheautomakerbeingrefreshedwithnewlight.Anothertransferofwealthhastakenplace.Theautoworkersinturnmakepurchasesfromotherbusiness,smallandlarge,andthelightcontin-uestoparadethroughthetunnel.
We also know that behind the walls of the tunnelthere are more businesses and interconnections that wecant see.A large steel company receives payment from
*Wecanalsoimaginethatsmall, locallyorientedbusinesses(suchas
restaurants) are included in our tunnel. While these businesses ob-viouslydontcaterdirectlytotheglobalmassmarket,theyarenone-thelessintegratedintotheactivitythatoccursinthetunnel,andtheyare heavily impacted by the overall health and vitality of themassmarket.
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the automobilemanufacturer and, in turn, its employeesshinewithnewlight.
Ifwecouldwatchtheactioninthetunneloveralongperiodoftime,wewouldfindthatthetunnelisnotatallastaticplace.Wewouldnoticethatsomeof thepanelsonthewallsgraduallygrowdimmerandattract fewer lights.Insomecases,theymayreversetheirdeclineandbecomestrong again. But inmany other cases, theyweaken and
growdark.Even as this happens, however, elsewhere on the
tunnel walls, we see that new panels are appearing andgrowingstronger.Afewseemtogrowrapidlyinsizebe-foreour eyes.This is theprocessofcreative destruction.Inthemassmarket,thecollectivepurchasingdecisionsofthe
lightsdeterminewhichbusinessessucceedandthrive,andwhichonesultimatelydeclineandfail.Thisisanaturalandcyclical process. When an inefficient business fails, itscapital, resourcesandemployeeswill eventuallybetrans-ferredtoanew,strongerbusiness.Asapanelonthetun-nelwallgoesdark,thelightsthatrepresentthatcompanysworkerswillalsogrowdim.Butover time, theywillfindnewjobsandtheirlightwillberestored.
Wenowhaveaprettyclearpictureofhowthemassmarket works. We see the lights streaming toward andcontactingvariouspanels,andthen,elsewhereinthetun-nel, other lightsbrightening aswealth is cycled betweenconsumers, businesses and workers within the tunnel.
Overtime,weseepanelsdieandothernewpanelsspringup, as oldbusinesses that canno longer compete in the
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marketarereplacedwithnew,morecompetitivestart-ups,oftenincompletelynewanddifferentindustries.
Wecanalsofeelthat,ingeneral,thetotalamountoflight in thetunnel is increasing.Thisispartlydueto thenew lights constantly streaming into the tunnel, but wealsohavethesense thatasthelight iscycled throughoutthetunnel,itsintensityseemstoverygraduallyincreaseofits ownvolitionas though thevery process ofmoving
thelightaroundnaturallymakesitgrowovertime.This then is themassmarket: a natural cycle of in-
creasing light and wealth governed by the logic of themarketplace. It is theprimary engine of our freemarketeconomy.
Automation Comes to the Tunnel
Nowthatwehaveaworkingsimulationofthemassmar-ket, letsgoaheadandperformourexperimentwith jobautomation.Tokeepthingssimple,letsfirstfocusontheissueof jobsbeingtakenovercompletelybymachinesorcomputersandleavethequestionofoffshoringforlater.
*****Nowweare back in our tunnel. Very gradually,webegin to eliminate the jobsheldbymanyof theaveragelights.Asthishappens, theimpactedlightsgrowdimmerandinmanycasesdisappearcompletely.
Theautomationprocessaffects jobs throughout theworld. Indevelopedcountries, thepeoplewholosetheirjobswillusuallycontinuetoreceiveincome,atleastforatime, fromgovernmentprogramssuchasunemploymentinsurance.However,aswehaveseen,theseprogramsgen-
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erallyproduceonlyverydim lights. Inthirdworldcoun-trieswithlittleornosafetynet, theseunluckypeoplewill
likelybecastoutfromthetunnel,andtheirlightwilldis-appearentirely.
Theimpactofautomationisstillverydifficulttodis-cernamongthemultitudeof lightsinthetunnel.Weno-tice,however,thatsomeofthebrightestlightsinthetun-nel are beginning to shinewith evenmore intensity. As
jobsareeliminated,manyof thebusinesses in the tunnelbecomemoreprofitable.Someofthiswealthisthentrans-ferredtotheownersandtopexecutivesofthebusinesses.Asthisprocesscontinues,weseethebrighterlightscon-tinuetoslowlygainstrengthasmoreoftheaveragelightsgraduallydimorflickerout.Thedistributionofincomeis
becomingmoreconcentratedinthetunnel.Now, finally,webegintoseearealdifferenceinthetunnel.Itbecomesobviousthattherearefewerlightsandthatthenumberiscontinuingtodiminish.Justasthisrea-lizationstrikesus,weimmediatelyfeelthatthereisanewsenseofurgencypervadingthepanelsthatlinethewallsofthetunnel.Thepanelsbegintodancewithmoreandmoredesperatemotionandcolorastheyattempttoattract thedwindlingnumberoflights.
The businesses on the walls of the tunnel are nowsuddenly seeing significantly slower demand for theirproducts and services. This is happening even thoughmanyof thebrightestlightsinthetunnelhavecontinued
togaininstrength.Imagine that your job is to sell as many $50 cell
phones as you can in one hour. You are offered two
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doors:Behinddoor# 1sitBillGatesandWarrenBuffet,thetworichestpeopleinAmerica.Behinddoor# 2area
thousand average people. You may well be tempted tochoose the first door just so youll get tomeet Bill andWarren,butintermsofgettingyourjobdone,youwouldprobablyagreethatdoor# 2isclearlythebestchoice.Thisisbecausethedemandforthemassmarketproductsthatdriveoureconomydependmuchmoreonthenumberof
potential customers thanonthewealthof anyparticularcustomer. You are not going to be able to sell 40 cellphonestooneperson,nomatterhowwealthytheyare.
Wecannowsensethatmanyofthebusinessesinthetunnelareclearlyintrouble.Eventhoughtheyarecontin-uingtosavemoneyasautomationslowlyeliminatessome
oftheirremainingworkers,thisisnotenoughtomakeupfor the reductionin salestheyareexperiencing.Manyofthese companies are now at the pointwhere theymusttakeactiontosurvive.
Agreatdealofeachcompanysresourcesisinvestedin factories,machines and equipment and offices. Thesethings,whichaneconomistmight refer toascapital,arevery hard toquickly get rid of. For example, ifyou justboughtalotofnewautomatedmachinesforyourfactory,thenyouarestuckwiththem.Youcantjustreturnthemand get your money back if demand for your productssuddenly starts to fall. For this reason, a businesswhichseesrapidlyfallingdemandusuallyhasonlyonechoicein
ordertosurvive:cutmorejobs.Weseethis,ofcourse,aspartofthenormalbusinesscycle.Businessesroutinelylayoffworkersinbadtimesandthenrehireingoodtimes.
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Inthetunnel,wenowseethatthebusinessesarebe-ginning to cutmoreandmore jobs. They arebecoming
more desperate and, inmany cases, theymust eliminateevenkeyemployeesthattheyformerlyfeltwerecrucialtotheiroperations.Asthishappens,webegintoseesomeofthebrighterlightsinthetunnelrapidlybegintodim.
The continuing decrease in demand falls especiallyheavilyonthemanufacturingbusinesseslocatedindevel-
opingnationslikeChina.Thesebusinessesrelyonproduc-ingveryhighvolumeproducts,whichtheyexporttofirstworldnations.Theyarenowseverelycuttingjobsandtheflowofnewmiddleclasspeopleintothetunnelhasallbutstopped.
As a result of the job cuts, the lights arebecoming
evenmoresparseinthetunnel.Manyofthebusinessesarenow failing and whole regions of the tunnel walls aregrowingdark.Nowweseethatmanyoftheverybrightestlightsinthetunnelfinallyfeeltheimpactandalsobegintolosetheirlight.Theownersofthebusinessesinthetunnelareseeingmuchoftheirwealthgraduallydrainaway.
Thetunnel hasbecomea fardarker andmore stag-nant place.We sense clearly that the hopes of even theremainingbrighterlightsaregraduallyevaporatingintothenewemptinessofthetunnel.
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A Reality Check
Clearly,oursimulationdidnotturnoutwell.Perhapsourinitialassumptionaboutjobsbeingautomatedwaswrong.But, again, lets leave that for the next chapter. In themeantime,wemightwonder ifwehavemadeamistakesomewhereinthesimulation.Letsseeifwecanperformsometypeofrealitycheckonourresult.Perhapswecan
looktohistorytoseeifthereisanythinginthepastthatmightsupportwhatwesawhappeninoursimulation.
Lets leaveourtunneland travelback in timetotheyear1860. In thesouthernpartof theUnitedStates,weknowwillfindthegreatestinjusticeeverperpetratedinthehistoryofournation.Here,longbefore thenew lightof
advancedtechnologyfirstbegantoshine,menhaddiscov-eredafarmoreprimitiveandperverseformof jobauto-mation.
The injustice andmoraloutrage associatedwith sla-veryrightlyattractsnearlyallofourattention.Forthisrea-son,most of us dont have occasion to think about theoverall economic impact of slavery. At the timeAbrahamLincoln was elected president, we know that while theNorthern populations moral objection to slavery was aprimary divisive issue, there were also significant differ-ences and debate about issues relating to the differingeconomicsystemsoftheNorthandtheSouth.
TheNorthern economywasbuilt on free labor and
entrepreneurshipandtendedto spreadopportunitymoreequallythroughoutthepopulation.Incontrast,theSouth-ernstatesreliedonslave labor, andwealthwasprimarily
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concentratedinthehandsofwhiteplantationownerswhoownedmanyslaves.Oneresultof thissystemwasthat it
wasveryhardforpoorerwhitestoadvancetheirsituationbecauserelativelyfewfreelaboropportunitieswereavaila-ble.
Documentedobservationsillustratetheimpactofsla-veryontheSoutherneconomy.InherbookTeamofRivals:The Political Genius of Abraham Lincoln, Doris Kearns
Goodwin describes a journey thatWilliam Seward, whowould years later become Lincolns Secretary of State,took in 1835. Seward traveled with his family from hishomeinNewYorkStatetotheslavestateofVirginia.5AstheSewardscrossintoVirginiatheyleavebehindthebus-tling towns and cities towhich they had becomeaccus-
tomed. Instead, they travel a rough, deserted road withfewhomes,businessesortaverns.Dilapidatedshacksdotthelandscape,and theland itself seemstohavebeenas-saultedbypoverty.Duringhisjourney,Sewardobserved:Howdeeply the curseof slavery is set upon this vene-rated and storied regionof theolddominion.Of all thecountriesIhaveseenFranceonlywhoseenergieshaveforforty years beenexpended inwarandwhosepopulationhasbeenmoredecimatedbytheswordisasmuchdecayedasVirginia.6
Itseemsclearthattherearesomedefiniteparallelsbe-tweenwhatwesawinoursimulationandtheslaveecon-omy in the South. We noticed that in our tunnel, the
brightest lightsinitiallybecameevenbrighterastheaver-agelightsbegantodimandflickerout.ThisfitswellwiththefactthatmostwealthintheSouthwasconcentratedin
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thehandsofrichplantationowners,whilethemajorityofthepopulationwastrappedinpoverty.
Thereisoneimportantdiscrepancy,however.Inoursimulation, the situation continued to deteriorate untileven the brightest lights eventually began to lose theirstrength.Incontrast,slaveryintheSouthernstateslastedfor overtwohundredyears.Theplantationownerswereabletoholdontotheirwealthatleastuntilthestartofthe
CivilWarin1861.Ifoursimulationseemstoindicatethataslave(orautomation-based)economyisdestinedtoun-dergo continuing decline, how is it that the slave stateswereabletomaintainstabilityforsolong?
TheanswerliesinthefactthattheSouthwasprimari-lyanexporteconomy.Thelargeplantationsproducedraw
cotton which was then shipped to Europe and to theNorthern states where itwasmanufactured into textilesandclothing. Itwasthisconstantwealthflowinginfromtheoutside thatwasable tomaintain theeconomyovertime.
Our simulation, of course, was of the entireworldmass market, so there was obviously no export marketavailable. In the simulation, we found that across-the-boardautomationof jobseventuallyreduceddemandforproductsandservicesasthenumberoflightsinthetunneldecreased. You can imagine that, if the South had beencompletely isolated economically with no outside tradeallowed, itwould likely have followed a path of decline
similartotheonewesawinthesimulation.Infact,oneofPresidentLincolnsfirstactsafterthe
SouthernstatessecededfromtheUnionwastoimplement
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acompleteblockadeof theSouth.Theblockadebecameincreasingly effective as the yearsprogressedultimately
achieving a 95 percent reduction in Southern cotton ex-portsandwascertainlyanimportant factorin theout-comeofthewar.Bythetimethewarendedin1865,theSoutherneconomywasincompleteruin.Onecanspecu-latethatiftheblockadecouldhavebeenmaintainedwith-outanactualshootingwartakingplace,theeconomicim-
pactalonemighthaveintimeledtotheendofslavery.*
Summarizing
Both our tunnel simulation and our examination of theSouthern slave economy seem to support the idea thatoncefullautomationpenetrates thejobmarkettoasub-
stantial degree, aneconomydriven bymass-market pro-ductionmust ultimately go into decline. The reason forthis is simply that, when we consider the market as awhole, thepeoplewho relyon jobs for their incomearethesameindividualswhobuytheproductsproduced.
Anotherwayofexpressingthisistosaythatalthoughmachines may take over peoples jobs, the machinesunlesswearereallygoingtojumpintothestuffofscience
* Isitreallyreasonable todrawacomparisonbetweentheeconomiceffectsof slaveryand advancedmachineautomation? Iwould arguethat thecomparison almost certainlyunderestimates theeconomic im-pactofautonomousmachines.Becauseofitsinhumanity,slaverycar-rieswith itobviouscosts.Theseincludeboththedirectcostsofen-
slavingunwillinghumanbeingsaswellaslostproductivity.Theown-ersofmachineswould,ofcourse,seenoneofthesecosts.Inaddition,machines,whichcanoperateessentiallycontinuously,obviouslyhavethepotential to be farmoreproductive than even awilling humanworkercouldbe.
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fictiondo not participate in the market as consumers.Recallfromourexampleofsellingcellphonestothetwo
billionairesortoathousandregularpeople,thatmakingafewpeoplericherwillnotmakeupforlosingalargenum-berofpotentialcustomers.ThatmayworkforyachtsandFerrarisbutnotforthemassproducedproductsandser-vicesthatarethebackboneofoureconomy.
Attheverybeginningoftheautomationprocessthis
effectwasnotatallclear.Thefirstbusinessestoautomatesawasignificantreductionintheircostsastheycutwork-ers, while the impact on the demand for their productswasnegligibleor in fact, demandmayhaveactually in-creasedforatime,astheywereabletolowertheirprices.Asaresult,theirprofits,andthereforethewealthoftheir
topemployeesandshareholdersincreased.Thesewerethebrighterlightsinthetunnelthatinitiallybecamestronger.However,asnearlyallbusinessesinthetunnelcontinued
toautomatejobs,atsomepointthedecreaseinthenum-berof potentialcustomersbegantooutweightheadvan-tagesgainedfromautomation.Oncethishappened,busi-nesseswereforcedtocutevenmorejobs,whicheliminat-edevenmoreconsumersfromthemarketandcausedde-mandtofallstillfurther.Fromthispointon,theeconomyenteredacontinuingdownwardspiral.
Notaveryhappyending.However,westillneedtoexamineourinitialassumption.Isitreallypossiblethat,atsomepoint in the future,machines or computers could
takeoverthejobsperformedbyalargepercentageofav-erage workers without new jobs within the capability ofthesepeoplebeingcreated?Couldthatreallyhappen?
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Well lookat thatquestioninthenextchapter.Wellalso lookatsomethingcalledtheLuddite fallacywhichis
an established line of economic reasoning that stronglycontradictstheresultwesawinoursimulation.
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Chapter 2
ACCELERATION
Letsnowturntothequestionofwhetherornottheas-sumptionwemadeaboutjobsbeingautomatedinthefu-ture is a reasonable one. It might be helpful to start byturningthatassumptioninsideoutandlookingatitscon-verse.Ifyoubelievetheassumptionwemadeisincorrect,
thenyoumustbelievethat:Technology will never advance to the point where the bulk of jobs
performedbytypicalpeoplewillbeautomated. Theeconomywillal-wayscreatejobsthatarewithinthecapabilitiesofthevastmajorityofthehumanpopulation.
When you look at things this way, you might see
somecause for concern. The realproblem,of course, isthat one offendingword: never.Never is a very longtime:itisthreehundredoraevenathousandyears.Neveris,well,forever.
Tomakethingsmorereasonable,letslowerthestan-dardsomewhat.Letsthinkintermsofourownlifetimes
or the lives of our children.That shouldmakethe issuemuchmore approachable and personal. After all, surelynoneofuswouldwantsomethingdramaticallynegativeto
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happenduring the lives of ourown children, even ifwewerentaroundtoseeit.
With that standard inmind, lets just assumea rea-sonableaveragelifespanof80yearsforababyborntoday.Thatgives us the year 2089as a cutoff date. So the as-sumptionthatwewanttotestnowbecomes:
Technologywillnotadvancetothepointwherethebulkofjobsper-formed by typical people will be automated before the year 2089.
Priortothatyear,theeconomywillalwayscreatejobsthatarewithinthecapabilitiesofthevastmajorityofthehumanpopulation.
Canwebankonthat?
The Rich Get Richer
Nearlyall of ussense that ourworld ischanging rapidlyand that perhaps things seem to be speeding up.Wevebecome accustomed especially to continuous improve-ment in technology.Wenotice that the laptop computerwebuy today isdramatically faster and lighter andmorefeature-packed that the onewe bought just a few yearsago,andyetitcostsless.Ournewcellphoneissmalleror
lighter,butitdoesmore.Ashumanbeings,weare geared toward thinking in
termsof constantmotionorgradualchange.Wetendtoanalyzethingsintermsofstraightlines.Forthemostpart,thisishowthephysicalworldaroundusworks.
Weare,ofcourse,familiarwiththeconceptofaccele-
ration.Weexperienceitwhiledrivingorwhenanairplanetakesoff.Butinthecourseofourdailylives,accelerationisalmostwithout exceptionsomething that is of very
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itisourexpandingabilitytomanipulateandcommunicateinformationthat isthedrivingforcebehindthetechnical
innovationweseeallaroundusandMooresLawdoesanespeciallygoodjobofcapturingtherateofprogressinthatarena.
When something doubles at a regular pace,we saythat itgrowsgeometrically,orexponentially.*To illustratetheextraordinaryaccelerationthat this implies, imaginestart-
ingwithapennyandthendoublingtheamountyouhaveeveryday foramonth.Youbeginwithonecent;on theseconddayyouhavetwocentsandthenfourcentsonthethirdday,andsoon.
Thefirstchartonthenextpageshowsthefirstfifteendaysasourpennydoubles.Youcanseethatwestartout
very slowlyand thenbegin toaccelerate.Onday fifteen,we have about $164which is not bad at all since westartedwithonlyapenny!
Inournextchart,welookatdays15-30.Nowwevehadtogreatlyexpandthescaleofourbarchartsowecanaccommodate some very big numbers toward the end.Youcanseethatwestartwhereweleftoffwith$164,butnowthisamountissotinyagainstournewscalethatwedontevenseeavisiblebar.Wehavetowaituntilday22beforewe see a hint of progressbut still that amountrepresentsnearly21thousanddollars.
Thingsreallystarttoflyfromthere.Wepassthemil-lion-dollarmarkatday28andenduponday30withover
fivemilliondollars.Notbadforamonthswork.Ifwehad*Thesetermshaveslightlydifferenttechnicalmeanings,but forourpurposestheyareinterchangeable.
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been lucky enough tochooseamonthwith 31days forourexperiment,wewouldhavenearlyelevenmilliondol-larstoshow for it. Ifwe couldcontinuetheprocessforanother thirty days, we would have an astonishing$5,764,607,523,034,235ornearlysixquadrilliondollars!
Asyoucansee,ageometricorexponentialprogres-sionisreallytheultimatecaseoftherichgetricher.Themoreyouhave,themoreyouget,anditjustkeepsgoing.Whenwecompare thiswith themore routine thingsweencounter in life, the contrast is astonishing. Consider
economicgrowth,orperhapstheraiseyoumighthopetogetatwork;inthesethings,wearehappytoseeagainofa
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fewpercentagepoints.Can thisbe real? Isthecomputa-tionalcapabilityofcomputersreallyexpandingthatfast?
Toillustratethatthisisindeedthecase,letmeuseanexamplefrommyownexperience.In1981, IenteredtheUniversityofMichiganasafreshmanwithplanstostudycomputer engineering.Computer engineeringwas then anew discipline just introduced atMichiganand at a fewother universities.Up until then, no onehad beenquite
surethatcomputerswereimportantenoughtomerittheirownengineeringfield.
TheUniversityofMichiganhadoneofthemostad-vanced computing centers in the country. Thecomputerthen in use was a state-of-the-art mainframe machinemanufactured by the Amdahl Corporation. In my first
computerprogrammingcourse,wewereassignedthetaskofwritingandrunningaprogramusingcomputerpunchcards.7
Todothis,youfirstwenttotheuniversitybookstoreand purchased a large box of blank punch cards. Thesewere similar to, but a little longer than, standard indexcards.
Youthenwroteyourprogramusingpencilandpaper,andtookyourblankcardstoacardpunchmachineatthecomputing center. You inserted a blank card in thema-chineandentered,orkeyedin,onelinefromyourpro-gram.Asyoudidthis, themachinepunchedcorrespond-ing holes in the card.You repeated this for each line in
yourprogram. If youmadeamistake,youhad to throwtheentire card away and start over. Fora complexpro-gram,youmighthavetopunchhundredsofcards.
http://en.wikipedia.org/wiki/Instructions_per_secondhttp://news-service.stanford.edu/news/2009/january28/small-012809.htmlhttp://news-service.stanford.edu/news/2009/january28/small-012809.htmlhttp://news-service.stanford.edu/news/2009/january28/small-012809.htmlhttp://news-service.stanford.edu/news/2009/january28/small-012809.htmlhttp://en.wikipedia.org/wiki/Instructions_per_second -
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Next,beingverycarefulnottoscrambleordropthestackof cards,you took them toa card readermachine.
Youfedthestackofcardsintothemachineandyourpro-gramwasenteredintoalonglineofotherprogramswait-ingfortheattentionofthecomputer.
After a time, in some cases hours, youwent to theprintcenterandretrievedapaperprintoutof theresults.Since it isvirtually impossibletowriteaperfectprogram
the first (or usually even second) time, you had to gothrough this process several times until you found andfixedthebugsinyourprogram.
Obviously, thewaywewithinteractwithcomputershaschangeddramatically.Ihadtoincludeadescriptionofpunchcardsaboveforthebenefitofyoungerreaderswho
maynothaveseenthese.Whataboutthecomputeritself?Themainframe in useatMichigan thenwasanAmdahl470/V8.Thiswasamachinethatprobablyoccupiedasig-nificant portion of a room and cost somewhere in theneighborhoodoftwomilliondollars.
In order to compare therelativespeedsof differentcomputers, engineers have developed a measurementknownasMillionsof Instructionsper Second, orMIPS.TheMIPSratingofacomputerisabitlikethehorsepow-erratingofanengine.Whileeachcomputerhasauniquedesign,MIPSratingsgiveusausefulwaytomakeroughcomparisons.
If you imagine a software program running on a
computer to be similar to someoneplaying a tuneon apiano, theneachcomputerinstructionwouldcorrespondtoonestrikeofthepianokeys.TheAmdahlmainframeat
http://yaleglobal.yale.edu/about/pdfs/oil.pdfhttp://www.economist.com/agenda/PrinterFriendly.cfm?Story_ID=1985889http://www.businessweek.com/magazine/content/06_14/b3978116.htmhttp://www.businessweek.com/magazine/content/06_14/b3978116.htmhttp://www.economist.com/agenda/PrinterFriendly.cfm?Story_ID=1985889http://yaleglobal.yale.edu/about/pdfs/oil.pdf -
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crosoftWindows.Windows3.1,alsointroducedin1992, became an enormous commercial success
forMicrosoft. By 1999, the Intel Pentium III was rated atover1,300MIPS.Ourpianoplayerisnowgoingatovera billion keystrokes per second. This is close to200timesthespeedoftheoldAmdahl.
In2008, an IntelCore 2Extremeprocessorwas
ratedatupto59,000MIPS.Thats59billionpianokeystrokes per second and over 8000 times thespeed of our 1981-vintage $2 million Amdahlmainframe.
Obviously, things have progressed very impressivelyover the24or soyearssinceI left college.Whatweare
more interested in, however, is whatwill happen in thefuture.
WeknowfromMooresLawthatcomputersarepro-gressingatageometricorarichgetricherratewherewedoublewhatwealreadyhaveeverytwoyears.Inthefirstchapter,Iusedanexamplewherewethoughtaboutselling
cellphonestoBillGatesandWarrenBuffet.LetsdragBillbackinto thestorynowandperformanexperiment thatmightgiveusanideaof thelevelof futureprogress thatwecanexpect.
BillGatesleftHarvardin1975tomovetoNewMex-icoandfoundMicrosoftalongwithhispartnerPaulAllen.Wecanmark thatdateasbeingessentially thebeginningof thepersonalcomputerindustry.AsBillstartswork in1975, lets imaginethatweslipourmagicpenny intohispocket.Billsfocusedonotherthings,andhewontnotice.
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WelldoublethepennyeverytwoyearsandseehowmuchBillendsupwith:
The IBM PC, which uses Microsofts MS-DOSsoftware, is introduced inAugust1981. ThissetsMicrosoftonitspathtosuccess.Billnowhaseightcentsinhispocket.
InMarch1986,MicrosoftgoespublicanditsstocktradesforthefirsttimeontheNASDAQmarket.
Billhasabout45cents.10 Windows 3.1 is introduced in 1992.For the firsttime,Microsoft began tooffersomecompetitiontoApplesMacIntosh.Billnowhasabout$3.60inhispocket.
WindowsXPisintroducedin2001.Billhasabout
$82.
Letszoomforwardto2009andlookinBillspocket:about$1,300.Obviously, itsagood thingBilldidntpinhisfortunesonourmagicpenny.
ConsidereverythingthatBillGateshasaccomplishedoverhiscareer.HebuiltMicrosoftintotheworldsdomi-
nantsoftwarecompanyandhasnowretiredfromfulltimeworkatthecompanytorunhischaritablefoundation.Af-ter all that, in terms of our experiment to measure thegeometric acceleration of technology, Bill has less than1,500dollars.However,wecanalsoseethat thingshaveaccelerated quite dramatically in the years between 2001
and2009: in justeightyears,Billhasgainedover$1,200,comparedwithagainofonly$82overthe26yearsleadingupto2001.
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Weknow from the chartswe looked at earlier thatBillwilleventuallyreachthemilliondollarmark.Whatcan
wesayaboutthefuture?
In2015,Billwillhaveabout$10,500oreighttimeswhathehasin2009.
In2021,Billwillhavenearly$84,000or64timesthe2009figure.
In 2025, Billwill havealmost $336,000or about
258timeswhathehasin2009. In2031,Billbecomesamulti-millionaire.Hewillhave2.6milliondollarsor2000timeswhathehasin2009.
Looking at these numbers, we can see that unlesstechnicalprogressslowssignificantly,computersaregoingto getdramaticallymore powerful by 2031. That date isnearly60yearsbeforethecutoffdateof2089thatwesetatthebeginningofthischapter.
WhatwouldBillhavein2089?1.4quadrilliondollars.Thisisoveronetrilliontimesthe2009amountof$1,300!
Thesenumbersshouldgiveyouasenseoftheincred-
ible degree of technological acceleration we can expectoverthecomingyearsanddecades.Asfuturistandinven-tor Ray Kurzweil writes, Exponential [or geometric]growthisdeceptive.Itstartsoutalmostimperceptiblyandexplodeswithunexpectedfury.11HowconfidentcanwebethatMooresLawwillcon-
tinuetobesustainable in thecomingyearsanddecades?Evidencesuggeststhatitislikelytoholdtrueforthefore-seeable future. At some point, current technologieswill
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runintoafundamentallimitasthetransistorsoncomput-erchipsarereducedinsizeuntiltheyapproachthesizeof
individual molecules or atoms. However, by that time,completely new technologies may be available. As thisbook was being written, Stanford University announcedthatscientiststherehadmanagedtoencodethelettersSandUwithintheinterferencepatternsofquantumelec-tronwaves.12 In other words, they were able to encode
digital information within particles smaller than atoms.Advances suchas thismaywell form the foundation offuture information technologies in the area of quantumcomputing; this will take computer engineering into therealmofindividualatomsandevensubatomicparticles.Even if suchbreakthroughsdont arrive in time,and
integrated circuit fabrication technology does eventuallyhit a physical limit, it seems very likely that the focuswouldsimplyshift frombuildingfasterindividualproces-sors to instead linking large numbers of inexpensive,commoditizedprocessorstogetherinparallelarchitectures.Aswellseeinthenextsection, thisisalreadyhappeningtoasignificantdegree,butifMooresLaweventuallyrunsout of steam, parallel processing may well become theprimaryfocusforbuildingmorecapablecomputers.Even if thehistoricaldoublingpaceofMooresLaw
doessomedayprovetobeunsustainable, there isnorea-son to believe that progresswould haltor even becomelinearinnature.Ifthepacefelloffsothatdoublingtook
four years (or even longer) rather than the current twoyears, thatwould still beanexponentialprogression that
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would bring about staggering future gains in computingpower.13
Letslookatouroriginalassumptionagain:
Technologywillnotadvancetothepointwherethebulkofjobsper-formed by typical people will be automated before the year 2089.Priortothatyear,theeconomywillalwayscreatejobsthatarewithinthecapabilitiesofthevastmajorityofthehumanpopulation.
Does that seem reasonable now? But wait, theresmore.
World Computational Capability
Back in1975, itprobablywouldhavebeenquiteeasy tomakealistofeverycomputerintheworld.Primarily,wewould have found computers in government agencies,universities, and large corporations. Amanufacturer likeIBM couldprobably havegivenusa list showingwhereeachcomputerwasinstalled.Intheprecedingsection,wetalkedabouthowthepowerandspeedofcomputershasincreased. Ifwetook thatgeometricrateof increaseandjustappliedittothecomputersthatexistedin1975, that
wouldbeanincredibleexpansionofcomputationalpower.Butofcourse,weknowthatisnotwhathappened.
The number of computers in the world has also in-creased at a fantastic rate. By some estimates, there arenow over a billion personal computers in use. But itdoesntstop there.Computers in the formof embedded
microprocessorsare inourcellphones,mp3players, carengines, appliances and in countless other places. Com-putersareeverywhere.
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In fact,wemightspeculatethatboththepowerandthenumberofcomputersintheworldareincreasingata
geometricrateorat leastsomethingcloseto it.That isclearlyanincomprehensibleincreaseinourtotalabilitytomanipulate information. If you consider the number ofobsoletedevicesthathavebeenthrownawaysincethePCwasintroduced,itseasytoseethatthecomputingpowerin landfills today is many orders of magnitude beyond
whatexistedintheworldin1975.Itseemsimpossibletoimaginethatsuchanincredible
advanceinourabilitytocomputeandtoprocessinforma-tioncouldtakeplacewithoutithavingadramaticeffectongeneral technology, economicsand society in general. Infact, however, in many areas, change has not come as
quicklyasweperhapsmighthaveexpected.Cars and airplanes now incorporate computers, buttheiroveralldesignandoperationisstill,forthemostpart,whatitwasin1975.NASAmanagedtheApollomissionsandreachedthemoonwithoutaccesstomoderncompu-tingpower.Eventhespaceshuttledatesbacktotheintro-duction of the first PCs. Likewise, economists speak ofsomething called theproductivity paradox, which basicallysaysthat,atleastuntilquiterecently,theeconomyhasnotreallyshowntheproductivitygainsyoumightexpectgivenall the new computers that have been introduced intoworkplaces. The computer revolution seems, so far, tohavelargelyturneditsenergyinwardonitself,resultingin
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advancesprimarilyintheinformationandcommunicationareas.*
Ihavethefeelingthatthisstaggeringincreaseinourcomputational capability represents a pent up resourcethatispoisedtoburstoutinnewandunexpectedways.Inthefuture,wecanexpectthatmanymoretraditionaltech-nologies,and in factnearlyeveryaspectof ourlives,willchangeperhaps very rapidlyin ways that we cannot
foresee.Asexamplesofwhatwemightexpect, letslookattwothingsthathavealreadyoccurred:onethat,atleastsofar,hasbeengenerallypositive,andonethathasbeendecidedlynegative.
Grid and Cloud Computing
Gridcomputingisarapidlygrowingfieldthatfocusesonleveragingnot just thepowerof anindividualcomputer,butalsothelargenumberofsuchcomputersnowavaila-ble.Theideaistotiemanycomputerstogetherusingspe-cial software.A big computationalproblem can then bebrokendownintopiecesanddistributedacrosshundredsoreventhousandsofcomputerssothattheycanworkonit simultaneously. Grid computing has the potential tobringanunprecedentedlevelofcomputingpowertobearondifficultproblemsintheareasofscienceandengineer-ing.
Oneofthefirstandmostnotableapplicationsofgridcomputingwas in theHumanGenomeProject. This in-
* Evenmuch of biotechnology and genetics could be considered atypeof information sciencebecause it is focused oncataloging andunderstandingtheinformationinourDNA.
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ternational project began in 1990 andwas completed in2003twoyearsaheadof schedule.Theprimarygoalof
theprojectwastosequencetheentirehumanDNAmole-culeandtoidentifythe25,000orsoindividualgenesthatcompriseourgenetic code.TheprocessofdecodingourDNAmoleculeandidentifyingeachgenetookatremend-ousamountofcomputationalresources,andgridcompu-tingplayedasignificantroleinthis.
ThegeneticinformationobtainedthroughtheprojectisstoredindatabasesandcanbeaccessedbyscientistsandresearchersviatheInternet.Theresultisafantasticsourceof knowledgethatcontinuestobeanalyzedandwhichiscertain to result in innumerable future advances in thefieldsofgenetics,bio-engineeringandmedicine.
Anespecially interestingdevelopment in the fieldofgridcomputingistheideathatunusedpoweronvirtuallyanycomputerconnectedtotheInternetcanbeintegratedintoavoluntarygridanddeployedtosolvebigproblems.Mostcomputers,if left on,donothingatallduringlargeblocksof time,especiallyovernight.Theideatotiethesecomputerstogetherbyhavingtheirownersdonateunusedcomputingpowerhassprungupinanumberofplaces.
Stanford Universitysfolding@ home project is gearedtowardsolvingdifficultproblemsina specializedareaofbiochemistryknownasproteinfolding.Advancesinthisareahavethepotentialtoprovidefuturesolutionsforcan-cerandfordiseasessuchasHuntingtonsandParkinsons.
AnothermajorplayerinthisareaistheBerkeleyOpenInfra-structure forNetwork Computing (BOINC).Thisspecial soft-ware,developedat theUniversityofCalifornia,Berkeley,
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allows individuals to donate unused computer time to avarietyof scientificprojects, includingSETI (TheSearch
forExtraterrestrialIntelligence),climateprediction,cancerresearch, astrophysics, andmanyothers.The software toparticipateintheseprogramscanbedownloadedfromtheweb.*
Inthe future,wecananticipate that grid computingwill become increasingly important. In addition, it is al-
ready evolving intowhat computer scientists refer to ascloudcomputing.Essentiallythiswillamounttoanewarchitectureforleveragingthepowerofhugenumbersofcomputersonanasneededbasis:computationalcapabili-ty, togetherwithspecificapplications,willbedeliveredasthoughitwereautilitymuchlikeelectricpower.Thetrend
towardgridandcloudcomputingoffersafantasticoppor-tunitytodeployourincrediblenewcomputationalcapacityin areas thatwill undoubtedly bringpositiveadvances infields such as science and medicine. Our next example,however,isfarlessbenign.
Meltdown
Asnearly everyoneknows, thesubprimemeltdownof2007wastriggeredwhenborrowerswhodidnothavethebestcreditratingsbegantodefaultontheirmortgages.Weknow that banks and mortgage companies made theseloans in somecasesbecause of honestmiscalculation oftherisksinvolved,andinothercasesduetooutrightfraud.
With expectations driven by the housing bubble, manylendersmayhavehadtherathercallousattitudethat,even*http://folding.stanford.eduandhttp://boinc.berkeley.edu
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iftheborrowercouldnothandlethepayments,thelendercould minimize its exposure by foreclosing at a higher
price.Whatdoes thathavetodowithcomputers?Well,if
that had been the entire story, then the subprime crisiswouldhavestillbeenserious,butitwouldhavebeencon-tainedwithintheU.S.Itcertainlywouldnothavecascadedaroundtheworldandresultedintheglobalfinancialcrisis
thatoccurredin2008.Foranexplanationofwhythecrisisspreadthrough-
outtheworld,wehavetostartbackin1973.Inthatyear,anacademicpaperwaspublishedwhichcontainedama-thematical formula called the Black-Scholes Option Pricing
Model.Thisformula,forthefirsttime,gaveawaytocalcu-
late the approximate valueof a stock option. Stock op-tions,whichrepresenttherighttobuyorsellastockatagivenpriceatsomepointinthefuture,hadbeentradedonmarketsforsometime,butnooneknewhowtocalculateaprecisevalueforthem.
In the years that followed, and especiallyduring the1980s,alargenumberofpeopleoriginallytrainedasphy-sicistsormathematiciansbeganto takemuchhigherpay-ingjobsonWallStreet.Theseguys(theywerevirtuallyallmen) were referred to as quants. The quants startedworkingwith theBlack-Scholes formulaandexpanded itin newways. They turned their formulas into computerprogramsandgraduallybegantocreatenewtypesof de-
rivativesbasedonstocks,bonds,indexesandmanyothersecuritiesorcombinationsofsecurities.14
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Astheircomputersgot faster and faster, thequantswereabletodomoreandmore.Theycreatednewexotic
derivativesbasedonstrangecombinationsofthings.Theycouldmagnify the reward (and risk) of a security. Theycould invert it,soyougained if thesecurity fell invalue.Theycouldeventrytocapturetherewardifaninvestmentincreasedinvalue,buteliminatetheriskifitwentdownoratleasttheythoughttheycould.
Ashousingpricescontinuedtoclimbduringthebub-ble, the subprime loans were packaged into mortgage-backedsecuritiessothattheycouldbetradedlikebonds.Thishadbecomestandardpractice formortgages.How-ever, in addition to that, new types of derivatives werecreatedbasedonthepackagedsubprimeloans.Mostnot-
able were collateralized debt obligations (or CDOs),whichattempted to siphonoff the lowest risk loansandrepackagethemintoasecuritythatcouldbemarketedasahigh quality investment. These new derivative securitieswerethensoldtobanksandfinancialinstitutionsallovertheworld,withtheunderstandingthattheywereverylowriskinvestments.
Whenthesubprimeborrowersstarteddefaulting,thevalueof themortgage-backedsecuritiesplunged, and thederivativesdidnotworkasexpected.Inmanycasesitwasdifficultorimpossibletocalculatetheirvalue.Inaddition,financialinstitutionshadengagedinmanyothercomplexinterrelationships based on exotic derivatives that were
intendedtohelpmanagevariousrisks.Allthisledtoun-certainty thatcausedvalues to fallevenmore.Theresult
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ourability tocompute.Wecanalsocertainlyexpectthatthisdramaticallyexpandedcomputationalcapacitywillbe
focusedincreasinglyonautomatingourjobs.Laterinthischapter,welllookinmoredetailatsev-
eral specific advancing technologies andhow theymightimpact the jobmarket and theeconomy in general.Butfirst,letsnowturnfrommachinestohumanbeings.Isitpossiblethatwecansomehowoutruncomputerssowe
canallkeepourjobs?
Diminishing Returns
In1811,EnglandwasinthemidstoftheIndustrialRevo-lution. That year, a group called theLuddites formed inNottingham. The Luddites consisted of skilled textile
workerswho felt threatened by the introduction of me-chanical looms that could be operated by low-paid, un-skilledworkers.TheytooktheirnamefromamannamedNedLudwhohadreportedlydestroyedoneof thesead-vanced looms.TheLudditesprotestsgrew into outrightriotsanddestructionofmachines.TheBritishgovernmentfinallyenactedharshmeasuresandthemovementcametoan end in 1812. Since then, the word luddite has, ofcourse,evolvedintoasomewhatderogatorytermforany-oneopposed to technologicalprogressorillequipped todealwithnewtechnologies.
Economistsgenerallydismisstheideathatadvancingtechnology will ever permanently displace humans and
thereby continuously increasetheunemploymentrate. Inotherwords,mostmainstreameconomistsfullyacceptourassumption at the beginning of this chapter. (Not the
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2089 version; the never one.) Those who have raisedconcerns in more recent times are dismissed as neo-
Luddites. Economists have also formulated somethingcalledtheLuddite fallacy tohelpexplainwhytheconcernsof neo-Luddites are wrong.Well look at this in a littlemoredetaillater.
Obviously, England is now a modern country, andthe vastmajority of workers still have jobs. The British
peoplearenowfarbetteroff thantheywerein1812.SoweretheLudditeswrong?Orjusttwohundredorsoyearstooearly?
Weknowthattechnologyhasadvancedtremendouslysince1812.Whatabouthumanbeings?Haveweadvancedaswell? In termsof basic biology,weareessentiallyun-
changed. Little if any biological evolution takes place inonlytwohundredyears.Still,doesntitseemlikelythattheaverageBritishworker today is farmore capable than atypicalworkernearlytwohundredyearsago?
LetsimaginewhatlifewaslikeforanaverageEnglishperson in1812.Asitturnsout, its easy toget somein-sight into this becauseCharlesDickenswasborn in thatexactyear.Dickensdrewonhisownexperiencesandob-servationsasachildwhenhe laterwrotehisfamousno-vels.Hisdescriptionsof aharsh,poverty-strickensocietyand an environmentmade filthy by the soot from coal-burningindustryarewellknown.
InOliverTwist,Dickensdescribesthemiserablelifeof
anorphanboyduring theIndustrialRevolution.HereheexpresseshisfeelingsasthestarvingOliverisgivenscrapsofmeatthathadfirstbeenofferedtoadog:Iwishsome
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well-fed philosopher,whose blood is ice,whose heart isiron;couldhaveseenOliverTwistclutchingatthedainty
viands thedoghadneglected. Iwishhecouldhavewit-nessedthehorribleaviditywithwhichOlivertorethebitsasunderwithalltheferocityoffamine.15
Clearly, the average British worker is far better fedtoday.Weknowtheenvironmentisalsomuchcleanerandmore healthy. The literacy rate in Britain today is pur-
portedtobeashighas99percent.Itshardtoknowwhatitwasin1812,butaround50percentmightbeadecentguessandofcourse, theabilitytoreadandwritewouldhavebeenhighlyconcentratedintheupperclasses.
In 1812, there was essentially no public educationavailable in England. The government did not begin to
investsignificantlyineducationuntil1870,andattendancewas not compulsory until 1880. Obviously, the averageworkertodayisfarbettereducatedthanheorshewouldhavebeenin1812.
Givenallofthis,wecansaythat,duetodramaticim-provementsinlivingconditionsandeducation,anaverageworker today is certainlymore capable and able to per-form more complex, high-level tasks than a worker in1812.Buttherealquestionis:canweexpectthatkindofimprovementtocontinueinthefuture?
Thefollowinggraphshowswhatanaverageworkersabilitytoperformcomplextasksmightlooklikeoverthepasttwohundredorsoyears.Thegraphicisjustanintui-
tiveestimate.Itisnotbasedonanyrealdata.However,Isuspect that most people would agree with the generalshapeofthegraph,andthatisallthatreallymatters.
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Average Workers Ability to Perform Complex Tasks
Ivechosenanarbitrarypointonthegraphtoindicatetheyear1812.Afterthatyear,wecanreasonablyassumethathumancapabilitycontinuedtorisequitesteeplyuntilwereachmodern times. The steeppart of thegraph re-
flectsdramatic improvements toouroveralllivingcondi-tionsintheworldsmoreadvancedcountries:
Vastlyimprovednutrition,publichealth,andenvi-ronmental regulations have allowed us to remainrelativelyfreefromdiseaseandreachourfullbio-logicalpotential.
Investmentinliteracyandinprimaryandsecond-aryeducation,aswellasaccesstocollegeandad-vancededucationforsomeworkers,hasgreatlyin-creasedoverallcapability.
Agenerally richer andmore varied existence, in-cludingeasyaccesstobooks,media,newtechnol-
ogiesand the ability to travel long distances, hasprobably had a positive impact on our ability tocomprehendanddealwithcomplexissues.
Luddites riot - 1812
Time
Average
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Capability
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Thedegreeofimprovementthatwehaveseen,how-ever,islargelyrelatedtothelowlevelatwhichthingsgot
started. Ineducation inparticular,weseemtohavehitaceilingandmayactuallybeseeingsomeevidenceofde-cline.IntheUnitedStates,themediaisrepletewithacon-tinuingparadeof storiesabouttheongoingcrisis inbothprimaryandsecondaryeducation.
IntheU.S.,wearenotevensurewhattheactualhigh
schoolgraduationrateis.Apaperpublishedin2008bytheNationalBureauof EconomicResearch16pointsout thatDependingonthedatasources,definitions,andmethodsused, theU.S. graduation rate has been estimated to beanywherefrom66to88percentinrecentyearsanasto-nishinglywiderangeforsuchabasicstatistic.Therangeof
estimatedminority rates is even greaterfrom 50 to 85percent.ArecentlypublishedstudybytheNationalCen-terforEducationStatistics17showedthatover14percentofadultsintheUnitedStatesmaylackbasicreadingskills.Itseemsselfevidentthatifasmanyasathirdofourchild-renareunabletograduatefromhighschoolandupto1/7of ourpopulation fails to achievebasic literacy, thenwearenotsucceedinginsignificantlyadvancingthecapabilityoftheaverageworker.
Even the earlier trends toward improved nutritionandpublichealthhave,inmanyways,turnedagainstus.InmostWesterncountrieswenowhavearagingobesityepi-demicamongtheadultpopulation,andmostdisturbing-
lyalsoamongchildren.Whileadvancesinmedicinecon-tinue,manyofthesebreakthroughsseemtoprimarilyim-pact the health of retirement-age people. The overall
http://nces.ed.gov/naal/estimates/overview.aspxhttp://www.informationweek.com/news/management/trends/showArticle.jhtml?articleID=17500858http://www.oecd.org/dataoecd/37/26/36187829.pdfhttp://news.cnet.com/Techs-part-in-preventing-attacks/2100-7348_3-5778470.htmlhttp://www.accessmylibrary.com/coms2/summary_0286-30757731_ITMhttp://www.economist.com/business/displayStory.cfm?source=hptextfeature&story_id=11575170http://www.sba.gov/advo/stats/sbfaq.pdfhttp://www.sba.gov/advo/stats/sbfaq.pdfhttp://www.economist.com/business/displayStory.cfm?source=hptextfeature&story_id=11575170http://www.accessmylibrary.com/coms2/summary_0286-30757731_ITMhttp://news.cnet.com/Techs-part-in-preventing-attacks/2100-7348_3-5778470.htmlhttp://www.oecd.org/dataoecd/37/26/36187829.pdfhttp://www.informationweek.com/news/management/trends/showArticle.jhtml?articleID=17500858http://nces.ed.gov/naal/estimates/overview.aspx -
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healthof ouryoungerpopulation is stagnantor, insomecases,perhapsevendeclining. Inrecentyears,oneof the
fewpositivestoriesinthepublichealthandnutritionarenahasbeenthedeclineinthesmokingrate.
While the last graph was just an estimate, here isanothergraph18thatisbasedonactualdata:
TheaveragemathscoreonSATtestsadministeredby
theCollegeBoardhasremainedessentiallyflatforthepast35years.Thegraphforaverageverbalscoreslooksvirtual-lyidentical.College-boundstudentsthattaketheSATare,of course,probablyaboveaverageinturnsofworkcapa-bility.Itseemsprettyclearthat,intermsofincreasingthecapabilityofouraverageworkers,wehavealreadypickedthelow-hangingfruit,andwearestrugglingjusttomain-
tainthingsattheircurrentlevel.Atthispoint,weshouldhaveaprettygoodsensethat
if computer technology continues to progress at the ex-
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traordinaryratewehaveseenintherecentpast,thenhu-man workerswill not be able outrunmachine capability.
Youcanseethisvisuallywiththetwographsbelow:
Human Capability v. Computer Technology
Whilethesetwographsarenotbasedonanyspecific
data,wehaveshownprettyconvincinglythattheirshapeismoreor lesscorrect.Weknowthat thelower (computertechnology) graph currently lies somewhere below thehuman average capability graph.Andwe know that the
technology graph is increasing at an exceptionally fastgeometricpace.Whatelsedoweneed toknow?Clearly,thelinesseemverylikelytointersectatsomepointinthefuture.*
*IfyouarefamiliarwiththewritingsofThomasRobertMalthus,this
graphmaylookfamiliartoyou.In1798,MalthuspublishedhisEssayson the Principle ofPopulation inwhichhe argued that geometrically in-creasinghumanpopulationwouldoutstripsocietysabilitytoproducefood. InMalthus version of thegraph above, the top (diminishingreturns)linerepresentsfoodproduction,whilethebottom(geometric)
Capability
to Perform
Routine Jobs
Computer Technology
Human Workers
Time
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The continuing advance of computer technologyalongageometricallyincreasingpathandthediminishing
returnsfrominvestmentineducationseemtomakeaverystrong case that theaverageworkerandperhapsmanyabove-average workersare in clear danger of havingtheir jobsautomated.Next, lets lookatsometrendsandspecifictechnologiesthatshowexactlyhowthisislikelytohappen.
Offshoring and Drive-Through Banking
Automationandoffshoreoutsourcinghaveoneimportantthing in common: they are both driven by technology.Obviously,itisthevastimprovementinourcommunica-tionand informationtechnologies thathasenabledmany
service-oriented jobs to be relocated to low-wage coun-tries.WhenIwasgrowingupinthe1970s,Ioftenhadthe
opportunity to seedrive-throughbanking inaction.This,ofcourse,wasbeforetheintroductionofATMmachines.Atypicalbankdrive-throughwassetupwithtwoorthreelanessothatmultiplecustomerscouldbehandledatonetime. If you used the lane closest to the building, you
linerepresentspopulation.Hebelievedthatthetwolineswouldinter-sectandresultinwidespreadfamine.Malthus,ofcourse,turnedouttobe wrong largely because he failed to anticipate the technologicalprogressthatwouldoccurinfoodproductionandprocessing.Sodoesthat mean the graph above is just another Malthusian prediction
whichisalsodestinedtobewrong?OnethingtokeepinmindisthatMalthusinessenceplacedhisbetagainsttechnology;thegraphaboveassumesexactly the opposite.We should also acknowledge the un-happypossibility thatMalthusmightstillbevindicatedinthefuture,especiallyifclimatechangehasahighlynegativeimpactonagriculture.
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communicated with the teller through a standard cashdrawer.
Ifyouwereinoneofthelanesfurtherout,however,thingswerefarmoreinteresting.Yousealedyourmoney,paperwork,checkbook,etc.intoaplasticcylinderandthendropped thecylinder into theprovidedopening.Thecy-linder then traveled through an underground tubepropelled I thinkby somesort of vacuummechanism
untilitreachedtheteller.Shethencompletedthetransac-tion and sent thecylinder back toyou the sameway. Itarrived somewhat likeaball being returnedat a bowlingalley.
At thetime,thisseemedveryhigh tech.Thesystemhaditsflaws,however.Iclearlyrememberwaitinginline
behindoneunluckybankcustomerwho,failing to insertthe cylinder properly, watched it fall to the ground andthen rollunderhis car.Hethen found thatwhenheat-temptedtogetoutandretrieveit,hewasunabletoopenhisdoor.This,of course,wasanuproarioussight foranelevenor twelveyearold. Iwouldbewilling tobet thatanotherpotentialproblemwas customers forgetting theystillhadthecylinderandsimplydrivingawaywithit.
Thistypeofdrive-throughbankhasnow,of course,followedinthepathofthedinosaurs.Todaythetechnolo-gyseemsclunky.Atthetime,however,itrepresentedtheleading edge of what was technically possible. Drive-throughbanksprovidedausefulconvenience tocustom-
ersandalsooftenofferedextendedhoursofoperation.ThepointIammakinghereisthatoffshoringisreally
a precursor of automation. Offshoring is what you do
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Offshoring is thesmallwavethatdistractsyou.Automa-tionisthebigonefurtheroutthatyoudontseecoming.
Short Lived Jobs
Theconventionalwisdomasgenerallypresentedbyecon-omistsandotheranalystsisthat technologycreatesjobs.Whilehistory has shown that this is indeed true, italso showsquiteclearlythatthenewjobtypescreatedbytechnology
areveryoftenthemselvesquicklyvaporizedby the samephenomenon.TheIT jobs that arenowbeingoffshoredand automated are brand new jobs that were largelycreatedinthetechboomofthe1990s.ForsomeonewhochoseIT as apromising careerpath littlemorethan tenyearsago,thiscanbeadishearteningreality.
Earlierinthischapter,Itoldofmyexperienceusingcomputerpunch cardsat theUniversity ofMichigan.Atthetime,thesecardswereusedfornearlyeverything.Theutility bill you received in the mail was often a type ofpunchcard.Asa result, therewere thousandsof newjobs forkeypunchoperators.Theselaterbecamenewjobs for data entry clerks sitting at computer terminals.Now,ofcourse,technologiessuchasopticalbarcodesaregreatlyreducingtheneedforthistypeofdataentry.
Similarly, Imentionedthatmycollegefieldof study,computerengineering,wasnewat thetime.Softwareen-gineering isnowalso ahighlyoffshored field, andmuchprogresshasbeenmadetowardautomatingsomepartsof
thesoftwaredevelopmentprocess.Acollegestudenttodaymightwellthinktwicebeforeselectingthisrelativelynewfieldthatwascreatedonlyaboutthirtyyearsago.
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Technology has always caused job transitions. Trainconductors have been largely replaced by airline flight
crews, for example. However, within the high tech andcomputerfields,thepaceofchangeisunprecedentedandcontinuestodriverelentlesslytowardthetotaleliminationofjobs.Whatweareseeingisclearempiricalevidenceofthegeometricincreaseinthepowerofcomputertechnol-ogy.
Traditional Jobs: The Average Lights in theTunnel
Alltheattentionbeingfocusedonnewjobsbeingcreatedbytechnologytendstodistractusfromtherealitythatthebulkof the job types inoureconomyhaveremainedre-
markablystableovertime.Whiletechnologyhascertainlyimpactedthewaypeopleinthesejobswork,orthetypesofbusinessesatwhichtheywork,ithasnotyetalteredthebasicdefinitionsofthesetraditionaljobcategories.
Thetablethat followsisconstructedfromdatapub-lished by the U.S. Bureau of Labor Statistics in May2006.21ItlistsalltheoccupationsintheUnitedStateswithatleastonemillionworkers.
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Acceleration /59
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U.S. Occupations with at least one million workers (2006)
Occupation Number ofWorkers
Percentageof Workers
Retailsalespersons 4,374,230 3.3%
Cashier