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  • THE LIGHTS IN

          • Martin Ford

          • CONTENTS

    • INTRODUCTION

    • Chapter 1

    • THE TUNNEL

      • The Mass Market

      • Visualizing the Mass Market

      • Automation Comes to the Tunnel

      • A Reality Check

      • Summarizing

    • Chapter 2

    • ACCELERATION

      • The Rich Get Richer

      • World Computational Capability

      • Grid and Cloud Computing

      • Meltdown

      • Diminishing Returns

      • Offshoring and Drive-Through Banking

      • Short Lived Jobs

      • Traditional Jobs: The “Average” Lights in the Tunnel

      • A Tale of Two Jobs

      • “Software” Jobs and Artificial Intelligence

      • Automation, Offshoring and Small Business

      • “Hardware” Jobs and Robotics

      • “Interface” Jobs

      • The Next “Killer App”

      • Military Robotics

      • Robotics and Offshoring

      • Nanotechnology and its Impact on Employment

      • The Future of College Education

      • Econometrics: Looking Backward

      • The Luddite Fallacy

      • A More Ambitious View of Future Technological Progress: The Singularity

      • A War on Technology

    • Chapter 3

    • DANGER

      • The Predictive Nature of Markets

      • The 2008-2009 Recession

      • Offshoring and Factory Migration

      • Reconsidering Conventional Views about the Future

      • The China Fallacy

      • The Future of Manufacturing

      • India and Offshoring

      • Economic and National Security Implications for the United States

      • Solutions

      • Labor and Capital Intensive Industries: The Tipping Point

      • The Average Worker and the Average Machine

      • Capital Intensive Industries are “Free Riders”

      • The Problem with Payroll Taxes

      • The “Workerless” Payroll Tax

      • “Progressive” Wage Deductions

      • Defeating the Lobbyists

      • A More Conventional View of the Future

      • The Risk of Inaction

    • Chapter 4

    • TRANSITION

      • The Basis of the Free Market Economy: Incentives

      • Preserving the Market

      • Recapturing Wages

          • Unit Cost Breakdown for a Hypothetical Product or Service

      • Positive Aspects of Jobs

      • The Power of Inequality

      • Where the Free Market Fails: Externalities

      • Creating a Virtual Job

        • Education

        • Community and Civic Activities

        • Journalism

        • The Environment and other Externalities

        • Setting the Incentives

      • Smoothing the Business Cycle and Reducing Economic Risk

      • The Market Economy of the Future

      • An International View

      • Transitioning to the New Model

      • Keynesian Grandchildren

      • Transition in the Tunnel

    • Chapter 5

    • THE GREEN LIGHT

      • Attacking Poverty

      • Fundamental Economic Constraints

        • Labor

        • Energy, Land, Natural Resources and Environmental Impact

        • Technology

        • Consumer Demand

      • Removing the Constraints

      • The Evolution toward Consumption

      • The Green Light

    • APPENDIX / FINAL THOUGHTS

      • Are the ideas presented in this book WRONG? (Opposing arguments with responses)

      • Two Questions Worth Thinking About

        • One

        • Two

      • Where are we now? Four Possible Cases

      • The Next 10-20 years: Some Indicators to Watch For

        • Labor intensive areas of the economy begin to see increased automation

        • New technology industries fail to create significant numbers of jobs

        • Diminishing prospects for college graduates

        • Systemic unemployment invades the economy

        • Increasingly bad news for entitlement and retirement programs

        • Trouble in China

        • Continuing Instability in the Financial Markets

        • Ugly and irrational political battles

      • Outsmarting Marx

      • The Technology Paradox

      • Machine Intelligence and the Turing Test

    • About / Contacting the Author

    • NOTES

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Acceleration / 45 CopyrightedMaterial–Paperback/Kindle available @ Amazon Astheir computers got fasterand faster, the quants wereabletodomoreandmore.Theycreatednewexotic derivativesbasedonstrangecombinationsofthings.They could magnify the reward (and risk) of a security. They could invertit,soyougainedifthesecurityfellinvalue. Theycouldeventrytocapturetherewardifaninvestment increasedinvalue,buteliminatetheriskifitwentdown— oratleasttheythoughttheycould. Ashousingpricescontinuedtoclimbduringthebub- ble, the subprime loans were packaged into mortgage- backedsecuritiessothattheycouldbetradedlikebonds. This had become standardpracticeformortgages. How- ever, in addition to that, new types of derivatives were createdbasedonthepackagedsubprimeloans.Mostnot- able were “collateralized debt obligations” (or CDOs), which attempted tosiphonoffthelowest risk loans and repackagethemintoasecuritythatcouldbemarketedasa high quality investment. These new derivative securities werethensoldtobanksandfinancialinstitutionsallover theworld,withtheunderstandingthattheywereverylow riskinvestments. Whenthesubprimeborrowersstarteddefaulting,the valueofthemortgage-backed securitiesplunged,andthe derivativesdidnotworkasexpected.Inmanycasesitwas difficultorimpossibletocalculatetheirvalue.Inaddition, financialinstitutionshadengagedinmanyothercomplex interrelationships based on exotic derivatives that were intendedtohelpmanagevariousrisks.Allthisledtoun- certaintythatcausedvaluestofallevenmore. Theresult THE LIGHTS IN THE TUNNEL / 46 CopyrightedMaterial–Paperback/Kindle available @ Amazon wasthedownfallofBearStearnsinMarch2008,andthe globalcrisisthatfollowed. The point of this, of course, is that it would have beenimpossibletocreatetheseweirdderivativeswithout accesstoverypowerfulcomputers.Ifthesubprimecrisis hadoccurredinearlieryears,itwouldcertainlyhavebeen a far smaller event. It’s worth noting that the meltdown startedin2007.Aswearenowin2009,weknowthatthe powerofthecomputersonWallStreetdeskshasroughly doubled,evenasthecrisishascontinued. Exoticderivativesare,ofcourse,nottheonlyexam- ple of the dramatic impact of advancing computer tech- nology on financial markets. On October 19, 1987, the stock market fell a staggering twenty percent in a single day.Therewasreallynospecificnewseventorotherfac- tor thatmighthaveexplainedthesuddendrop. Manyof the people involved in quantitative technologies on Wall Street at the time believe that the crash may have been precipitated by computer programs that traded autono- mouslyinthehopeofproviding“portfolioinsurance”for biginvestors. Asthisis beingwritten,articlesare appearinginthe pressregardingtheuseofextremelyfastWallStreetcom- putersthatallowtransactionsto beexecutedinfractions ofasecond. Thispractice,known as“flashtrading,” has quicklyattractedthenoticeoftheSecuritiesandExchange Commissionandmayresultinnewregulation. Astheseexamplesshow,wecanexpectthattherate ofchangeandthevolatilityofnearlyeverythingaroundus will be somehow amplified by the incredible increase in Acceleration / 47 CopyrightedMaterial–Paperback/Kindle available @ Amazon ourabilitytocompute.Wecanalso certainlyexpectthat thisdramaticallyexpandedcomputationalcapacitywillbe focusedincreasinglyonautomatingourjobs. Laterinthischapter,we’lllookinmoredetailatsev- eral specific advancing technologies and how theymight impact the job market and the economy in general. But first,let’snowturnfrommachinestohumanbeings.Isit possiblethatwecansomehow“outrun”computerssowe canallkeepourjobs? Diminishing Returns In1811,EnglandwasinthemidstoftheIndustrialRevo- lution. That year, a group called the Luddites formed in Nottingham. The Luddites consisted of skilled textile workers who felt threatened by the introduction of me- chanical looms that could be operated by low-paid, un- skilledworkers.Theytooktheirnamefromamannamed NedLudwhohadreportedlydestroyedoneof thesead- vanced looms. The Luddites’protests grew into outright riotsanddestructionofmachines.TheBritishgovernment finallyenactedharshmeasuresandthemovementcameto an end in 1812. Since then, the word “luddite” has, of course,evolvedintoasomewhatderogatorytermforany- oneopposedtotechnological progressorillequippedto dealwithnewtechnologies. Economistsgenerallydismisstheideathatadvancing technology will ever permanently displace humans and thereby continuouslyincreasethe unemployment rate.In otherwords,mostmainstreameconomistsfullyacceptour assumption at the beginning of this chapter. (Not the THE LIGHTS IN THE TUNNEL / 48 CopyrightedMaterial–Paperback/Kindle available @ Amazon “2089” version; the never one.) Those who have raised concerns in more recent times are dismissed as “neo- Luddites.” Economists have also formulated something calledtheLudditefallacytohelpexplainwhytheconcerns of neo-Luddites are wrong. We’ll look at this in a little moredetaillater. Obviously, England is now a modern country, and the vast majority of workers still have jobs. The British peoplearenowfarbetteroffthantheywerein1812.So weretheLudditeswrong?Orjusttwohundredorsoyears tooearly? Weknowthattechnologyhasadvancedtremendously since1812.Whatabouthumanbeings?Haveweadvanced aswell? In termsof basicbiology, we areessentially un- changed. Little if any biological evolution takes place in onlytwohundredyears.Still,doesn’titseemlikelythatthe average British worker today is far more capable than a typicalworkernearlytwohundredyearsago? Let’simaginewhatlifewaslikeforanaverageEnglish personin1812.Asitturns out,it’seasytoget somein- sightinto this becauseCharlesDickens was bornin that exactyear.Dickensdrewonhisownexperiencesandob- servationsasachildwhenhelaterwrotehisfamousno- vels.Hisdescriptionsofaharsh,poverty-strickensociety and an environment made filthy by the soot from coal- burningindustryarewellknown. InOliverTwist,Dickensdescribesthemiserablelifeof anorphanboyduringtheIndustrialRevolution.Herehe expresseshisfeelingsasthestarvingOliverisgivenscraps ofmeatthathadfirstbeenofferedtoadog:“Iwishsome Acceleration / 49 CopyrightedMaterial–Paperback/Kindle available @ Amazon well-fed philosopher, whose blood is ice, whose heart is iron;couldhaveseenOliverTwistclutchingatthedainty viands the dog had neglected.I wish he could have wit- nessedthehorribleaviditywithwhichOlivertorethebits asunderwithalltheferocityoffamine.” 15  Clearly, the average British worker is far better fed today.Weknowtheenvironmentisalsomuchcleanerand more healthy. The literacy rate in Britain today is pur- portedtobeashighas99percent.It’shardtoknowwhat itwasin1812,butaround50percentmightbea decent guess—andofcourse,theabilitytoreadandwritewould havebeenhighlyconcentratedintheupperclasses. In 1812, there was essentially no public education available in England. The government did not begin to investsignificantlyineducationuntil1870,andattendance was not compulsory until 1880. Obviously, the average workertodayisfarbettereducatedthanheorshewould havebeenin1812. Givenallofthis,wecansaythat,duetodramaticim- provementsinlivingconditionsandeducation,anaverage worker today is certainly more capable and able to per- form more complex, high-level tasks than a worker in 1812.Buttherealquestionis:canweexpectthatkindof improvementtocontinueinthefuture? Thefollowinggraphshowswhatanaverageworker’s abilitytoperformcomplextasksmightlooklikeoverthe pasttwohundredorsoyears.Thegraphicisjustanintui- tiveestimate.Itisnotbasedonanyrealdata.However,I suspect that most people would agree with the general shapeofthegraph,andthatisallthatreallymatters. THE LIGHTS IN THE TUNNEL / 50 CopyrightedMaterial–Paperback/Kindle available @ Amazon  Average Worker’s Ability to Perform Complex Tasks         I’vechosenanarbitrarypointonthegraphtoindicate theyear1812.After thatyear,wecanreasonablyassume thathumancapabilitycontinuedtorisequitesteeplyuntil we reach modern times.The steep part of thegraph re- flectsdramaticimprovementstoouroveralllivingcondi- tionsintheworld’smoreadvancedcountries:  Vastlyimprovednutrition,publichealth,andenvi- ronmental regulations have allowed us to remain relativelyfreefromdiseaseandreachourfullbio- logicalpotential.  Investmentinliteracyandinprimaryandsecond- aryeducation,aswellasaccesstocollegeandad- vancededucationforsomeworkers,hasgreatlyin- creasedoverallcapability.  A generally richer and more varied existence, in- cludingeasyaccesstobooks,media,newtechnol- ogies and the ability to travel long distances, has probably had a positive impact on our ability to comprehendanddealwithcomplexissues. Luddites riot - 1812 Time Average Human Capability Acceleration / 51 CopyrightedMaterial–Paperback/Kindle available @ Amazon Thedegreeofimprovementthatwehaveseen,how- ever,islargelyrelatedtothelowlevelatwhichthingsgot started.In educationinparticular,weseemtohavehit a ceiling—andmayactuallybeseeingsomeevidenceofde- cline.IntheUnitedStates,themediaisrepletewithacon- tinuingparadeofstoriesabouttheongoingcrisisinboth primaryandsecondaryeducation. IntheU.S.,wearenotevensurewhattheactualhigh schoolgraduationrateis.Apaperpublishedin2008bythe NationalBureauofEconomicResearch 16 pointsout that “Dependingonthedatasources,definitions,andmethods used, the U.S. graduation rate has been estimated to be anywherefrom66to88percentinrecentyears—anasto- nishinglywiderangeforsuchabasicstatistic.Therangeof estimated minority rates is even greater—from 50 to 85 percent.”ArecentlypublishedstudybytheNationalCen- terforEducationStatistics 17 showedthatover14percent ofadultsintheUnitedStatesmaylackbasicreadingskills. Itseemsselfevidentthatifasmanyasathirdofourchild- renareunabletograduatefromhighschoolandupto1/7 of ourpopulation fails to achieve basic literacy, then we arenotsucceedinginsignificantlyadvancingthecapability oftheaverageworker. Even the earlier trends toward improved nutrition andpublichealthhave,inmanyways,turnedagainstus.In mostWesterncountrieswenowhavearagingobesityepi- demicamongtheadultpopulation,and—mostdisturbing- ly—alsoamongchildren.Whileadvancesinmedicinecon- tinue,manyofthesebreakthroughsseemtoprimarilyim- pact the health of retirement-age people. The overall THE LIGHTS IN THE TUNNEL / 52 CopyrightedMaterial–Paperback/Kindle available @ Amazon healthofouryoungerpopulationisstagnantor, insome cases,perhapsevendeclining.Inrecentyears,oneofthe fewpositivestoriesinthepublichealthandnutritionarena hasbeenthedeclineinthesmokingrate. While the last graph was just an estimate, here is anothergraph 18 thatisbasedonactualdata:  TheaveragemathscoreonSATtestsadministeredby theCollegeBoardhasremainedessentiallyflatforthepast 35years.Thegraphforaverageverbalscoreslooksvirtual- lyidentical.College-boundstudentsthattaketheSATare, ofcourse,probablyaboveaverageinturnsofworkcapa- bility.Itseemsprettyclearthat,intermsofincreasingthe capabilityofouraverageworkers,wehavealreadypicked thelow-hangingfruit,andwearestrugglingjusttomain- tainthingsattheircurrentlevel. Atthispoint,weshouldhaveaprettygoodsensethat if computer technology continues to progress at the ex- Average SAT Math Scores 1972-2007 0 100 200 300 400 500 600 700 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 Year Average Math Score Acceleration / 53 CopyrightedMaterial–Paperback/Kindle available @ Amazon traordinaryratewehaveseenintherecentpast,thenhu- man workers will not be able outrun machine capability. Youcanseethisvisuallywiththetwographsbelow: Human Capability v. Computer Technology            Whilethesetwographsarenotbasedonanyspecific data,wehaveshownprettyconvincinglythattheirshapeis moreor lesscorrect.Weknowthatthelower(computer technology) graph currently lies somewhere below the human average capability graph. And we know that the technology graph is increasing at an exceptionally fast geometric pace.Whatelsedo weneed toknow? Clearly, thelinesseemverylikelytointersectatsomepointinthe future. *    * IfyouarefamiliarwiththewritingsofThomasRobertMalthus,this graphmaylookfamiliartoyou.In1798,MalthuspublishedhisEssays on thePrinciple of Population in which he argued thatgeometrically in- creasinghumanpopulationwouldoutstripsociety’sabilitytoproduce food. In Malthus’ version of the graph above, the top (diminishing returns)linerepresentsfoodproduction,whilethebottom(geometric) Capability to Perform Routine Jobs Computer Technology Human Workers Time THE LIGHTS IN THE TUNNEL / 54 CopyrightedMaterial–Paperback/Kindle available @ Amazon The continuing advance of computer technology alongageometricallyincreasingpathandthediminishing returnsfrominvestmentineducationseemtomakeavery strong case that the average worker—and perhaps many above-average workers—are in clear danger of having theirjobsautomated.Next,let’slookatsometrendsand specifictechnologiesthatshowexactlyhowthisislikelyto happen. Offshoring and Drive-Through Banking Automationandoffshoreoutsourcinghaveoneimportant thing in common: they are both driven by technology. Obviously,itisthevastimprovementinourcommunica- tionandinformationtechnologiesthathasenabledmany service-oriented jobs to be relocated to low-wage coun- tries. WhenIwasgrowingupinthe1970s,Ioftenhadthe opportunitytoseedrive-throughbankinginaction.This, ofcourse,wasbeforetheintroductionofATMmachines. Atypicalbankdrive-throughwassetupwithtwoorthree lanessothatmultiplecustomerscouldbehandledatone time. If you used the lane closest to the building, you   linerepresentspopulation.Hebelievedthatthetwolineswouldinter- sectandresultinwidespreadfamine.Malthus,ofcourse,turnedoutto be wrong largely because he failed to anticipate the technological progressthatwouldoccurinfoodproductionandprocessing.Sodoes that mean the graph above is just another “Malthusian” prediction whichisalsodestinedtobewrong?Onethingtokeepinmindisthat Malthusinessenceplacedhisbetagainsttechnology;thegraphabove assumes exactly the opposite. We should also acknowledge the un- happypossibilitythatMalthusmightstillbevindicatedinthefuture, especiallyifclimatechangehasahighlynegativeimpactonagriculture. [...]... case of a pair of sunglasses sitting on a table The sunglasses might be closed with the lenses facing down, or with the lenses up Or perhaps the glasses are open with the lenses oriented vertically Or maybe one side of the glasses is open and the other closed And, of course, the glasses could be rotated in any direction And perhaps they are touching or somehow entangled with other objects Building and. .. the power of computer technology Traditional Jobs: The “Average” Lights in the Tunnel All the attention being focused on new jobs being created by technology tends to distract us from the reality that the bulk of the job types in our economy have remained remarkably stable over time While technology has certainly impacted the way people in these jobs work, or the types of businesses at which they work,... use at a number of retail stores We can be sure that in the future, these will become more reliable, easier to use, and more popular What will we do if someday a substantial percentage of the three and a half million cashiers in the U.S no longer have jobs? What additional education and training can we offer these workers? And what jobs would it prepare them for? And what is the impact of that potential... presented by economists and other analysts is that technology creates jobs While history has shown that this is indeed true, it also shows quite clearly that the new job types created by technology are very often themselves quickly vaporized by the same phenomenon The IT jobs that are now being offshored and automated are brand new jobs that were largely created in the tech boom of the 1990s For someone... recognize the sunglasses in any possible configuration and then Copyrighted Material – Paperback/Kindle available @ Amazon THE LIGHTS IN THE TUNNEL / 66 pick them up, fold them and put them back in their case is so difficult that we can probably conclude that the housekeeper’s job is relatively safe for the time being Contrast the housekeeping robot’s complex visual recognition challenge with the task of. .. seems likely that the radiologist’s job is at higher risk of being automated in the near future.* A big part of the reason for this is that the radiologist has what I call a software job “Software” Jobs and Artificial Intelligence When I speak of a “software” job, I don’t mean that a person who has the job necessarily works with or programs software I simply mean that automation of the job potentially... courtroom These attorneys are employed in the areas of legal research and contracts They work at law firms and spend much of their time in the library or accessing legal databases through their computers They research case law, and write briefs which summarize relevant court cases and legal strategies from Copyrighted Material – Paperback/Kindle available @ Amazon Acceleration / 71 the past They review... advance, many of the jobs now being transferred overseas will simply disappear altogether Currently, most of the controversy and political debate is focused is on offshoring rather than automation This may well prove to be a shortsighted view Information technology (IT) workers in the developed nations have been one of the groups hardest hit by job losses from offshoring A 2006 study by the Organisation... Many of the jobs listed in the table are already in the process of being automated or offshored Others will be targeted in the very near future Millions of other workers in occupations that do not appear in the list are also at high risk As we will see, this includes many occupations that are not, by any means, either low-skill or low paid Allowing these jobs to be relentlessly eliminated by the millions,... four years, and then medical school for another four That is followed by another five years of internship and residency, and often even more specialized training after that Radiology is one the most popular specialties for newly minted doctors because it offers relatively high pay and regular work hours; radiologists generally don’t need to work weekends or handle emergencies In spite of the radiologist’s . technology continues to progress at the ex- Average SAT Math Scores 19 72-2007 0 10 0 200 300 400 500 600 700 19 72 19 75 19 78 19 81 1984 19 87 19 90 19 93 19 96 19 99 2002 2005 Year Average Math Score Acceleration. 3,026, 710  2.3%  Combinedfoodpreparation and serv- ingworkers,includingfastfood 2,4 61, 890  1. 9%  Registerednurses 2, 417 ,15 0  1. 8%  Laborers and freight,stock, and ma- terialmovers,hand 2,372 ,13 0  1. 8%  Waiters and waitresses 2, 312 ,930  1. 7%  Customerservicerepresentatives. 1, 663,280  1. 3%  Elementaryschoolteachers 1, 509 ,18 0  1. 1%  Salesrepresentatives,wholesale and manufacturing,excepttechnical and scientificproducts 1, 488,990  1. 1%  THE LIGHTS IN THE

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