IMF-第二代人工智能：人工智能與未來工作（英）

Gen-AI:Artificial

IntelligenceandtheFutureofWork

PreparedbyMauroCazzaniga,FlorenceJaumotte,LongjiLi,

GiovanniMelina,AugustusJ.Panton,CarloPizzinelli,Emma

Rockall,andMarinaM.Tavares

SDN/2024/001

IMFStaffDiscussionNotes(SDNs)showcase

policy-relatedanalysisandresearchbeing

developedbyIMFstaffmembersandare

publishedtoelicitcommentsandtoencourage

debate.TheviewsexpressedinStaffDiscussion

Notesarethoseoftheauthor(s)anddonot

necessarilyrepresenttheviewsoftheIMF,

itsExecutiveBoard,orIMFmanagement.

2024

JAN

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SDN/2024/001

?2024InternationalMonetaryFund

IMFStaffDiscussionNotes

ResearchDepartment

Gen-AI:ArtificialIntelligenceandtheFutureofWork

PreparedbyMauroCazzaniga,FlorenceJaumotte,LongjiLi,GiovanniMelina,AugustusJ.Panton,CarloPizzinelli,EmmaRockall,andMarinaM.Tavares*

AuthorizedfordistributionbyPierre-OlivierGourinchas

January2024

IMFStaffDiscussionNotes(SDNs)showcasepolicy-relatedanalysisandresearchbeing

developedbyIMFstaffmembersandarepublishedtoelicitcommentsandtoencouragedebate.

TheviewsexpressedinStaffDiscussionNotesarethoseoftheauthor(s)anddonotnecessarilyrepresenttheviewsoftheIMF,itsExecutiveBoard,orIMFmanagement.

ABSTRACT:Artificialintelligence(AI)hasthepotentialtoreshapetheglobaleconomy,especiallyintherealmoflabormarkets.AdvancedeconomieswillexperiencethebenefitsandpitfallsofAIsoonerthanemerging

marketanddevelopingeconomies,largelybecausetheiremploymentstructureisfocusedoncognitive-

intensiveroles.TherearesomeconsistentpatternsconcerningAIexposure:womenandcollege-educated

individualsaremoreexposedbutalsobetterpoisedtoreapAIbenefits,andolderworkersarepotentiallylessabletoadapttothenewtechnology.LaborincomeinequalitymayincreaseifthecomplementaritybetweenAIandhigh-incomeworkersisstrong,andcapitalreturnswillincreasewealthinequality.However,ifproductivitygainsaresufficientlylarge,incomelevelscouldsurgeformostworkers.Inthisevolvinglandscape,advanced

economiesandmoredevelopedemergingmarketeconomiesneedtofocusonupgradingregulatory

frameworksandsupportinglaborreallocationwhilesafeguardingthoseadverselyaffected.Emergingmarketanddevelopingeconomiesshouldprioritizethedevelopmentofdigitalinfrastructureanddigitalskills.

RECOMMENDEDCITATION:Cazzanigaandothers.2024.“Gen-AI:ArtificialIntelligenceandtheFutureofWork.”IMFStaffDiscussionNoteSDN2024/001,InternationalMonetaryFund,Washington,DC.

ISBN:979-8-40026-254-8

JELClassificationNumbers:E24,J24,J31,O33,O38

Keywords:

ArtificialIntelligence,LaborMarket,JobDisplacement,Income

Inequality,AdvancedEconomies,EmergingMarketEconomies,Low-IncomeDevelopingCountries

Author’sE-MailAddress:

mauro98cazzaniga@,FJaumotte@,LLi4@,

GMelina@,APanton@,CPizzinelli@,ERockall@,MMendestavares@

*TheauthorsthankPierre-OlivierGourinchasandAntonioSpilimbergoforfeedbackandguidanceandmanyIMFcolleaguesfor

usefulcomments.TheviewsexpressedhereinarethoseoftheauthorsandshouldnotbeattributedtotheIMF,itsExecutiveBoard, oritsmanagement.Anyremainingerrorsaretheresponsibilityoftheauthors.

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Contents

ExecutiveSummary

2

I.Introduction

3

II.AIExposureandComplementarity

5

III.WorkerReallocationintheAI-InducedTransformation

11

IV.AI,Productivity,andInequality

15

V.AIPreparedness

19

VI.ConclusionsandPolicyConsiderations

22

AnnexI.Data

26

Annex2.AdditionalInformationonAIOccupationalExposureandPotentialComplementarity

28

Annex3.MethodologyfortheWorkerTransitionAnalysis

29

Annex4.ModelDetails

32

Annex5.AIPreparednessIndex

34

References

36

Boxes

1.AIOccupationalExposureandPotentialComplementarity1

24

2.Artificial-Intelligence-ledInnovationandthePotentialforGreaterInclusion1

25

Figures

1.EmploymentSharesbyAIExposureandComplementarity:CountryGroupsandSelect

8

2.EmploymentSharebyExposureandComplementarity(SelectedCountries)

9

3.ShareofEmploymentinHigh-ExposureOccupationsbyDemographicGroups

10

4.ShareofEmploymentinHigh-ExposureOccupationsbyIncomeDeciles

11

5.OccupationalTransitionsforCollege-EducatedHigh-ExposureWorkersforBRAandGBR

12

6.LifeCycleProfilesofEmploymentSharesbyEducationLevelforBrazilandtheUnited

13

7.1-YearRe-EmploymentProbabilityofSeparatedWorkers

14

8.EstimatedWagePremiafromOccupationChanges

15

9.ExposuretoAIandtoAutomationandIncomeintheUK

17

10.ChangeinTotalIncomebyIncomePercentile

18

11.ImpactonAggregates(Percentage

18

12.AIPreparednessIndexand

20

13.ICTEmploymentShareandIndividualComponentsoftheAIPreparednessIndex

21

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ExecutiveSummary

Artificialintelligence(AI)issettoprofoundlychangetheglobaleconomy,withsomecommentators

seeingitasakintoanewindustrialrevolution.Itsconsequencesforeconomiesandsocietiesremainhardtoforesee.Thisisespeciallyevidentinthecontextoflabormarkets,whereAIpromisestoincreaseproductivitywhilethreateningtoreplacehumansinsomejobsandtocomplementtheminothers.

Almost40percentofglobalemploymentisexposedtoAI,withadvancedeconomiesatgreaterriskbutalsobetterpoisedtoexploitAIbenefitsthanemergingmarketanddevelopingeconomies.Inadvancedeconomies,about60percentofjobsareexposedtoAI,duetoprevalenceofcognitive-task-orientedjobs.A

newmeasureofpotentialAIcomplementaritysuggeststhat,ofthese,abouthalfmaybenegativelyaffectedbyAI,whiletherestcouldbenefitfromenhancedproductivitythroughAIintegration.Overallexposureis40

percentinemergingmarketeconomiesand26percentinlow-incomecountries.Althoughmanyemerging

marketanddevelopingeconomiesmayexperiencelessimmediateAI-relateddisruptions,theyarealsolessreadytoseizeAI’sadvantages.Thiscouldexacerbatethedigitaldivideandcross-countryincomedisparity.

AIwillaffectincomeandwealthinequality.Unlikepreviouswavesofautomation,whichhadthestrongesteffectonmiddle-skilledworkers,AIdisplacementrisksextendtohigher-wageearners.However,potentialAIcomplementarityispositivelycorrelatedwithincome.Hence,theeffectonlaborincomeinequalitydepends

largelyontheextenttowhichAIdisplacesorcomplementshigh-incomeworkers.Modelsimulationssuggestthat,withhighcomplementarity,higher-wageearnerscanexpectamore-than-proportionalincreaseintheir

laborincome,leadingtoanincreaseinlaborincomeinequality.Thiswouldamplifytheincreaseinincomeandwealthinequalitythatresultsfromenhancedcapitalreturnsthataccruetohighearners.Countries’choices

regardingthedefinitionofAIpropertyrights,aswellasredistributiveandotherfiscalpolicies,willultimatelyshapeitsimpactonincomeandwealthdistribution.

Thegainsinproductivity,ifstrong,couldresultinhighergrowthandhigherincomesformostworkers.

Owingtocapitaldeepeningandaproductivitysurge,AIadoptionisexpectedtoboosttotalincome.IfAI

stronglycomplementshumanlaborincertainoccupationsandtheproductivitygainsaresufficientlylarge,

highergrowthandlabordemandcouldmorethancompensateforthepartialreplacementoflabortasksbyAI,andincomescouldincreasealongmostoftheincomedistribution.

College-educatedworkersarebetterpreparedtomovefromjobsatriskofdisplacementtohigh-

complementarityjobs;olderworkersmaybemorevulnerabletotheAI-driventransformation.IntheUKandBrazil,forinstance,college-educatedindividualshistoricallymovedmoreeasilyfromjobsnowassessedtohavehighdisplacementpotentialtothosewithhighcomplementarity.Incontrast,workerswithout

postsecondaryeducationshowreducedmobility.Youngerworkerswhoareadaptableandfamiliarwithnew

technologiesmayalsobebetterabletoleveragethenewopportunities.Incontrast,olderworkersmaystrugglewithreemployment,adaptingtotechnology,mobility,andtrainingfornewjobskills.

ToharnessAI'spotentialfully,prioritiesdependoncountries’developmentlevels.AnovelAI

preparednessindexshowsthatadvancedandmoredevelopedemergingmarketeconomiesshouldinvestinAI

innovationandintegration,whileadvancingadequateregulatoryframeworkstooptimizebenefitsfrom

increasedAIuse.Forlesspreparedemergingmarketanddevelopingeconomies,foundationalinfrastructuraldevelopmentandbuildingadigitallyskilledlaborforceareparamount.Foralleconomies,socialsafetynetsandretrainingforAI-susceptibleworkersarecrucialtoensureinclusivity.

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I.Introduction

Artificialintelligence(AI)promisestoboostproductivityandgrowth,butitsimpactoneconomiesandsocietiesisuncertain,varyingbyjobrolesandsectors,withthepotentialtoamplifydisparities.Asapositiveproductivityshock,AIwillexpandeconomies’productionfrontiersandwillleadtoreallocations

betweenlaborandcapitalwhiletriggeringpotentiallyprofoundchangesinmanyjobsandsectors.AIoffersunprecedentedopportunitiesforsolvingcomplexproblemsandimprovingtheaccuracyofpredictions,

enhancingdecision-making,boostingeconomicgrowth,andimprovinglives.However,preciselybecauseofitsvastandflexibleapplicabilityinnumerousdomains,theimplicationsforeconomiesandsocietiesareuncertain(IlzetzkiandJain2023).

AIrepresentsawidespectrumoftechnologiesdesignedtoenablemachinestoperceive,interpret,act,andlearnwiththeintenttoemulatehumancognitiveabilities.Acrossthisspectrum,generativeAI(GenAI)includessystemssuchassophisticatedlargelanguagemodelsthatcancreatenewcontent,rangingfromtexttoimages,bylearningfromextensivetrainingdata.OtherAImodels,incontrast,aremorespecialized,

focusingondiscretetaskssuchaspatternidentification.Meanwhile,automationischaracterizedbyitsfocuson

optimizingrepetitivetaskstoboostproductivity,ratherthanproducingnewcontent.ThefieldofAIis

experiencingaswiftevolution,especiallywiththeadventofGenAI,whichhasbroadenedAI'spotentialapplications.Thissuggeststhatitsimpactwillexpandtoreshapejobfunctionsandthedivisionoflabor.

OnecriticaldimensiontoconsideristhesocietalacceptabilityofAI.Acceptabilitymayvarydependingonjobroles.SomeprofessionsmayseamlesslyintegrateAItools,whileotherscouldfaceresistancebecauseofcultural,ethical,oroperationalconcerns.Thisuncertaintybecomesespeciallypronouncedinlabormarkets.

AlthoughAIholdsthepotentialforproduction-orientedapplications,itseffectwilllikelybemixed.Insome

sectorswherehumanoversightofAIisnecessary,itcouldamplifyworkerproductivityandlabordemand.

Conversely,inothersectors,AImightpavethewayforsignificantjobdisplacements.Ariseinaggregate

productivityoftheeconomycouldhoweverstrengthenoveralleconomicdemand,potentiallycreatingmorejobopportunitiesformostworkersinarippleeffect.Moreover,thisevolutioncouldalsoleadtotheemergenceofnewsectorsandjobroles—andthedisappearanceofothers—transcendingmereintersectoralreallocation.

Beyondimmediatejobeffects,anothercriticaleconomicdimensionisthecapitalincomechannel.AsAIdrivesefficiencyandinnovations,thosewhoownAItechnologiesorhavestakesinAI-drivenindustriesmay

experienceincreasedcapitalincome.Thisshiftcouldpotentiallyexacerbateinequalities.

AIchallengesthebeliefthattechnologyaffectsmainlymiddleand,insomecases,low-skilljobs:its

advancedalgorithmscannowaugmentorreplacehigh-skillrolespreviouslythoughtimmuneto

automation.Whilehistoricalwavesofautomationandtheintegrationofinformationtechnologyaffected

predominantlyroutinetasks,AI'scapabilitiesextendtocognitivefunctions,enablingittoprocessvastamounts

ofdata,recognizepatterns,andmakedecisions.Asaresult,evenhigh-skilloccupations,whichwere

previouslyconsideredimmunetoautomationbecauseoftheircomplexityandrelianceondeepexpertisenowfacepotentialdisruption.1Jobsthatrequirenuancedjudgment,creativeproblem-solving,orintricatedata

1

Anotherhistoricalexampleoftechnologythathittherelativelyeducatedistheintroductionofthecalculator.Beforethewidespread

useofcalculators,theroleofaccountantswasconsideredamedium-tohigh-skilljob,giventhatasignificantportionofthe

populationwasuneducated.Theintroductionofcalculatorsledtoareductioninthenumberofaccountants(WoottonandKemmerer2007).

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interpretation—traditionallythedomainofhighlyeducatedprofessionals—maynowbeaugmentedorevenreplacedbyadvancedAIalgorithms,potentiallyexacerbatinginequalityacrossandwithinoccupations.Thisshiftchallengestheconventionalwisdomthattechnologicaladvancesthreatenprimarilylower-skilljobsandpointstoabroaderanddeepertransformationofthelabormarketthanbyprevioustechnologicalrevolutions.

TheimpactofAIisalsolikelytodiffersignificantlyacrosscountriesatdifferentlevelsofdevelopmentorwithdifferenteconomicstructures.Advancedeconomies,withtheirmatureindustriesandservice-driveneconomies,typicallyhaveahigherconcentrationofjobsinsectorsthatrequirecomplexcognitivetasks.Theseeconomiesarethereforebothmoresusceptibleto,yetbetterpositionedtobenefitfrom,AIinnovations.

Conversely,emergingmarketanddevelopingeconomies,oftenstillreliantonmanuallaborandtraditional

industries,mayinitiallyfacefewerAI-induceddisruptions.However,theseeconomiesmayalsomissouton

earlyAI-drivenproductivitygains,giventheirlackofinfrastructureandaskilledworkforce.Overtime,theAI

dividecouldexacerbateexistingeconomicdisparities,withadvancedeconomiesharnessingAIforcompetitiveadvantagewhileemergingmarketanddevelopingeconomiesgrapplewithintegratingAIintotheirgrowth

models.

ToinformthediscussiononthepotentialimpactofAIonthefutureofworkandwhichpoliciescountriesshouldenactinresponse,thisnoteaimstoanswersixquestions.

(1)WhichcountriesaremoreexposedtoAIadoption?Whichcountriesarelikelytobenefitmost?

(2)HowdifferentlywillAIaffectworkerswithincountries?Whichsegmentsofworkersarelikelytothriveandwhichfacemorerisks?

(3)Historically,howfrequentlydidworkersshiftbetweenrolesnowfacingvaryingAIexposure?Whatinsightsdotheseshiftsrevealaboutlaboradaptability?

(4)InwhatwayscouldAIreshapeincomeandwealthinequality?

(5)Whatisthepotentialimpactforgrowthandproductivity?

(6)WhichcountriesappearbetterpreparedfortheAItransition?HowcanpoliciesmaximizegainsandmitigatelikelyAI-relatedchallenges?

ThisnotebuildsonagrowingbodyofworkthatexplorestheimpactofAIonlabormarketsandthe

macroeconomy.ManyempiricalstudiessofarhavefocusedlargelyontheUS,findingthatmanyofthetasksofasignificantportionoftheworkforce,includingthoseofhigh-skilledworkers,couldbesubstantiallyreplacedbyAI(forexample,Felten,Raj,andSeamans2021,2023;Eloundouandothers2023;Webb2020).Afew

studies(OECD2023;Albanesiandothers2023;BriggsandKodnani2023)adoptacross-countryapproach;Gmyrek,Berg,andBescond(2023)undertakeacomprehensivereviewofemergingmarketeconomiesandfindlessexposuretoAIthaninadvancedeconomies;Colombo,Mercorio,andMezzanzanica(2019)focusontheItalianlabormarket.Thesestudiesapplyempiricalapproachessimilartothoseusedintheautomation

literature(forexample,AutorandDorn2013,AcemogluandRestrepo2022,DasandHilgenstock2022).

Thisnotecontributestotheexistingliteratureinfoursignificantways.First,whilepreviousAIexposure

measuresoftenimplicitlyequateexposurewithsubstitutabilityofhumantasks,thisnoteattemptstoassessthepotentialforcomplementarityandsubstitutionwithlabor,usingtheapproachdevelopedbyPizzinelliandothers(2023).Thismethodconsidersthewidersocial,ethical,andphysicalcontextofoccupations,alongwith

requiredskilllevels,todiscernwhetherAImaycomplementorreplaceroles.Thisaddstorecentstudiesthathaveattemptedtomakethisdistinctionusingapurelytask-basedframework(AcemogluandRestrepo2018,2022;Gmyrek,Bert,andBescond2023).Second,thenoteofferssomeinitialinsightintothepotentialfor

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workerstomakethetransitionfromoccupationsatriskofdisplacementtothosewithhighAI-complementaritypotential,drawingonmicrodataforoneadvancedandoneemergingmarketeconomy.Third,ittakesadeep

lookathowAImayaffectincomeandwealthinequalitywithincountries.ItdissectsAIexposurepatternsacrossdemographicsandearningslevelsandusesamodel-basedanalysistoevaluateAI'simpactonlaborand

capitalincomeinequality,aswellasonincomelevels.Last,thenoteexamineshowAIpreparednessforthis

technologicalshiftmaydifferacrosscountriesatdifferentincomelevels,usingaverylargesampleofadvancedandemergingmarketanddevelopingeconomies.

Withthisanalysistherearesomeimportantcaveats.First,althoughinthemodelanalysisactivitygrowsinoccupationswithhighAIcomplementarityandfallsinlow-complementarityoccupations—mimickingsectoral

reallocations—theanalysisonAIexposureassumesthatsectorsizesarefixedandthatthetasksrequiredineachoccupationareunchanged.Consequently,theresultsaremorepertinentfortheshorttomediumterm.

Overlongerhorizons,workerswilllikelymigrateacrossdifferentsectorsandroles,oracquirenewskills,andjobswillevolve.Inaddition,theanalysisassumesthatworkerswithinthesameoccupationwillbeaffectedinthesameway,buttherecanbevariationintheeffectsofAI.AImayalsoaffectfirmdynamicsandmarket

concentration(Babinaandothers,forthcoming),drivinginequalitybetweenworkersatdifferentfirms.Second,thestudyreliesonthepremisethattasksperformedwithinsimilaroccupationsarehomogenousaroundthe

world,whiletherecanbesignificantcross-countryvariations.Third,theapproachabstractsfromlinkages

acrossoccupationsandcountries(tradelinkages),aswellasfromcross-borderspilloversofAIexposure.Last,whiletheanalysesonworkers’AIexposureandsocieties’preparednessuseempiricalapproaches,the

potentialimpactsoninequalityandproductivityareanalyzedwithamodel.Thelatterthereforedependon

potentiallystrongcalibrationassumptions.ThepaceofAIadoption,influencedbythetimeneededbyfirmstoinvestinanynecessaryphysicalcapitalandthereorganizationrequiredtocapitalizeonAI,isdifficultto

foresee.Likewise,thetimerequiredtoexertaggregatemacroeconomiceffects,theimpactonintersectoral

reallocationoffactorsforproduction,thebirthofnewindustries,andAI’sexactimplicationsforeconomiesandsocietiesarechallengingtopredict.Anyestimateembodiesalevelofuncertaintyreminiscentofpast

introductionsofgeneral-purposetechnologies,suchaselectricity.Thisuncertaintyappliesalsototheresultsofthisnote.

Theremainderofthenoteisstructuredasfollows.SectionIIillustratestheconceptualframeworkofAIexposureandcomplementarityandattemptstoquantifyempiricallythedegreeofexposuretoand

complementaritywithAIacrosscountriesandgroupsofworkerswithincountries.SectionIIIexamineshoweasilyworkershavehistoricallyshiftedacrossrolesnowfacingvaryingdegreesofAIexposureand

complementarity.SectionIVusesamodeltoprojectpotentialimplicationsofAIadoptionforproductivity,incomes,andinequality.SectionVassessescountries’AIpreparednessinkeypolicyareas.SectionVIconcludesandpresentspolicyconsiderations.

II.AIExposureandComplementarity

II.1ConceptualFramework

AssessingtheimpactofAIonemploymentiscomplexbecauseofitsswiftevolution,uncertaintyin

integrationacrossproductionprocesses,andshiftingsocietalperceptions.GiventherapidadvanceandevolvingcapabilitiesofAI-basedtechnologies,whichproductionprocesseswillintegrateAIandwhichhuman

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taskswillbereplacedorenhancedremainuncertain.Overtime,thechangingsocialacceptabilityofAIcouldalsoaffectitsintegrationintoproductionprocesses.

Thisnoterefinesacommonlyusedconceptualframeworktobettermeasurehumanwork’sexposure

to,andcomplementaritywith,AI.Tostudytheeffectoftechnologicalinnovationonjobs,itisstandardto

conceptualizeindividualoccupationsasabundleoftasksandtoconsiderwhichtaskscanbereplacedor

complementedbytechnology(seeforinstanceAcemogluandRestrepo2022;andMoll,Rachel,andRestrepo2022forrecentapplications).Felten,Raj,andSeamans(2021,2023)define“exposure”toAIasthedegreeofoverlapbetweenAIapplicationsandrequiredhumanabilitiesineachoccupation.Theanalysisrefinesthis

approachbyaugmentingitwithPizzinelliandothers’(2023)indexofpotentialAIcomplementarity.Thisindexleveragesinformationonthesocial,ethical,andphysicalcontextofoccupations,alongwithrequiredskilllevels

(seeBox1fordetails).Theindexreflectsanoccupation’slikelydegreeofshieldingfromAI-drivenjob

displacementand,whenpairedwithhighAIexposure,givesanindicationofAIcomplementaritypotential.Forexample,becauseofadvancesintextualanalysis,judgesarehighlyexposedtoAI,buttheyarealsohighly

shieldedfromdisplacementbecausesocietyiscurrentlyunlikelytodelegatejudicialrulingstounsupervisedAI.Consequently,AIwilllikelycomplementjudges,increasingtheirproductivityratherthanreplacingthem.2

Conversely,clericalworkers,whoarealsoveryexposedtoAIbuthavealowerlevelofshielding,aremoreatriskofbeingdisplaced.Thelevelofshieldingandcomplementaritywilllikelyevolveovertimeandatadifferentpaceacrosscountries,reflectinghigherAIaccuracy,whichwilldecreasethechancesfor“hallucinat