韩国央行（BOK）：人工智能与劳动力市场

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No.2023-30

BANKOFKOREA

BOKISSUENOTE

Nov.16,2023

AIandtheLaborMarket

HanJi-woo*⋅OhSam-il**

▢1Artificialintelligence(AI)hasbeenmakingremarkableadvancesoverthelastdecade,beingemployedacrossvarioussectorsoftheeconomyandisexpectedtohaveanevengreaterimpactinthefuture.WhileAIholdsthepotentialtoimproveproductivity,createnewjobopportunities,italsoraisesconcernsaboutjobdisplacement.ThisreportexamineswhichoccupationsarehighlysusceptibletobeingreplacedbyAIandtheimplicationsofAIforthethelabormarket.

▢2UsingAIpatentinformation,weconstructoccupationalAIexposureindices,revealingthatapproximately3.41millionworkersinSouthKorea(12%oftheworkforce)faceahighpotentialforreplacementbyAItechnology.Unlikeconventionaltechnologieslikerobotsandsoftware,higher-educatedandhigher-incomeoccupationsaremoreexposedtoAI,primarilyduetoitstendencytoreplacenon-routinecognitive(analytic)tasks.

▢3JobswithhigherAIexposurearemorelikelytoexperienceadeclineinwithin-industryemploymentshareandadeclineinwages.Thisprojectionisbasedontheobserveddeclineinbothemploymentsharesandwagesoverthepast20yearsforjobswithhighexposuretorobotsandsoftware.Specifically,a10percentileincreaseintheAIexposureindexcouldpotentiallyleadtoa7%pdecreaseinemploymentshareanda2%pdecreaseinwagegrowthoverthenext20years.

▢4Whilenewtechnologymaydisplaceexistingjobs(displacementeffect),itcanalsocreatenewemploymentopportunities(productivityeffect).Moreover,significantchangesinthewaytasksareperformedwithinexistingjobsmayoccur.ThebenefitofAIasawholewilldependontheadaptabilityofworkers‘skills,andhowpolicymakerschoosetosupportthegroupsthatarehardesthitbythesechanges.

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*LaborMarketResearchTeam,ResearchDepartment(jiwoo.han@bok.or.kr)

**LaborMarketResearchTeam,ResearchDepartment(

samil.oh@bok.or.kr

)

■Disclaimer:Theviewsexpressedhereinarethoseoftheauthors,anddonotnecessarilyreflecttheofficialviewsoftheBankofKorea.Whenreportingorcitingthispaper,theauthors’namesshouldalwaysbeexplicitlystated.

■WethankLeeJungIk,KimHye-jin,ImSun-binandLeeSoo-hyungfortheirhelpfulinputs.Authorsareliabletoanyremainingerrorsinthepaper.

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Ⅰ.Introduction

Artificialintelligence(AI)hasbeenmakingremarkableadvancesoverthelastdecade,beingemployedacrossvarioussectorsoftheeconomyandisexpectedtohaveanevengreaterimpactinthefuture.AI,asatechnology,identifiesstatisticalpatternswithinbig-datasetstoperformspecifictasks.Itdiffersfromconventionalautomationtechnologies(suchasrobotsandsoftware)asitoperatesbasedonpredefinedhuman-providedmethods.AIhasdemonstratedsuperiorperformanceinvariousdomainscomparedtohumancapabilities.Asaresult,inmajorcountries,oneoutofthreecompanieshasalreadyimplementedAItechnology(IBM,2022,<Figure1>).Additionally,surveyresultsindicatethatastaggering42%ofcompaniesplantoincorporateAIutilizationinthenearfuture.

However,theadventofnewtechnologiesinevitablycreateswinnersandlosersinthelabormarket.WhileAIhasthepotentialtobringaboutimprovementsinproductivityandworkenvironments(McKinseyGlobalInstitute,2017),italsocarriesconcernsaboutajoblessfuture(West,2018;Suskind,2020).Inessence,whilesomemaybenefitfromincreasedproductivityduetoAI,othersareatriskoflosingtheirjobs.Therefore,understandingdistributionalconsequencesisimportantformanypurposes.Forexample,itallowspolicymakerstodevelopappropriateeducationandskillpolicies.Inthiscontext,thispaperseeksanswerstothefollowingkeyquestions:

.WhichoccupationsaresusceptibletoAIsubstitution?

.WhataretheimplicationsofAIforthelabormarket?

<Figure1>UtilizationofAI

Source:IBMGlobalAIAdoptionIndex2022.

Ⅱ.RelatedLiterature

AstheutilizationofAIincreased,there'sbeenactiveresearchonwhichjobsaremorelikelytobereplacedbyAI.Notably,studiessuchasWebb(2020)andFeltenetal.(2019)utilizeoccupationalAIexposuremeasures.Specifically,Webb(2020)demonstratedthathigh-skilledandhigh-wagejobsarerelativelymoreexposedtoAIusingthesemeasures.McElheranetal.(2023)presentedsurveyresultsfromU.S.companiesshowingan'AIdivide'acrossdifferentcompanysizes.Meanwhile,Cook(2023)notonlyaddressesjobdisplacementduetoAIadoptionbutalsoemphasizespolicyeffortsforjobtransitions,mentioningrolesthatcouldbecomplementedornewlycreatedbyAItechnology.

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ResearchonAIimpactonjobshasbeenexpandinginlinewiththeexpansioninAIemployment.Fortheinvestigation,occupationalindicatorstomeasureAIexposuredevelopedbyWebb(2020)andFeltenetal.(2019)arepopularlyused.Webb(2020)indicatedthatastheexposureindicestoroboticsandsoftwareincreases,there'sadecreaseinemploymentshareandwagegrowthforthosejobs,suggestinganegativeimpactofAIontheemploymentandwagesofreplaceablejobs.Ontheotherhand,Albanesietal.(2023),utilizingEuropeandata,revealedanincreaseintheemploymentshareofoccupationshighlyexposedtoAI.Thistrendwasparticularlyprominentinoccupationswithahigherrepresentationofyoungindividualsandhighlyskilledworkers.

Meanwhile,concernshavebeenraisedaboutthepotentiallynegativesocietaloutcomesofunregulatedAI,leadingtodiscussionsaboutapproachestoregulateit.WhiteHouse(2022)highlightedconcernsregardingworsenedwageinequalityandethicalissuesarisingfromAI.Acemogluetal.(2023)emphasizedpolicyeffortsaimedatsteeringAItowardsa'human-complementary'pathratherthanevolvingthroughnegativepathwayssuchasworkerdisplacementandreducedbargainingpowerforworkers.TheyalsoarguedthatifAItechnologiesevolvetocreateandsupportnewtasksandskills,itcouldcontributetoreducinginequality.

ThispaperutilizeddomesticdatatoexaminewhichjobsinKoreaarehighlyexposedtoAIandpresentedimplicationsregardingtheimpactofAIonthelabormarket.Specifically,wematchedWebb's(2020)AIexposureindexwithdatafromtheKoreaStandardClassificationofOccupations(KSCO)toidentifyoccupationsexposedtoAI.Additionally,byusingtheexposureindexforrobotandsoftware,weestimatedtheinfluenceofAIontheemploymentandwagesofrelatedjobs.Finally,welaidoutpolicysuggestionsbasedontheseimplications.

Ⅲ.AIExposureIndex

1.ConstructionofoccupationalAIexposureindex

OccupationalAIexposureindiceswereutilizedtoexaminethelikelihoodofcertainjobsbeingreplacedbyAItechnology.Amongtherelevantliterature,thedatafromWebb(2020)andFeltonetal.(2019)havebeenwidelyreferenced.ThisstudyisbasedonWebb(2020)tocalculatethedomesticoccupationalAIexposureindices1).Webb's(2020)dataprovidesexposureindicesnotonlyforAItechnologybutalsoforwell-establishedtechnologiessuchasrobotsandsoftware.

TheoccupationalAIexposureindexindicatestheextenttowhichtasksthatcan

1)Asexplainedin<Box1>,theoccupationalimpactmeasuresofWebb(2020)andFeltenetal.(2019)aresimilar.Therefore,theresultsobtainedusingthelatter'sapproachwouldnothavesignificantlydifferedfromourfindingsbasedontheformer.

currentlybeperformedbyAItechnologyareconcentratedwithinthejob'stasks2).Sinceasingleoccupationinvolvesvarioustasks,theAIexposureindexisinitiallymeasuredatthetasklevel.TogaugehowreplaceableaspecifictaskisbyAItechnology,weexaminetheoverlapbetweenjobdescriptionsandAI-relatedpatenttitlesusingverb-nounpairs(<Figure2>)3).Forinstance,oneoftheprimarytasksofadoctoris‘diagnosepatient’scondition.’Tocalculatetheexposureindex,weinvestigatehowmanyAIpatentscontainthephrase

condition.’After

indices,wethen

measuringcalculate

‘diagnose

task-based

occupation-basedindicesusingspecifictaskweightsforaparticularoccupation.Additionally,toobtaindomesticoccupational

AIexposureindices,weconvertedtheAIexposureindicesbasedontheUSOccupationalInformationNetwork(O*NET)

<Figure2>ConstructingAIexposureindex

totheKoreanStandardClassificationofOccupations(KSCO,sub-categories)4).

Meanwhile,toanticipatetheimpactofAIonthelabormarketinfutureanalyses,occupationalexposureindicesforrobotsandsoftware,whichsignificantlyaffectthelabormarket,werealsocomputed.Weemployedthesameapproach,leveragingthetextsofjobdescriptionsandcorrespondingpatentsonrobotandsoftwaretechnologies(Webb,2020).OccupationalexposureindicesforrobotsandAIdonotdisplayasignificantlinearcorrelation(<Figure3>).ThisimpliesthatthejobsreplacedbyrobotsdifferfromthosereplacedbyAI.Conversely,softwareexposureindicesshowarelativelystrongcorrelationwithAIexposureindices(<Figure4>).AI,oncelearningalgorithmsaresetbyhumans,autonomouslylearnsfromdataorexperimentstoachievespecificgoals,whereassoftwareoperatesbasedonrules('if-then')definedbyprogrammers5).Software

Source:Webb(2020).

2)RefertoWebb(2020)fordetailsonthemeasurement.

3)Webb(2020)usesjobdescriptionsfromtheO*NETdatabaseandpatentsfromtheGooglePatentsPublicData.

4)O*NETisrevisedtocomplywiththeInternationalStandardClassificationofOccupations(ISCO)andthencomparedtotheKoreantaxonomyonoccupationsknownasKSCO.Ininstanceswherea1:Npropensitymatchingispossible,wematchthenearestoccupationthroughanaggregateaverageofvariousoccupations.Whenmatchingisn'tpossible,wefindtheclosesttaskstomatchtheoccupation.

5)Softwarehandlesroutineinformationprocessing,whileAIcanundertakenon-routinetasks.

。

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islimitedtorepetitive(routine)tasks,whileAIcanextendtonon-repetitive(non-routine)tasks.However,thereareinstanceswherethedistinctionbetweenAIandsoftware,suchasinautonomousdrivingtechnology,isnotclear.MeaningfulcorrelationsbetweensoftwareandAIexposureindicesseemtoemergeduetotheintersectionbetweenthesetwotechnologies.

<Figure3>AIandrobotexposuresbyoccupation1)

Note:1)Thedottedlineisthetrendline.

Source:Authors’calculation.

<Figure4>AIandsoftwareexposuresbyoccupation1)

Note:1)Dottedlineisatrendline.

Source:Authors’calculation.

2.WhichoccupationsaresusceptibletoAIsubstitution?

Amongdomesticjobs,anestimated3.41millionpositions(12%ofalljobs)aredeemedsusceptibletoreplacementbyAI.Thisestimationisderivedfromidentifyingoccupationswithinthetop20%ofAIexposureindicesandsummingupthenumberofworkersengagedintheseoccupations.Ontheotherhand,expandingthethresholdtothetop25%wouldincreasethesevulnerablepositionstoaround3.98million(14%ofalljobs).

TheoccupationswiththehighestAIexposureindicesincludechemicalengineers,powerplantoperators,trainorsubwaydrivers,sewagetreatmenttechnicians,wasterecyclingtechnicians,andmetallurgicalengineers.6)(<Table1>).Thesejobsarewell-suitedforoptimizingtasksusinglarge-scaledata.Forinstance,chemicalengineersareinvolvedindesigningandoperatingproductionprocesses,whereAIalgorithmscouldpotentiallyreplaceengineersintasksrelatedtoprocessoptimization.Conversely,jobswiththelowestAIexposureindices,suchassimpleserviceworkersorthoseinreligiousoccupations,requireessentialface-to-facecontactandrelationshipbuilding.

6)InAIexposurebywagepercentile,well-paidandhigh-skilledoccupationssuchasgeneraldoctors,whoareinthetop1%earners,specializeddoctorsinthetop7%,accountantsinthetop19%,assetmanagersinthetop19%,andlawyersinthetop21%,scorehigh.Journalists(attop86%),clergies(attop98%),universityprofessors(top98%),popandclassicalsingers(top99%)showlowAIexposurescores.Themostandleastexposedoccupationstorobotsandsoftwarearelistedin<Box2>.

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<Figure5>AIexposurepercentile

Source:KLIPS,authors’calculation.

<Table1>MostandleastAI-exposed

occupations1)

Most-exposed

Least-exposed

chemicalengineer

powerplantoperator

trainorsubwaydriver

sewagetreatment

technician

wasterecycling

technician

metallurgicalengineer

foodpreparation

service

universityprofessor,

lecturer

rentalsalesagent

clergy

foodandbeverage

serviceworker

transportationserviceworker

Note:1)Basedonoccupationsub-categorization(153).

Source:Authors’calculation.

Byindustry,high-productivitysectorsICT,professionalscienceandtechnology,andmanufacturingsectorsexhibitednotablyhighAIexposureindices(<Figure6>).Inrecenttimes,AItechnologyhasbeenextensivelyutilizedinwirelessnetworkswithinthetelecommunicationssector,equipmentmonitoringsolutionsinmanufacturing,andmore7).Conversely,industriesinvolvingin-personservicessuchashospitalityanddining,arts,sports,andleisurecategories

exhibitedasexpected,lowerAIexposureindices.Comparedtoothersectors,theAIexposureindexwasrelativelylowerinaccommodationandfoodservices,whereasitwashigherinICT(<Figure7>).

<Figure6>AIexposurebyindustry

Source:KLIPS,authors’calculation

<Figure7>Exposuretotechnologiesbyindustry

Source:KLIPS,authors’calculation

Regardingwageandeducationlevels,higher-educatedandhigher-incomeworkerstendtohavegreaterexposuretoAI(<Figures8,9>).Thisnotablydiffersfromothertechnologieslikerobotsandsoftware,whichhadamoresignificantimpactonlower-educated(highschoolorbelow)andmid-incomeworkers.It'sestimatedthat

7)InKorea,AIisbeingusedtoinspectnewcarbodiesandmonitorchipfabprocessing.

occupationsperformingnon-routinecognitiveanalytictasks,whichAIcansubstituteforinnon-routinecognitivetasks8),aremoreexposedtoAI.There'saconsiderableriskofAIsubstitutioninhigh-educatedandhigh-incomejobs.ThissuggeststheimpactonthelabormarketfromwiderAIadoptioncanpanoutindifferentformthanearliertechnologies.

<Figure8>Technologyexposureby

educationlevel

Sources:KLIPS,authors’calculation.

<Figure9>Technologyexposurebywagepercentile1)

Note:1)Locallyweightedsmoothingregression.(bandwith0.8)

Source:KLIPS,authors’calculation.

Whenexamininggender,theAIexposureindexformalejobsappearsslightlyhighercomparedtofemalejobs.Similartoindustrialrobotsorsoftwaretechnologies,malejobsshowgreaterexposuretoAI,possiblyduetoarelativelyhigherfemalepresenceinface-to-faceserviceindustries,whichtendtohavelowerAIexposureindices.However,therewasn'tacleardistinctionobservedinAIexposureindicesacrossdifferentagegroups.

<Figure10>Technologyexposureby

gender

Sources:KLIPS,authors’calculation.

<Figure11>Technologyexposurebyage

Source:KLIPS,authors’calculation

8)Webb(2020)presentstheaverageofstandardizedoccupation-levelexposurescoresbyweightedtasksusingalocallyweightedsmoothingregression(<Box3>).Non-routinecognitivetasksareassumedtobemoreexposedtoAI.

。

Ⅳ.AIimpactonthelabormarket

AIisarapidlyadvancingtechnology,anditsutilizationbybusinessesisstillinitsearlystages9).Therefore,rigorouslyanalyzingtheimpactofAIonthelabormarketatthisstageischallenging.There'ssignificantuncertaintyabouthowAItechnologywillevolveinthefutureandhowitwillintegrateintoindividualindustries.Forinstance,recentadvancementsingenerativeAI,liketheadventofChatGPT,signifytheswiftdevelopmentinAI-relatedtechnologies.Additionally,theregulationsurroundingAIremainsasubjectofongoingdebate.

Thedevelopmenthasstokedaflurryofstudiesonthepotentialimpactonthelaborwithdataattainablesofar.Acemogluetal.(2020)discoversfromdataononlinevacanciesthatAI-exposedestablishmentsreducehiringinnon-AIpositionsaswellasoverallnewhiringtosuggestAIisalteringthetaskstructureofjobsandhiringscaleinlinewithAIsubstitution10).Huietal.(2023)observesshort-termimpactofreduceddemandandearningsforknowledgeworkersfromthereleaseofthelargelanguagemodelChatGPT.Webb(2020)postulatesAIadoptioncouldbringaboutdeclinesinwithin-employmentandwagefromtheexposuretothenewtechnologyinthe

samehistoricpatternwiththeadoptionofindustrialrobotsandsoftware.

UtilizingthemethodologyoutlinedbyWebb(2020),thisstudyexaminedtheimpactoftheonsetofrobotsandsoftwareonthedomesticlabormarket,aimingtoinferthepotentialimplicationsofAIadoption.Specifically,empiricalanalyseswereconductedtoinvestigatetheimpactofrobotsandsoftwareintroductiononemploymentandwagesoverthepasttwodecades(2000to2021).Regressionequationswereestimatedbycomparingoccupation-industry-yearcells(basedonindustryandoccupationmid-classifications)between2000and2021.

Δyo,i,t=ai+BE从posureo+出Zo,i+Eo,i,t

Δyo,i,tdenotesthechangesinemploymentandwagebetween2000and2021.Tomeasurethechangeinemployment,wemultiplied100totheDHSchange11)ofemploymentsharesbetween2000and2021cells.Toidentifythechangeinwages,wemultiplied100tothelogdifferenceoftheaverageofwagesineachcellunit.E从posureoistheexposureoftheoccupationtorobotsorsoftware,Zo,icontainstheindustryfixedeffectsandwage

9)AccordingtotheMckinseyGlobalSurvey(2023),theadoptionofAIincompanieshasmorethandoubledfrom20%in2017to50%in2022.Additionally,40%ofrespondentsstatedthattheirorganizationswouldfurtherincreaseinvestmentinAI.

10)Acemogluetal.(2020)concludethatdespitethesurgeinAIadoption,itsimpactremainsrelativelysmallincomparisontothescaleoftheUSlabormarket,thusnotsignificantlyaffectingemploymentpatternsbeyondAI-relatedhiringitself.

11)DHSisasymmetricmeasureofthegrowthratedefinedasthedifferenceoftwovaluess1,sodividedintheformof2×(s1—so)/(s1+so).BasedontheliteratureDavisetal.(1996),WebbusesDHSchangeinsteadoflogchangetoreflectzero-valuedobservationssuchasnewandobsoletejobs.

,

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levelofoccupations(basedon2000data).TheanalyticaldatautilizedtheKoreaLaborandIncomePanelStudy(KLIPS)12).Inthecaseofrobots,duetolimitedutilizationintheservicesector,theestimationwasrestrictedtothemanufacturingindustry.Asforsoftware,theestimationwasconductedacrosswholeindustries.

Regardingrobots,itwasobservedthatwhentheexposureindexincreasesbythe10thpercentile,employmentsharedecreasesby12%p,andthewagegrowthratedecreasesby5%p.Sincetheobservationisbasedonwithin-industryeffect,specificmanufacturingoccupationexposedtorobotsweremoreaffectedthanthoseunexposedtoautomation.ThisalignswiththefindingsofAcemoglu&Restrepo(2020)regardingtheemploymentandwagereductionsduetorobots.Webb(2020)alsodemonstrated,usingU.S.data,thatjobswithhigherexposureindicestorobotsshowsignificantdecreasesinemploymentshareandwagegrowth.However,incomparisontotheU.S.,thereductioninemploymentandtheslowdowninwagegrowthduetotheintroductionofrobotsappearedrelativelymorepronouncedinKorea13).ThisdifferenceisattributedtoKorea'sleadingpositionintheadoptionofrobotsinmanufacturingglobally.Korea'shighutilizationofrobots,

particularlyinsectorslikesemiconductorsandautomobiles,appearstohavesignificantlyimpactedthelabormarket14).

<Table2>Estimationresults:robots1)

Employment

Wage

(1)

(2)

(1)

(2)

E①pOSUTe

-1.194***

-1.166***

-0.018

-0.462***

Wage

-2.236*

-0.816*

Wage2

0.012**

0.000

Industry

fixed

effects

O

O

O

O

Ra2dj

0.352

0.392

0.188

0.545

Samples

63

63

63

63

Note:1)*p自O.1O,**p自O.O5,***p自O.O1.

Sources:KLIPS,authors’calculation.

Withsoftware,10thpercentileofexposurerelatestodeclinesof7%pinwithin-industryemploymentshareand2%pinwagegrowthrate.TheresultsonceagainarecongruouswiththefindingwithU.S.datainWebb(2020).However,theestimatednegativeimpactonthelabormarketappearedtoberelativelysmallercomparedtotheeffectsofrobots.

12)AlthoughtheEconomicalActivePopulationSurveyhasgreaternumberofsamples,itonlyprovidesindustrialandoccupationalinformationinbigcategories.

13)IntheUS,10thpercentileexposuretorobotsisassociatedwith3.6%pdropinwithin-industryemploymentshareand2.8%fallinwagegrowthrate(Webb,2020).

14)IntheWorldRobotics2022ReportofInternationalFederationofRobotics(IFR),themanufacturingsectorinSouthKoreaemploys1,000industrialrobotsper10,000employeesin2021.Singapore,rankingsecond,utilizes670robotsper10,000employees,whileJapan,rankedthird,employs399industrialrobotsper10,000employees,showcasingasignificantdifferencecomparedtoSouthKorea.

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<Table3>Estimationresults:software1)

Employment

Wage

(1)

(2)

(1)

(2)

E①pOSUTe

-0.730**

-0.735***

-0.208

-0.235*

Wage

-0.916

-1.344***

Wage2

0.005*

0.003**

Industry

fixed

effects

O

O

O

O

Ra2dj

0.218

0.236

0.115

0.428

Samples

154

154

154

154

Note:1)*p自O.1O,**p自O.O5,***p自O.O1.

Source:KLIPS,authors’calculation.

Consideringthedecreaseinrelevantjobsandthedecreasedwagegrowthfromtheadoptionofrobotsandsoftware,AIcanbringaboutsimilarnegativeimpactonthejobssusceptibletoAIsubstitution.Basedonthepositivecorrelationwithsoftware,wecanassume10thpercentileexposuretoAIcanlowersector-employmentshareby7%pandslowwagegrowthrateby2%p15).

However,newtechnologynotonlydisplacesexistingjobsbutalsocreatesnewones.There'sanincreaseinhigh-productivityjobsinvolvedindevelopingandmaintainingAItechnology,includingstartupsfocusedonAI-relatedinnovations.Moreover,theproductivityboostduetoAIcouldleadtooverallincreasedlabordemandandwagegrowth.Nevertheless,sinceproductivityimprovementimpactontheoveralleconomyfromtechnologydiffusioncanbelimited,whereasthedisplacementisconcentratedoncertaingroups,concerningworkerscanfacehardshipinrelocationafterAItakesovertheirjobs.

Ⅴ.Otherissues

1.Wageinequality

VariousdiscussionsexistregardinghowAImightinfluencewageinequality.ThisstudycalculatedthechangesinwagedistributionresultingfromAIadoption,basedontheestimationthatthere'sanegativerelationshipbetweentheAIexposureindexandwagegrowth(Webb,2020).UsingtheAIexposureindexbyoccupationalclassificationsandwagedata(asof2021),thestudycalculatedtheoccupationalwagelevels(山age*e—B.e①pOSUTe)16).Subsequently,itdeterminedthewagedistributionacrossoccupationstoderivethe90:10ratiosandtheGiniindex.

Thesimulationresultsindicatedareductioninboththe90:10ratios17)andtheGinicoefficient,suggestingamitigatedwageinequalityduetoAIimplementation.Accordingto<Figure12>,assumingasimilarwageelasticitytothatofsoftware,the90:10ratioisestimatedtodecreaseby7%followingAIadoption.Furthermore,theGinicoefficientisprojectedtodecreasefrom0.20to0.18withthediffusionofAI(<Figure13>).

15)However,it'sessentialtonotethatthesefindingsmayvarybasedonthedevelopmenttrajectoryofAItechnologyandthei