世界经济论坛-未来的工作：大型语言模型和工作-一个商业工具包（英）

IncollaborationwithAccentureJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkitWHITEPAPERDECEMBER2023Images:GettyImagesContentsForeword34ExecutivesummaryIntroduction51Consideration1:Jobchangeandjobdisplacementrisk1.1Responsiblebusinessstrategies2Consideration2:Jobquality2.1Responsiblebusinessstrategies3Consideration3:Skillingandlearning3.1ResponsiblebusinessstrategiesConclusion789101112131415ContributorsEndnotesDisclaimerThisdocumentispublishedbytheWorldEconomicForumasacontributiontoaproject,insightareaorinteraction.Thefindings,interpretationsandconclusionsexpressedhereinarearesultofacollaborativeprocessfacilitatedandendorsedbytheWorldEconomicForumbutwhoseresultsdonotnecessarilyrepresenttheviewsoftheWorldEconomicForum,northeentiretyofitsMembers,Partnersorotherstakeholders.©2023WorldEconomicForum.Allrightsreserved.Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,includingphotocopyingandrecording,orbyanyinformationstorageandretrievalsystem.JobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit2December2023JobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkitForewordMaryKateMorleyRyanElselotHasselaarTalentandOrganization/HumanPotentialManagingDirector,AccentureHeadofMission,Work,WagesandJobCreation,WorldEconomicForumGenerativeartificialintelligence(AI)and,inparticular,largelanguagemodels(LLMs),underpinnedbyadvancementsinmachinelearningandnaturallanguageprocessing,representaparadigmshiftinhowweinteractwithinformationand,byextension,howwework.Thesetechnologiescancreateoriginalcontent,generateinsightsfromlargeamountsofdata,translatelanguageswithnear-humanaccuracyandpotentiallyevenmakecomplexdecisions.Theversatilityandefficiencyofthesetechnologies,includingnewLLM-poweredhuman-machineinterfacessuchasintelligentagents,couldhaveprofoundimplicationsforjobsandthefutureofwork.initiativeincuratingstrategiesandpracticesthatfacilitateLLMstoworkforbusinesses,employeesandsocietyasawhole.Thispaperisadirectfollow-uponthepreviouseditionoftheJobsofTomorrowseries,JobsofTomorrow:LargeLanguageModelsandJobs,whichtookastructuredapproachtounderstandingthedirectimpactofLLMsonspecificjobs.ThatpaperprovidedastructuredanalysisofthepotentialimpactofLLMsonjobs,enablingstakeholders–businessleaders,policy-makers,workersandthebroaderpublic–tomakemoreinformeddecisions.Inaddition,thestructuredapproachproposedinthatpaperalsoprovidedacasestudyforfuturewavesoftechnologicaladvancementacrosssectors.WhiletheapplicationofLLMscouldleadtosignificantproductivitygainsandthecreationofnewtypesofjobs,thereisalsoariskthattheycoulddisplaceexistingroles,exacerbatingsocioeconomicdisparitiesandcreatingasenseofjobinsecurityamongtheglobalworkforce.Assuch,integratingAIintoourworkplacesisabalancingactbetweenseizingopportunitiesandmanagingpotentialdisruptions.WearedeeplygratefultotheCentrefortheNewEconomyandSocietypartnersandconstituentsfortheirleadershipofthejobsagenda,aswellasforthepartnershipoftheAccentureteam,whosemembersservedascorecollaboratorsonthispaper.TheinsightsofthispaperwillbeinstrumentalfortheJobsConsortium,aglobalcoalitionofministersandchiefexecutiveofficersthatpromotesabetterfutureofwork,throughboostinglabourmarketforesight,drivingjobcreationandimprovingjobqualitywhileenablingjobtransitionsandwillserveasakeytoolfortheGoodWorkAlliance,aglobal,cross-industrygroupofbusinessescommittedtoprioritizinggoodworkinanevolvingjobslandscape.Thispaperisintendedtoserveasatoolkitforbusinessestoprovideguidanceonstrategiestomaximizethepotentialofemployeesastheyadapt,learnandgrowwiththesetechnologiesintheirprofessionalcareers.ThispaperalsoservesasacalltoactionforbusinessleaderstotaketheJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit3ExecutivesummaryBusinesseswillneedtostrategicallynavigateconcernsoverjobdisplacementrisk,jobqualityandskilling.Theexplosivepopularityandaccessibilityofgenerativeartificialintelligence(AI)technologies,suchasGitHub’sCopilot,MidjourneyandChatGPT,haveproducedAI’sfirsttrueinflexionpointinpublicadoption,demonstratingthetechnology’stransformativepotential.WhiletherearemyriadpossibleusecasesforgenerativeAI,includingimage,video,writtenlanguageandmusiccreation,largelanguagemodels(LLMs)haveanoutsizedpotentialtoimpactthegreatestnumberofjobsinthenearfuture.Jobsemphasizingface-to-faceinteractionarelikelytobelessaffected.Businessesareurgedtoadoptproactiveandresponsibleapproachestomanagethistransformation,addressingconcernslikejobchangeandjobdisplacementrisk,jobqualityandskilling.Structuredanalysis,planningandproactivepreparationarerequiredofbusinessleaderstoensurethatLLMsandothertechnologicaladvancementsleadtoanimprovedfutureofworkwithnewopportunitiesforworkers.Thispaperservesasatoolkitforbusinesses,providingpracticalstrategiestonavigatethechangingjoblandscapeinthreeprimaryareasofconsideration:1)jobchangeandjobdisplacementrisk,2)jobquality,and3)learningandskilling.Eachoftheseconsiderationsisaddressedthroughbusinesspracticesguidedbythreefundamentalapproaches:1)promotingworkerawareness,2)facilitatingorganizationalchange,and3)shiftingworkplacenormsandculture.Theresultisabusinessstrategymatrixforeffectivelyleadingtheworkforcetransitionthroughthelarge-scaledeploymentofLLMs.TheFutureofJobsReport2023statesthatglobalbusinessleadersbelievethat23%ofglobaljobsareexpectedtotransformwithinthenextfiveyearsduetorapidtechnologicaladvances,particularlyingenerativeAItechnologies.Especially,LLM’shavethepotentialforbothautomatingandaugmentingtasksacrossvariousoccupations.TheJobsofTomorrow:LargeLanguageModelsandJobswhitepaper,publishedbytheWorldEconomicForumandAccentureearlierin2023,foundthat40%ofworkinghourscouldbetransformed,affectingrolesfromspecializedfieldsrequiringadvanceddegreestothosefocusedonroutineprocedures.JobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit4IntroductionUpto40%ofworkinghourscouldbetransformedbyLLMs–businessesmusttakethelead.Technologyisrapidlytransformingthelabourmarket.TheFutureofJobsReport2023foundthatglobalbusinessleadersexpect23%ofcurrentpoint,demonstratingthetechnology’stransformativepotential.OneweekintoitsNovember2022launch,ChatGPT,OpenAI’strainedlanguagemodel,reachedonemillionusers.ByJanuary,ChatGPThadreachedonehundredmillionmonthlyactiveusers,makingitthefastest-growingconsumerjobstotransformwithinthenextfiveyears.This1transformationisdrivenbykeytrendsliketechnologyadoption,thegreentransitionandtheglobalmacroeconomicoutlook.Inparticular,technologyadoptionisdrivingchangeinlabourmarkets:82%ofbusinessleadersexpectincreasedadoptionofnewtechnologiestodrivebusinesstransformation,while37%ofbusinessleadersanticipatethatnewtechnologieswillbeanetjobcreator,and21%believethattheywillbeanetjobdisplacer.applicationinhistoryatthetime.3Generativetransformermodelshavetheabilitytoimpactallclassesofcreativework,possessingthecapabilitytogeneratenovelimages,videos,music,soundsandwrittenlanguage.WhiletherearemyriadpossibleusecasesforgenerativeAI,largelanguagemodels(LLMs)andtheiruniquelanguage-generatingcapabilitieshaveanoutsizedpotentialtoimpactthegreatestnumberofjobsinthenearfuture.LLMs,suchasthosepoweringChatGPT,havedemonstratedthisrapiddevelopmentandhavethepotentialtoimpactmanyjobsandworkersacrossindustries.InSeptember2023,toincreaseunderstandingofhowLLMscouldimpactjobs,theWorldEconomicForum,incollaborationwithAccenture,publishedtheJobsofTomorrow:LargeLanguageModelsandJobswhitepaper.ItprovidesastructuredanalysisofthepotentialThroughout2023,specifically,generativeartificialintelligence(AI)hasdevelopedatarapidpaceintermsofcapabilitiesandadoption,andthatpaceshowsnosignsofslowingdown.Infact,threeoutofeveryfourcompaniesacrosstheglobeareexpectedtoadopttechnologiesthatincludegenerativeAIinthenext3to5years,and98%ofglobalexecutivesagreeAIfoundationmodelswillplayanimportantroleintheirorganizations’strategiesinthatsametimeperiod.2GitHub’sCopilot,MidjourneyandChatGPTareacaseinJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit5Over40%ofworkingimpactofLLMsonjobsandfindsthatitwillbothautomateandaugmentjobtasks,ultimatelyhavingatransformativeeffectonjobs.potentialforjobtransformationasfoundbytheJobsofTomorrow:LargeLanguageModelsandJobswhitepaper,itiscriticalthatbusinessesadoptaproactive,human-centredandresponsibleapproachtoLLMs.hourscouldbetransformedbyLLMsthroughautomationoraugmentation.TheSeptember2023whitepaperfoundthatanestimated62%oftotalworktimeacrossoccupationsinvolveslanguage-basedtasks–tasksthatcouldbeexposedtothepotentialimpactsofLLMs.Over19,000individualtasksacross867occupationswereassessedtounderstandthepotentialexposureofeachtasktoLLMadoption,classifyingthemastaskswithhighpotentialforautomation(thetaskcouldbeperformedbyLLMs,withouthumans),highpotentialforaugmentation(thetaskwillcontinuetobeperformedbyhumans,withLLMsincreasinghumanproductivity),lowpotentialforeither(humanswillcontinuetoperformthetaskwithnosignificantimpactfromLLMs)orunaffected(non-languagetasks).Thiswhitepaperisafollow-uptotheJobsofTomorrow:LargeLanguageModelsandJobspaperandservesasatoolkitforbusinessestoaddressthreeconsiderationsforthetechnologicaltransformationoflabourmarketstocome.Thefirstisjobchangeandjobdisplacementrisk:asLLMsarecapableofperformingmanyofthelanguagetasksusedonthejob,andupto60%ofworktimeuseslanguagetasks,thereispotentialforsomejobstobedisplacedasothersemerge.Thesecondisjobquality:thedeploymentofthesetechnologicaltoolscouldaffectnotonlythenumberofjobsbutalsothenatureoftheworkitself,potentiallyaffectingthemeaningfulnessofwork,thewell-beingofworkersandthediversityassociatedwithnewandlegacyroles.Thethirdconcernislearningandskilling:toadjusttoandembracetechnologicalchangerequirescontinuouslearning;anagileworkforceisthebestapproachtomeettheevolvingdemandsofthelabourmarket.Theanalysisfoundthatover40%ofworkinghourscouldbetransformedbyLLMsthroughautomationoraugmentation.Jobswiththehighestpotentialforautomationoftasksincludethosethatemphasizeroutineandrepetitiveproceduresanddonotrequireahighdegreeofinterpersonalcommunication,includingmanyclericaloccupations.JobswiththehighestpotentialforaugmentationbyLLMsarethosethatemphasizecriticalthinkingandcomplexproblem-solvingskills,especiallythoseinscience,technology,engineeringandmathematics(STEM)fields.Theyincludeamixofhighlyspecializedrolesoftenrequiringadvanceddegrees,suchascomputerprogrammers,plusrolesthatrequirehumanvalidation,suchasassessors,monitorsandscreeners.Jobsemphasizingface-to-facecommunicationandinterpersonalinteractionsareexpectedtobelessexposedtotheimpactsofLLMs,andthoseemphasizingnon-languagetaskswillbeevenlessexposedornotexposedInthefollowingsections,eachconsiderationisfirstdefinedandthenaddressedwithseveralpracticalbusinessstrategiesthatensureacohesiveandinclusiveapproachtotherapidlychangingjoblandscape.Thiswhitepaperproposesthatthebusinessstrategiesfallintothreeprimaryapproaches:1)promotingworkerawareness,whichinvolvesinformingandeducatingemployeesaboutthepotentialimpactsofLLMsontheircurrentrolesandfuturejobprospects,empoweringthemtoproactivelyengagewiththeevolvingtechnologicallandscape,2)facilitatingorganizationalchange,inwhichcompaniesadapttheirstructures,processesandstrategiestoharnessthebenefitsofnewtechnologieswhilemitigatingtherisksassociatedwithsuchtransformations,and3)shiftingworkplacenormsandculture,toreshapetheunderlyingattitudes,behavioursandvalueswithintheatall.Lastly,thepaperalsofoundthatnewjobs4couldemerge,forexample,AImodelandpromptengineers,interfaceandinteractiondesigners,AIcontentcreators,datacuratorsandtrainers,andethicsandgovernancespecialists.workplacetopromoteagilityinresponsivenesstochange.Table1summarizesthekeyconsiderationsandproposedbusinessstrategies.GiventhelikelyubiquitousimplementationofLLMsinbusinessenvironments,pairedwithitsTABLE1SummaryofbusinessstrategiesineachoftheprimarythreeconcernsJobchangeandjobdisplacementriskJobqualitySkillingandlearningWorkerawareness1Deployproactiveforecastingandcommunicateexpectations4EnsureinclusivedesignofAIandLLMapplications7RolloutbroadLLMliteracyprogrammesalongsideAI-specificjobsOrganizationalchange2Setupandmakeuseofinternaljobmarkets5ImplementtransparentgovernancestructuresforLLMdeployment8Applyaskill-firstapproachorganizationwideShiftingnormsandculture3Createincreasedworkforceagility6IncreaseawarenessofLLMbenefitsintheworkplace9OfferworkplacelearningopportunitiesJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit6Consideration1Jobchangeandjobdisplacementrisk1Proactivelyaddressingjobchangeandjobdisplacementriskthroughinternaljobmarketsandworkeragilityensuressmoothtransitionsforemployees.ConcernshavearisenthatthelatestwaveofforaugmentationbyLLMs,meaningthesegenerativeAItechnologies,specificallyLLMs,couldleadtotheautomationofjobtasksand,ultimately,jobloss.Whilelabourmarketpredictionsarenever100%certain,recentWorldEconomicForumresearchtookastructuredapproachandfoundthattheadoptionofLLMscouldautomatesometaskstechnologieswillassistintaskexecutionandboostindividualproductivity.Additionally,thepaperfoundthereispotentialtogeneratenewemploymentopportunitiesbycreatingrolesthatoversee,complementandenhanceAI’scapabilities.andaugmentothers.5TheFutureofJobsReport2023echoesmanyofthesefindings,indicatingthatmanyofthejobswithhighpotentialforautomationbyLLMswerealsoexpectedbybusinessleaderstoundergoemploymentdeclinewithinthenextfiveyears,suchasbanktellersandrelatedclerks,dataentryclerks,andadministrativeandexecutivesecretaries.Jobswithhigherpotentialforaugmentationareexpectedtogrow,suchasAIandmachinelearningspecialists,dataanalystsandscientists,anddatabaseandnetworkprofessionals.TheWorldEconomicForum’sJobsofTomorrow:LargeLanguageModelsandJobswhitepaperfoundthatjobtaskswiththehighestpotentialforautomationbyLLMstendtobethosethatuselanguageinaroutineandrepetitivemanner.WhileLLMswillimpacttasks–ratherthanjobsasawhole–jobsemphasizingthesetypesoflanguagetaskscouldseeadecline,withsomeworkersawareofthispotential.Forexample,overthecourseofQ3of2023,globalsearchesfor“Ismyjobsafe?”doubled,indicatingthepublic’sincreasingconcernaboutwhetherLLMswouldJobtasksemphasizingabstractreasoningandproblem-solvingskillshavethehighestpotentialforaugmentationbyLLMs,meaningthesetechnologieswillassistintaskexecutionandboostindividualproductivity.Nevertheless,labourmarketpredictionsarenevercompletelycertainandwilllikelyevolvewiththedevelopmentofLLMs.Businessesmustbeproactivelyengagedinaddressingtheconcernsoftheirworkerswhilepreparingthemtoadapttothetransitiontocome.automatetheirjobs.However,LLMsandother6generativeAItechnologiesofferpotentialforjobgrowthaswell.Thesamepaperfoundthatjobtasksemphasizingabstractreasoningandproblem-solvingskillshavethehighestpotential1.1ResponsiblebusinessstrategiesWorkerawareness–deploychancetogrow.Enablinginternalmobilitynotonlyrewardsloyalemployees,itenablesfirmstoaddresstheirtalentshortageswhilemitigatingcosts.About60%ofcompaniesgloballynotethatskillsgapsareamajorlimitationtobusinesstransformation.12Replacingworkersiscostly:Gallupestimatesthatthereplacementcostcanexceedtwotimesanemployee’sannualsalary.13Retainingexperiencedworkersthroughjobtransitionsontheinternaljobmarketreducestotalhiringcostsandincreasesthespeedatwhichpeoplecontributevaluetoanorganization.proactiveforecastingandcommunicateexpectationsUsingpredictiveanalyticstoforecastwhichjobswillmostlikelybeaffectedbyLLMsandotherdisruptions,andcommunicatingactivelywithmanagementandemployeestoproactivelyprovidepathwaystomitigatenegativeemploymentimpacts.–Organizationshavetheabilityandresponsibilitytosupportworkersthroughjobchangesanddisruptions.Equippingemployeeswiththerightknowledgeempowersthemtomakebetter–HSBC,aglobalfinancialservicesorganizationbasedintheUK,deployedaninternaljobmarketforabout200,000ofitsemployeeswithplanstoexpandaccesstoall220,000employeesaroundtheworld.Theyestimatethattheirinternaltalentmarketplaceiscentraltotheirskill-buildingstrategyandhasunlockedover170,000hoursofwork.Furthermore,about45%ofprojectsarecross-functional.14decisionsinsearchingforreskillingopportunities7ortransitioningtoadifferentjoborcareer.Clearlysharingdataandmethodswillalsoincreasetrustandimproveemployeewell-being,performanceandbusinessaccountability.AnalyseslikeJobs8ofTomorrow:LargeLanguageModelsandJobsproviderealisticassessmentsofthelabourmarketandcanhelpshapeexpectationsintheshortterm.OrganizationscanusetheresultsofthesestudiesorapplysimilaranalysismethodstounderstandhowLLMscouldtransformtheirbusinessandtheworkoftheiremployees.Shiftingnormsandculture–createincreasedworkforceagility–In2019,SingaporelauncheditsNationalAIStrategy,whichincludesadditionalskillingandeducationprogrammestosupportworkers–particularlyrelevantasa2018reportbyCiscoandOxfordEconomicsfoundthatSingaporehadthemostrelativeexposureofsixASEANcountriestopotentialjobdisplacementeffectsofAI,with7in10workersinSingaporeCreateacompanyculturethatvaluesandrewardsflexibilityinjobroles,encouragingemployeestoembracediverseworkexperiencesandinterdisciplinaryskilldevelopment,whichcouldreducetheanxietyaroundjobdisplacementandpromotearesilientworkforce.–Bycultivatingaculturethatvaluesworkforceagility,employeesbecomemoreadaptableandresilient,betterequippedtotransitionintonewrolesasLLMsimpactjobmarkets.Creatingsuchacompanycultureinvolvesadeliberateapproachthatstartswithleadershipcommitmentandthecleararticulationofanewvisionandvalues.Itinvolvesengagingemployees,aligninghiringandrewardsystemstothesevalues,andreinforcingthemthroughconsistentpoliciesandcommunication.sayingAIwillimpacttheirjobs.Furthering9thiscommitmenttoskillingandworkforceresilience,theInfocomMediaDevelopmentAuthority(IMDA),forexample,recentlycommittedtoreskilling18,000SingaporeansinAIandadjacentskillsthroughtheseskillingprogrammes.10Theseeffortshavebornefruit–sincetheintroductionoftheprogrammein2015,1in4eligibleSingaporeanshasparticipatedinSkillsFutureSingaporeacrossmanyindustries,participatingcompaniesandeducationprogrammes.11–Agoodexampleis“sideprojecttime”,or“the20%concept”,popularizedbyGooglebutwhichisalsocurrentlyusedbyfirmslikeAtlassian15andRakuten.16Theseprogrammeshaveenabledemployeestofocusonpersonalprojectsnotdirectlytiedtoajobtaskduringtheirtimeatwork.Sideprojectsenableemployeestoexplorepersonalinterestsandbuildtransferableskillsoutsidetheirjobspecialization,helpingretention,improvingmoraleandencouragingcreativity.17Italsoenablescompaniestoboosttheirinnovativepotential–somethinglargecompaniesstrugglewith.18Theoutputfromtheseprogrammescanbesignificant:GmailandAdSensebotharosefrompastsideprojectsatGoogle.19Organizationalchange–setupandmakeuseofinternaljobmarketsCreateadynamicinternaljobmarketplacethathelpsemployeestransitionintorolesastechnologyandbusinessconditionschange.–DevelopinginternaljobmarketsenablesemployeestounderstandtheopportunitiesavailabletothemwithinthefirmandprovidesaJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit8Consideration2Jobquality2MaintaininghighjobqualityinvolvesworkerinclusioninLLMgovernance,involvingdiverseteamsinLLMdevelopmentandpromotingawarenessofLLMbenefits.ConcernshavealsoarisenthatLLMsandothergenerativeAItechnologiescoulderodejobquality,potentiallymakingjobsandworkplaceslessfulfillingandlessinclusiveandfair.Additionally,increasingconcernsaboutbiasinLLMshighlighttheriskofinherentsystemicdiscriminationinthesemodels,whichcouldexacerbateexistinginequalities.Despitetheseconcerns,emergingdatashowthatLLMSandAItechnologiesalsohavethepotentialtoimprovejobquality.AsdiscussedinJobsofTomorrow:LargeLanguageModelsandJobs,theuseofLLMscouldautomatethemoreroutineandrepetitivetasksonthejob,whichcouldotherwisedisengageworkers,whilemakingroomformorecreative,problem-solvingandindependentdecision-makingtasksonthejob,boostingworkerfulfilment.TheWorldEconomicForum’sGoodWorkFrameworkoffersarobustdefinitionofjobqualityandastrategictemplatetomaintainandimprovethequalityofworkinrapidlyevolvinglabourmarkets.Itoutlineskeyobjectivestocreateabetterfutureofwork,includingpromotingfairwagesandresponsibletechnologyuse,providingflexibilityandprotectionforallevidencethatLLMshaveimpactedworker’swell-being.20Yet,workeranxietyhasincreased.A2023surveybytheAmericanPsychologicalAssociationfoundthat38%ofworkersareworriedabouttheimpactofAIontheirjobs;roughlyhalfofthosewiththeseconcernssaythatworknegativelyaffectstheirmentalhealth,comparedtoonly29%ofthosewithoutconcerns.21AnothercriticalconcernisthatLLMscouldinducebiasinresponsesthatleadtodecision-making,highlightingtheimportanceofadheringtotheGoodWorkFramework’sobjectiveofdrivingdiversity,equityandinclusion.Forinstance,persistentpatternsofracialandethnicdiscriminationcouldbereflectedinhiringdatasets,whichcouldskewalgorithmsusedtosortandfilterjobcandidatesintheapplicationscreeningprocess.22Inthesamevein,mostLLMsaretrainedonEnglishtexts,whichcouldleadLLMstoproduceoverwhelminglyAnglo-centricresponses.23Furthermore,theburdensofadaptingLLM-inducedchangesinjobscoulddisproportionatelyfallonparticularpopulationgroupswhomaybeoverorunderrepresentedinaffectedoccupations,suchaswomenandethnicminorities.24LLMscouldautomatethemoreroutineandrepetitivetasksonthejob,whichcouldotherwisedisengageworkers,whilemakingroomformorecreative,problemsolvingandindependentdecision-makingtasksonthejob,boostingworkerfulfilment.workers,ensuringhealthandwell-being,drivingdiversity,equityandinclusion,andcreatingacultureofcontinuouslearningandemployability.Businessesmustmoveproactivelyandwithurgencytoaddresstheseconcerns,particularlyaroundjobquality,agencyandinclusivity,iftheyaretoestablishthetrustneededtounlockthepositivepotentialofLLMs.OfparticularrelevancewhenincorporatingLLMsandotherAItechnologiesonthejobistheframework’sobjectiveofmaintainingthehealthandtotalwell-beingofworkers.ThereisnotyetstrongJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit92.1ResponsiblebusinessstrategiesWorkerawareness–ensureinclusivedesignofAIandLLMsapplicationsGoodWorkFramework.30SuchmechanismsensureongoingassessmentandrefinementofLLMapplications,focusingontheirethical,impartialandeffectiveusewithinthecompany.–SeveralleadingcompanieshavebeenrecognizedfortheireffortsinadoptingtransparentandinclusiveAIgovernance,whichcanbetailoredtoLLMsspecifically.Googlehasimplementedathree-tieredgovernancestructuretooverseetheresponsibleuseofAI.ThisstructureincludesmultidisciplinaryreviewersandproductteammemberswhoseprimaryfocusisondevelopingAIapplicationsthatyieldsocialbenefits.31IBMisknownforitscommitmenttotrustworthyAI;theyhaveanAIEthicsBoardandhavepublishedclearprinciplesontrustandtransparencyinAI.IBMemphasizesAIthatisexplainable,fairandsecure,andtheyprovidetoolsforbusinessestodetectandmitigatebiasinAIsystems.32AccentureestablishedaresponsibleAI(RAI)complianceprogrammetoinstitutionalizeitsRAIprinciplesintopracticebyembeddingRAIacrossitsentireenterprise–fromdevelopmentanduse,todeploymentandpost-deploymentmonitoring.EmphasizethecollaborativeandinclusivedevelopmentofAIapplicationsandLLMs.Thisinvolvesestablishingcross-functionalteamswithdiversebackgroundsandactivelyinvolvingemployeesinthedesignandimplementationofcompany-specificAIsystemsandLLMs.–LLMshavethegreatestpositiveimpactwhendeveloped,testedandpilotedbyteamswithadiversem