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）.pdf

该【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） 】是由【蒙查查】上传分享，文档一共【17】页，该文档可以免费在线阅读，需要了解更多关于【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） 】的内容，可以使用淘豆网的站内搜索功能，选择自己适合的文档，以下文字是截取该文章内的部分文字，如需要获得完整电子版，请下载此文档到您的设备，方便您编辑和打印。:..IncollaborationentureJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkitWHITEPAPERDECEMBER2023:..Images:GettyImagesContentsForeword3Executivesummary4Introduction51Consideration1:::,,interpretationsandconclusionsexpressedhereinarearesultofacollaborativeprocessfacilitatedandendorsedbytheWorldEconomicForumbutwhoseresultsdonotnecessarilyrepresenttheviewsoftheWorldEconomicForum,northeentiretyofitsMembers,Partnersorotherstakeholders.?,includingphotocopyingandrecording,?ABusinessToolkit2:..December2023JobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkitForewordMaryKateMorleyRyanElselotHasselaaranization/HeadofMission,Work,HumanPotentialManagingWagesandJobCreation,Director,AccentureWorldEconomicForumGenerativeartificialintelligence(AI)and,inparticular,initiativeincuratingstrategiesandpracticesthatlargelanguagemodels(LLMs),underpinnedbyfacilitateLLMstoworkforbusinesses,,representaparadigmshiftinhowweinteractwithinformationand,byThispaperisadirectfollow-uponthepreviousextension,,Jobsofcreateoriginalcontent,generateinsightsfromTomorrow:LargeLanguageModelsandJobs,largeamountsofdata,translatelanguageswithwhichtookastructuredapproachtounderstandingnear-,includingnewLLM-poweredimpactofLLMsonjobs,enablingstakeholders–human-machineinterfacessuchasintelligentbusinessleaders,policy-makers,workersandtheagents,couldhaveprofoundimplicationsforjobsbroaderpublic–,,thereisalsoariskthatWearedeeplygratefultotheCentrefortheNewtheycoulddisplaceexistingroles,exacerbatingEconomyandSocietypartnersandconstituentsforsocioeconomicdisparitiesandcreatingasenseoftheirleadershipofthejobsagenda,,entureteam,,aglobalcoalitionofministersandchiefexecutiveofficersthatpromotesabetterfutureThispaperisintendedtoserveasatoolkitforofwork,throughboostinglabourmarketforesight,businessestoprovideguidanceonstrategiesdrivingjobcreationandimprovingjobqualitywhiletomaximizethepotentialofemployeesastheyenablingjobtransitionsandwillserveasakeytooladapt,learnandgrowwiththesetechnologiesinfortheGoodWorkAlliance,aglobal,cross-–ABusinessToolkit3:..ExecutivesummaryBusinesseswillneedtostrategicallynavigateconcernsoverjobdisplacementrisk,-to-faceinteractionaregenerativeartificialintelligence(AI)technologies,’sCopilot,MidjourneyandChatGPT,adoptproactiveandresponsibleapproachestohaveproducedAI’sfirsttrueinflexionpointinmanagethistransformation,addressingconcernspublicadoption,demonstratingthetechnology’slikejobchangeandjobdisplacementrisk,,planningenerativeAI,includingandproactivepreparationarerequiredofbusinessimage,video,reation,leaderstoensurethatLLMsandothertechnologicallargelanguagemodels(LLMs),TheFutureofJobsReport2023statesthatglobalprovidingpracticalstrategiestonavigatethebusinessleadersbelievethat23%ofglobaljobschangingjoblandscapeinthreeprimaryareasofareexpectedtotransformwithinthenextfiveyearsconsideration:1)jobchangeandjobdisplacementduetorapidtechnologicaladvances,particularlyinrisk,2)jobquality,and3),LLM’:1)promotingworkerawareness,2)Tomorrow:anizationalchange,and3)shiftingpaper,,foundthat40%businessstrategymatrixforeffectivelyleadingofworkinghourscouldbetransformed,affectingtheworkforcetransitionthroughthelarge-–ABusinessToolkit4:..IntroductionUpto40%ofworkinghourscouldbetransformedbyLLMs–,demonstratingthetechnology’,thatglobalbusinessleadersexpect23%ofcurrentChatGPT,OpenAI’strainedlanguagemodel,,ChatGPTtransformationisdrivenbykeytrendsliketechnologyhadreachedonehundredmillionmonthlyactiveadoption,thegreentransitionandtheglobalusers,makingitthefastest-,:82%ofbusinessleadersexpectincreasedadoptionofGenerativetransformermodelshavetheabilitytonewtechnologiestodrivebusinesstransformation,impactallclassesofcreativework,possessingwhile37%ofbusinessleadersanticipatethatnewthecapabilitytogeneratenovelimages,videos,jobcreator,and21%music,,largelanguagemodels(LLMs)andtheiruniquelanguage-Throughout2023,specifically,generativeartificialgeneratingcapabilitieshaveanoutsizedpotentialintelligence(AI)hasdevelopedatarapidpaceintoimpactthegreatestnumberofjobsintheneartermsofcapabilitiesandadoption,,suchasthosepoweringChatGPT,,,toincreasegenerativeAIinthenext3to5years,and98%understandingofhowLLMscouldimpactjobs,ofglobalexecutivesagreeAIfoundationmodelstheWorldEconomicForum,incollaborationwithanizations’Accenture,publishedtheJobsofTomorrow:’,MidjourneyandChatGPTareacaseinItprovidesastructuredanalysisofthepotentialJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit5:..Over40%impactofLLMsonjobsandfindsthatitwillbothpotentialforjobtransformationasfoundbytheofworkingautomateandaugmentjobtasks,ultimatelyhavingJobsofTomorrow:,itiscriticalthatbusinessestransformedbyadoptaproactive,human-%oftotalworktimeacrossupationsinvolveslanguage-basedtasks–tasksThiswhitepaperisafollow-:,000individualtasksacross867paperandservesasatoolkitforbusinessestooccupationswereassessedtounderstandtheaddressthreeconsiderationsforthetechnologicalpotentialexposureofeachtasktoLLMadoption,:asLLMsautomation(thetaskcouldbeperformedbyLLMs,arecapableofperformingmanyofthelanguagewithouthumans),highpotentialforaugmentationtasksusedonthejob,andupto60%ofworktime(thetaskwillcontinuetobeperformedbyhumans,useslanguagetasks,thereispotentialforsomewithLLMsincreasinghumanproductivity),(humanswillcontinuetoperformisjobquality:thedeploymentofthesetechnologicalthetaskwithnosignificantimpactfromLLMs)ortoolscouldaffectnotonlythenumberofjobsunaffected(non-languagetasks).butalsothenatureoftheworkitself,potentiallyaffectingthemeaningfulnessofwork,thewell-beingTheanalysisfoundthatover40%:toadjusttoandembracetechnologicalautomationoftasksincludethosethatemphasizechangerequirescontinuouslearning;anagileroutineandrepetitiveproceduresanddonotrequireworkforceisthebestapproachtomeettheevolvingmunication,,eachconsiderationisplexfirstdefinedandthenaddressedwithseveralproblem-solvingskills,especiallythoseinscience,practicalbusinessstrategiesthatensureacohesivetechnology,engineeringandmathematics(STEM),suchasthebusinessstrategiesfallintothreeprimarycomputerprogrammers,plusrolesthatrequireapproaches:1)promotingworkerawareness,whichhumanvalidation,suchasassessors,-to-facethepotentialimpactsofLLMsontheircurrentrolescommunicationandinterpersonalinteractionsandfuturejobprospects,empoweringthemtoareexpectedtobelessexposedtotheimpactsproactivelyengagewiththeevolvingtechnologicalofLLMs,andthoseemphasizingnon-languagelandscape,2)anizationalchange,inpaniesadapttheirstructures,,thepaperalsofoundthatnewjobsandstrategiestoharnessthebenefitsofnewcouldemerge,forexample,AImodelandprompttechnologieswhilemitigatingtherisksassociatedengineers,interfaceandinteractiondesigners,AIwithsuchtransformations,and3)shiftingworkplacecontentcreators,datacuratorsandtrainers,andnormsandculture,,,-specificjobsOrganizational2Setupandmakeuseofinternal5Implementtransparent8Applyaskill-firstapproachanizationwidedeploymentShiftingnormsand3Createincreasedworkforce6IncreaseawarenessofLLM9OfferworkplacelearningcultureagilitybenefitsintheworkplaceopportunitiesJobsofTomorrowLargeLanguageModelsandJobs–ABusinessToolkit6:..1Consideration1JobchangeandjobdisplacementriskProactivelyaddressingjobchangeandjobdisplacementriskthroughinter