2024年生成人工智能时代的治理报告：一种360°弹性政策和监管方法（英文版）-世界经济论坛

Incollaboration

withAccenture

Governanceinthe

AgeofGenerativeAI:

A360ºApproachforResilient

PolicyandRegulation

WHITEPAPER

OCTOBER2024

WJRLD

ECCNMIC

FORUM

Images:GettyImages,Midjourney

Contents

Foreword3

Executivesummary4

Introduction5

1

Harnesspast6

1.1Examineexistingregulationscomplicated6

bygenerativeAIattributes

1.2Resolvetensionsbetweenpolicyobjectives9

ofmultipleregulatoryregimes

1.3Clarifyexpectationsaround10

responsibilityallocation

1.4Evaluateexistingregulatoryauthoritycapacity11

foreffectiveenforcement

2

Buildpresent12

2.1Addresschallengesofstakeholdergroups12

2.2Facilitatemultistakeholderknowledge-sharing18

andinterdisciplinaryefforts

3

Planfuture21

3.1Targetedinvestmentsandupskilling21

3.2Horizonscanning22

3.3Strategicforesight25

3.4Impactassessmentsandagileregulations25

3.5Internationalcooperation26

Conclusion27

Contributors28

Endnotes33

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GovernanceintheAgeofGenerativeAI2

October2024

GovernanceintheAgeofGenerativeAI:

A360ºApproachforResilientPolicyandRegulation

Foreword

ArnabChakraborty

ChiefResponsible

AIOfficer,Accenture

Wearelivinginatimeofrapidinnovationandglobaluncertainty,inwhichgenerativeartificialintelligence(AI)standsoutasatransformativeforce.This

technologyimpactsvariousindustries,economiesandsocietiesworldwide.WiththeEuropeanUnion’s(EU’s)AIActnowineffect,wehaveaprecedent

forcomprehensiveAIregulation.TheUS,Canada,Brazil,theAfricanUnion,JapanandChinaarealsodevelopingtheirownregulatoryapproaches.Thispivotalmomentcallsforvisionaryleadershipandacollaborativeapproachtoanticipatorygovernance.

Overthepastyear,theAIGovernanceAlliance

hasunitedindustryandgovernmentwithcivil

societyandacademia,establishingaglobal

multistakeholderefforttoensureAIservesthe

greatergoodwhilemaintainingresponsibility,

inclusivityandaccountability.Wehavebeenabletopositionourselvesasasoundingboardfor

policy-makerswhoaregrapplingwiththedifficultiesofdevelopingAIregulatoryframeworks,andto

conveneallplayersfromtheAIvaluechaintocreateameaningfuldialogueonemergingAIdevelopmentissues.

WithAccentureasitsknowledgepartner,the

Alliance’sResilientGovernanceandRegulation

workinggroup(composedofover110members),hascontributedtoshapingasharedunderstandingoftheglobalregulatorylandscape.Thegrouphas

workedtoestablishacomprehensivegovernanceframeworkthatcouldbeusedtoregulate

generativeAIusewellintothefuture.

CathyLi

Head,AI,DataandMetaverse;DeputyHead,Centreforthe

FourthIndustrialRevolution;

Member,ExecutiveCommittee,WorldEconomicForum

Thispaperisaculminationofthoseeffortsand

equipspolicy-makersandregulatorswithaclear

roadmapforaddressingthecomplexitiesof

generativeAIbyexaminingexistingregulatory

gaps,theuniquegovernancechallengesof

variousstakeholdersandtheevolvingformsofthistechnology.Theoutputsofthispaperaredesignedtobepracticalandimplementable,providingglobalpolicy-makerswiththetoolstheyneedtoenhancegenerativeAIgovernancewithintheirjurisdictions.

Throughthispaper,our

AIGovernanceAlliance:

BriefingPaperSeries

,launchedinJanuary2024,

andoureventsandcommunitymeetings,weseektocreateatangibleimpactinAIliteracyandknowledgedissemination.

Giventheinternationalcontextinwhichthis

technologyoperates,weadvocateforaharmonizedapproachtogenerativeAIgovernancethat

facilitatescooperationandinteroperability.SuchanapproachisessentialforaddressingtheglobalchallengesposedbygenerativeAIandforensuringthatitsbenefitsaresharedequitably,particularlywithlow-resourceeconomiesthatstandtogainsignificantlyfromitsresponsibledeployment.

Weinvitepolicy-makers,industryleaders,

academicsandcivilsocietytojoinusinthis

endeavour.Together,wecanshapeafuturewheregenerativeAIcontributespositivelytoourworldandensuresaprosperous,inclusiveandsustainable

futureforall.

GovernanceintheAgeofGenerativeAI3

Executivesummary

Governmentsshouldaddressregulatorygaps,engagemultiplestakeholdersinAIgovernanceandprepareforfuture

generativeAIrisks.

TherapidevolutionandswiftadoptionofgenerativeAIhavepromptedgovernmentstokeeppaceandprepareforfuturedevelopmentsandimpacts.

Policy-makersareconsideringhowgenerative

artificialintelligence(AI)canbeusedinthe

publicinterest,balancingeconomicandsocial

opportunitieswhilemitigatingrisks.Toachievethispurpose,thispaperprovidesacomprehensive

360°governanceframework:

1

Harnesspast:UseexistingregulationsandaddressgapsintroducedbygenerativeAI.

Theeffectivenessofnationalstrategiesfor

promotingAIinnovationandresponsible

practicesdependsonthetimelyassessmentoftheregulatoryleversathandtotacklethe

uniquechallengesandopportunitiespresentedbythetechnology.PriortodevelopingnewAIregulationsorauthorities,governmentsshould:

–AssessexistingregulationsfortensionsandgapscausedbygenerativeAI,

coordinatingacrossthepolicyobjectivesofmultipleregulatoryinstruments

–Clarifyresponsibilityallocationthroughlegalandregulatoryprecedentsand

supplementeffortswheregapsarefound

–Evaluateexistingregulatoryauthoritiesforcapacitytotacklegenerative

AIchallengesandconsiderthe

trade-offsforcentralizingauthoritywithinadedicatedagency

2

Buildpresent:Cultivatewhole-of-societygenerativeAIgovernanceandcross-sectorknowledgesharing.

Governmentpolicy-makersandregulatorscannotindependentlyensuretheresilient

governanceofgenerativeAI–additional

stakeholdergroupsfromacrossindustry,civilsocietyandacademiaarealsoneeded.Governmentsmustuseabroadersetof

governancetools,beyondregulations,to:

–Addresschallengesuniquetoeach

stakeholdergroupincontributingto

whole-of-societygenerativeAIgovernance

–Cultivatemultistakeholder

knowledge-sharingandencourageinterdisciplinarythinking

–LeadbyexamplebyadoptingresponsibleAIpractices

3

Planfuture:IncorporatepreparednessandagilityintogenerativeAIgovernanceand

cultivateinternationalcooperation.

GenerativeAI’scapabilitiesareevolving

alongsideothertechnologies.Governmentsneedtodevelopnationalstrategiesthat

considerlimitedresourcesandglobaluncertainties,andthatfeatureforesight

mechanismstoadaptpoliciesandregulationstotechnologicaladvancementsandemerging

risks.Thisnecessitatesthefollowingkeyactions:

–TargetedinvestmentsforAIupskillingandrecruitmentingovernment

–HorizonscanningofgenerativeAIinnovationandforeseeablerisks

associatedwithemergingcapabilities,convergencewithothertechnologiesandinteractionswithhumans

–Foresightexercisestoprepareformultiplepossiblefutures

–Impactassessmentandagile

regulationstoprepareforthedownstreameffectsofexistingregulationandforfutureAIdevelopments

–Internationalcooperationtoalignstandardsandrisktaxonomiesandfacilitatethesharingofknowledgeandinfrastructure

GovernanceintheAgeofGenerativeAI4

Introduction

A360°frameworkisneededforresilient

generativeAIgovernance,balancinginnovationandriskacrossdiversejurisdictions.

Asorganizationsandindividualsconsiderhowbesttoadoptgenerativeartificialintelligence(AI),new

powerfulcapabilitiescontinuetoemerge.Forsome,humanity’sfuturewithgenerativeAIcanfeelfullofpromise,andforothers,concern.Indeed,across

industriesandsectors,generativeAIpresents

bothopportunitiesandrisks.Forexample–will

generativeAIenhancepersonalizedtreatment

plansimprovingpatients’healthoutcomes,orwillitinducenovelbiosecurityrisks?Willjournalismbedemocratizedthroughnewstorytellingtools,orwilldisinformationbescaled?

ThereisnosingleguaranteedfutureforgenerativeAI.Rather,howsocietyadaptstothetechnologywilldependonthedecisionshumansmakein

researching,developing,deployingandexploitingitscapabilities.Policy-makers,througheffective

governance,canhelptoensurethatgenerativeAIfacilitateseconomicopportunityandfairdistributionofbenefits,protectshumanrights,promotes

greaterequityandencouragessustainable

practices.Governancedecisionsmadenowwillshapethelivesofpresentandfuture

generations,how(andwhether)thistechnologybenefitssocietyandwhoisleftbehind.

Inresponsetothecontinuedgrowthofthe

generativeAIindustryandrapidadoptionof

itsapplicationsacrosstheworld,thispaper’s

360°frameworkoutlineshowtobuildresilientgovernancethatfacilitatesAIinnovationwhile

mitigatingrisks,fromthedevelopmentstagetoitsuse.Theframeworkisdesignedtosupport

policy-makersandregulatorsinthedevelopmentofholisticanddurablegenerativeAIgovernance.Thespecificimplementationoftheframework,

however,willdifferbetweenjurisdictions,

dependingonthenationalAIstrategy,maturityofAInetworks,economicandgeopoliticalcontexts,individuals’expectationsandsocialnorms.

FIGURE1

A360ºapproachforresilientpolicyandregulation

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Encouragewhole-of-societygenerative

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IncorporatepreparednessandagilityingenerativeAIgovernanceand

facilitateinternationalcooperation.

GovernanceintheAgeofGenerativeAI5

Harnesspast

Greaterclarityandcertaintyregarding

existingregulatoryenvironmentsisnecessarytoaddressemerginggenerativeAIchallengesandopportunities.

Successfulimplementationofnationalstrategiesforresponsibleandtrustworthygovernance

ofgenerativeAIrequiresatimelyassessmentofexistingregulatorycapacity–amongothergovernancetools–totackletheunique

opportunitiesandrisksposedbythetechnology.Thisincludesexaminationoftheadequacyofexisting

legalinstruments,lawsandregulations,resolutionofregulatorytensionsandgaps,clarification

ofresponsibilityallocationamonggenerativeAI

supplychainactorsandevaluationofcompetent

regulatoryauthorities’effectivenessandcapacities.Suchassessmentsmustrespectthefundamental

rightsandfreedomsalreadycodifiedininternationalhumanrightslaw,suchastheprotectionof

particulargroups(e.g.minorityrights1andchildren’srights2)aswellaslegalinstrumentsthataredomain-specific(e.g.tocybercrime3andclimatechange4).5

1.1

oWithincreasingdigitalizationandagrowingtrend

ofmonetizing

personaland

professionaldata,protectionof

privacyisboth

vitalandcomplex.Policy-makersarelookingtoprioritizeprivacy-preservingconsiderations.

ExamineexistingregulationscomplicatedbygenerativeAIattributes

WhilegenerativeAI’semergingpropertiesand

capabilitiesmaywarrantnovelregulations,policy-makersandregulatorsshouldfirstexaminetheirjurisdiction’sexistingregulationsforaddressing

newchallenges.Theyshouldalsoidentifywhereexistingregulationsmaybeapplied,adaptedorforegonetofacilitatetheobjectivesofanationalAIstrategy.NavigatinggenerativeAI’sinteractionswithexistingregulationsrequiresanuanced

understandingofboththetechnicalaspects

andthelegalprinciplesunderlyingtheimpactedregulations.Table1discussesexamplesofhowregulatoryinstrumentscanbecomplicatedinthecontextofgenerativeAI.

Privacyanddataprotection

GenerativeAImodelsamplifyprivacy,safetyandsecurityrisksduetotheirrelianceonvastamountsoftrainingdata,powerfulinferencecapabilityandsusceptibilitytouniqueadversarialattacksthat

canunderminedigitaltrust.6Anumberofrisks

arisefromtheinclusionofpersonal,sensitiveandconfidentialinformationintrainingdatasetsanduser

inputs,lackoftransparencyoverthelawfulbasisforcollectingandprocessingdata,theabilityofmodelstoinferpersonaldataandthepotentialformodelstomemorizeanddiscloseportionsoftrainingdata.Withincreasingdigitalizationandagrowingtrendofmonetizingpersonalandprofessionaldata,

protectionofprivacyisbothvitalandcomplex.

Policy-makersarelookingtoprioritizeprivacy-

preservingconsiderationsapplicabletodigitaldatawhilealsocreatingaffordancesfordatapoolingthatcouldleadtoAI-facilitatedbreakthroughs.7Suchaffordancescouldbemadetopromoteinnovationforpublicgoodsinareassuchasagriculture,

healthandeducation,orwithinnarrowlyspecifiedexceptionsfordataconsortiathatfacilitatethe

trainingofAImodelstoachievepublicpolicy

objectives.8Anotheremergingissueforpolicy-

makersisthatofensuringgenerativeAIsafety

andsecurity,evenwhenitmayinvolveinteractionwithpersonaldata,asinthecaseofinvestigatingandrespondingtosevereincidents.Thiscould

beaddressedthroughthecreationofregulatoryexceptionsandguardrailstoensurebothprivacyandresponsibleAIoutcomes.

Pillar1

GovernanceintheAgeofGenerativeAI6

GovernanceintheAgeofGenerativeAI7

Copyrightand

intellectualproperty

GenerativeAIraisesseveralissuesrelatingto

copyrightinfringement,plagiarismandintellectualproperty(IP)ownership(seeIssuespotlight1),

someofwhicharecurrentlybeingconsideredbycourtsinvariousjurisdictions.Rightsrelatedtoprotectinganindividual’slikeness,voiceandotherpersonalattributesarealsoimplicatedby

thecreationof“deepfakes”usinggenerativeAI.

AblanketrulingonAItrainingisuncertainand

judgescoulddeterminethefairnessofcertaindatausesforspecificproductsbasedontheproduct’sfeaturesoroutputs’frequencyandsimilarityto

trainingdata.9Lookingahead,thereisapressingneedforcomprehensiveexaminationofregulatoryframeworksandfornecessaryguidanceon

documentinghumancreativityinthegenerationofcontentasameansofassertingIPprotection.

ISSUESPOTLIGHT1

TraininggenerativeAIsystemsoncopyright-protecteddata,andtensionswiththetextanddataminingexception

Textanddatamining(TDM)istheautomated

processofdigitallyreproducingandanalysing

largequantitiesofdataandinformationto

identifypatternsanddiscoverresearchinsights.Variousjurisdictionsaroundtheworld–such

asJapan,Singapore,Estonia,SwitzerlandandtheEuropeanUnion(EU)–haveintroduced

specificexemptionswithintheircopyrightlawstoenableTDMextractionfromcopyright-protectedcontenttoinnovate,advancescienceandcreatebusinessvalue.

GiventhevastamountsofdatathatgenerativeAIsystemsusetotrainonandgeneratenew

content,jurisdictionsshouldestablishregulatoryclarityregardingTDMforthepurposeof

generativeAItraining.Thiscouldbedone,forexample,byconfirmingwhetherAIdevelopmentconstitutes“fairdealing”or“fairuse”(akey

defenceagainstcopyrightinfringement)or

fallswithintheexemptionsrecognizedinsome

copyrightlaws.CountriesliketheUKareexploringsuchregulatoryexceptions,seekingtopromote

apro-innovationAIagenda.10Ultimately,thereismountingpressureongovernmentstoresolvethecopyrighttensiondefinitively.11

Licensinganddataaccessonan“opt-in”or

“opt-out”basisarealsounderexaminationto

addressTDMconcerns,inadditiontoarangeoftechnologiesandstandardsthatattempttocedecontroltocreators,allowingthemtooptoutfrommodeltrainers.12Licensingproponentsargue

thatscrapingforgenerativeAItrainingwithout

payingcreatorsconstitutesunlawfulcopyingandisaformofreducingcompetition.13AIdevelopers,however,arguethatrequirementstopay

copyrightownersforcontentusedintraining

wouldconstrainmodeldevelopment,negativelyimpactventurecapital(VC)fundingandreducecompetitionamonggenerativeAImodels.14WhiletheydonoteliminateIPlawconcernsentirely,

opt-in/outandlicensingeffortscouldcontributetosettingstandardsthatgenerativeAIfoundationmodelproviderswouldbeexpectedtouphold.

Consumerprotectionandproductliability

WhileAI-specificregulationremainsvoluntaryor

pendinginjurisdictionsoutsideoftheEU,consumerregulationandproductliabilitylawscontinueto

beapplicable,regardlessofwhethertheystrictlycontemplateAIorothertechnologies.GenerativeAIhasthepotentialtoinfluencetheconsumer

marketbyautomatingvarioustasksandservices.Thismay,however,alsochallengetraditional

approachestoriskassessmentandmitigation(duetothetechnology’sbroadapplicabilityandability

tocontinuallylearnandgeneratenewanduniquecontent),aswellasproductsafetystandards

(forexample,inhealthandphysicalsafety).Thedevelopmentofstandardsshouldbeaniterative,multidisciplinaryprocessthatkeepspacewith

technologicaladvancements.

accesstoavastnumberofusers,contributingtoeconomiesofscalethatchallengecompetition.15Inresponse,competitionauthoritiesaroundtheglobearestartingtoprovideguidanceoncompetition

risksandexpectationsingenerativeAImarkets.16CompetitioncomplexitiesateachlayeroftheAI

stackwillneedtobeevaluatedasthetechnologyevolvestoenableaccessandchoiceacrossAI

models,includinggeneral(e.g.ChatGPT),area-

specific(e.g.modelsdesignedforhealthcare)andpersonalusemodels.Suchevaluationswillalso

needtobeconsideredalongsideexistinglegislationrelatingtonationalsecurity,freedomofexpression,mediaandassembly.

Competition

Marketauthoritiesmustensurethatthecompetitiveconditionsdrivingtherapidpaceofinnovation

continuetobenefitconsumers.Althoughexisting

competitionlawsremainapplicable,generativeAI

raisesnewconcernsrelatedtotheconcentrationofcontrolovercriticalcomponentsofthetechnologyandcertainpartnershiparrangements.Forexample,generativeAI’scapabilitiesareenhancedwith

accesstohigh-performancecomputecapacitiesandcertaindatasetsthatmayprovecriticalformodeldevelopment.Thelattercandependon

TABLE1

SelectionofcomplexitiesintroducedbygenerativeAIforexistingregulatoryareas

Regulatoryarea

Emergingcomplexities(non-exhaustive)

Emergingstrategiesunderconsiderationbyregulators(non-exhaustive)

LegalbasisforuserdatabeingusedtotraingenerativeAImodels

Incidentalcollectionofpersonaldatabyweb-crawlers

Enforcementofdata-minimizationprinciples17andopt-in/outrightsbygenerativeAIprovidersanddeployers18

Clarifyingwebterms-of-serviceagreementsandencouragingprivacy-enhancingtechnologicalmeasuressuchasthe

detectionandredactionofpersonallyidentifiableinformation19

Privacyanddataprotection

Specifyingpurposelimitationsfordatacollection

Onlinesafetyandprotectionofvulnerable

groups,especiallyminors,fromharmfuloutputs

Guidanceforpurposethresholdswithindomain-specificregulations,e.g.financialservices20

Positionstatementshighlightingexpectationsforsafetymeasuresandpreferencesforemergingbestpractices21

Copyrightinfringementoftrainingdata

ClearpolicypositionsandaccumulationoflegalprecedentsontherelationsbetweencopyrightandgenerativeAI22

IPrightsandownershipofworksgenerated

Guidanceonassessingtheprotectableelements

byAI

ofAI-generatedworks23

CopyrightandIPAttributionandfaircompensationforartists

andcreators

Investmentsinsolutionsforattributionandauthorrecognitionsuchaswatermarkingandcontentprovenance,alongwith

privacyanddataprotection

ExtensionofgenerativeAImodeltraining

ConsiderationsofnewIPchallengesandclassificationsrelated

toadditionaldatamodalities(e.g.sensory,biological,motion)

toemergingdatamodalities

Liabilityobligationsresultingfromscopeofmultipleapplicableregulations

Considerationsaroundwhetherandinwhichcasesaconcerniscoveredbytheexistingregulations

Thelackofaspecificpurposeofthegenerative

CombiningtheconventionalAIfaultanddefectiveness

AImodelbeforeitsimplementationcomplicates

criteriawithnewmethodsdesignedforgenerativeAI’s

liabilityarisingfromdefectivenessandfault

technicalnuances

Consumer

protectionandproductliability

Efficacyofevidentialdisclosurerequirements

Broadeningthedisclosurerequirementtoencourage

transparencyviaexplainability,traceabilityandauditability,andincludesystemsthatarenotjustclassifiedashigh-risk

Businessconductoragreementsthatenableadominantfirmtoexcluderivals

InitiatingsectoralstudiestodevelopabaselineunderstandingofthecompetitivedynamicsoftheAItechnologystack,

reviewingagreementsbetweenindustryplayersandexaminingsinglefirmconduct24

Unfairordeceptivepractice

Competition

Issuingguidanceonunfairordeceptivepracticeprohibitionsifitdoesnotexist25

Impactofdownstreamapplicationsoncompetitionacrossseveralsectors

StakeholderconsultationsonhowgenerativeAIimpactscompetitioninimportantmarkets,e.g.searchengines,

onlineadvertising,cloudcomputingandsemiconductors26

GovernanceintheAgeofGenerativeAI8

1.2Resolvetensionsbetweenpolicyobjectivesofmultipleregulatoryregimes

oRegulatorsmustaddressemergingtensionsand

mitigatetheriskofundermininglegalcertaintyandrespect

forlegitimateexpectations.

TheintersectionalnatureofgenerativeAI

technologiesandtheapplicabilityofmultiple

regulatoryinstrumentscreatesacomplex

environmentwhereregulatoryframeworksoftenoverlapandconflictduetocompetingpolicy

throughtheEU’sGeneralDataProtectionRegulation(GDPR).Asimilartensionemergesbetweencopyrightlaw–whichprotectstherightsofcreatorsand

inventorsensuringthattheycancontrolandprofitfromtheircreations–andgenerativeAIinnovation,whichoftenusescopyrightedmaterialfortraining.

Addressingtensionsbetween

horizontalandverticalregulations

Horizontalregulationsmayalsoconflictwith

verticalregulationstailoredtospecificsectors.Forinstance,financialinstitutionsusinggenerativeAI

mayencounterchallengesbalancinghorizontalprivacyregulationswithfinancialsectorknow-

your-client(KYC)procedures.Wheredata

protectionregulationsrequireorganizationsto

minimizepersonaldatacollectionlinkedtoa

specificpurpose,KYCguidelinesrequirefinancialinstitutionstoconductthoroughduediligenceonclientstoensurecompliancewithanti-money-

launderinglaws.

objectives.Astechnologyevolvesandbecomesmorewidelyadopted,regulatorsmustaddressemergingtensionsandmitigatetheriskof

undermininglegalcertaintyandrespectforlegitimateexpectations.

Addressingtensionsbetweenhorizontalregulations

Multiplehorizontalregulations,whichaimtocreatebroad,industry-agnosticstandards,mayconflictwhentheyimposerequirementsthataredifficult

toreconcileacrossgenerativeAIcontextsor

applications.Forexample,generativeAImodeldevelopersmayhavetroubleidentifyingthe

appropriatelawfulbasisfordataprocessingand

deliveryaccordingtodataprotectionrightsarticulated

GovernanceintheAgeofGenerativeAI9

Clarifyexpectationsaround

responsibilityallocation

1.3

canhelptoclarifygenerativeAIresponsibility.

Theissuanceofeffectiveguidancerequires

considerationofhowliabilitywithinthegenerativeAIsupplychaincanvaryfordifferentrolesandactorsaswellasconsiderationofretroactiveliabilities

anddispute-resolutionprovisions.Unresolvedambiguityinresponsibilityallocationcanlimitinvestorconfidence,createanunevenplayingfieldforvarioussupplychainactorsandleaverisksunaddressedandharmswithoutredress.

AsdefinedintheWorldEconomicForum’sDigitalTrustFramework,27maintainingaccountability

andoversightfortrustworthy