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IncollaborationwithAccenture
GovernanceintheAge
A360oApproachPolicyand
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Contents
Images:GettyImages,Midjourney
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Foreword
ExecutivesummaryIntroduction
1Harnesspast
1.1ExamineexistingregulationscomplicatedbygenerativeAIattributes
1.2Resolvetensionsbetweenpolicyobjectivesofmultipleregulatoryregimes
1.3Clarifyexpectationsaroundresponsibilityallocation
1.4Evaluateexistingregulatoryauthoritycapacityforeffectiveenforcement
2Buildpresent
2.1Addresschallengesofstakeholdergroups
2.2Facilitatemultistakeholderknowledge-sharingandinterdisciplinaryefforts
3Planfuture
3.1Targetedinvestmentsandupskilling
3.2Horizonscanning
3.3Strategicforesight
3.4Impactassessmentsandagileregulations
3.5Internationalcooperation
ConclusionContributorsEndnotes
Disclaimer
Thisdocumentispublishedbythe
WorldEconomicForumasacontributiontoaproject,insightareaorinteraction.
Thefindings,interpretationsand
conclusionsexpressedhereinarearesultofacollaborativeprocessfacilitatedand
endorsedbytheWorldEconomicForumbutwhoseresultsdonotnecessarily
representtheviewsoftheWorldEconomicForum,northeentiretyofitsMembers,
Partnersorotherstakeholders.
?2024WorldEconomicForum.Allrightsreserved.Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,includingphotocopyingandrecording,orbyanyinformation
storageandretrievalsystem.
GovernanceintheAgeofGenerativeAI2
GovernanceintheAgeofGenerativeAI3
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,ourAIGovernanceAlliance:
BriefingPaperSeries,launchedinJanuary2024,
andoureventsandcommunitymeetings,weseektocreateatangibleimpactinAIliteracyandknowledgedissemination.
Giventheinternationalcontextinwhichthis
technologyoperates,weadvocateforaharmonizedapproachtogenerativeAIgovernancethat
facilitatescooperationandinteroperability.SuchanapproachisessentialforaddressingtheglobalchallengesposedbygenerativeAIandforensuringthatitsbenefitsaresharedequitably,particularlywithlow-resourceeconomiesthatstandtogainsignificantlyfromitsresponsibledeployment.
Weinvitepolicy-makers,industryleaders,
academicsandcivilsocietytojoinusinthis
endeavour.Together,wecanshapeafuturewheregenerativeAIcontributespositivelytoourworldandensuresaprosperous,inclusiveandsustainable
futureforall.
Executivesummary
Governmentsshouldaddressregulatorygaps,engagemultiplestakeholdersinAIgovernanceandprepareforfuture
generativeAIrisks.
GovernanceintheAgeofGenerativeAI4
1
2
3
TherapidevolutionandswiftadoptionofgenerativeAIhavepromptedgovernmentstokeeppaceandprepareforfuturedevelopmentsandimpacts.
Policy-makersareconsideringhowgenerative
artificialintelligence(AI)canbeusedinthe
publicinterest,balancingeconomicandsocial
opportunitieswhilemitigatingrisks.Toachievethispurpose,thispaperprovidesacomprehensive
360°governanceframework:
Harnesspast:UseexistingregulationsandaddressgapsintroducedbygenerativeAI.
Theeffectivenessofnationalstrategiesfor
promotingAIinnovationandresponsible
practicesdependsonthetimelyassessmentoftheregulatoryleversathandtotacklethe
uniquechallengesandopportunitiespresentedbythetechnology.PriortodevelopingnewAIregulationsorauthorities,governmentsshould:
–AssessexistingregulationsfortensionsandgapscausedbygenerativeAI,
coordinatingacrossthepolicyobjectivesofmultipleregulatoryinstruments
–Clarifyresponsibilityallocationthroughlegalandregulatoryprecedentsand
supplementeffortswheregapsarefound
–Evaluateexistingregulatoryauthoritiesforcapacitytotacklegenerative
AIchallengesandconsiderthe
trade-offsforcentralizingauthoritywithinadedicatedagency
Buildpresent:Cultivatewhole-of-societygenerativeAIgovernanceandcross-sectorknowledgesharing.
Governmentpolicy-makersandregulatorscannotindependentlyensuretheresilient
governanceofgenerativeAI–additional
stakeholdergroupsfromacrossindustry,civilsocietyandacademiaarealsoneeded.Governmentsmustuseabroadersetof
governancetools,beyondregulations,to:
–Addresschallengesuniquetoeach
stakeholdergroupincontributingto
whole-of-societygenerativeAIgovernance
–Cultivatemultistakeholder
knowledge-sharingandencourageinterdisciplinarythinking
–LeadbyexamplebyadoptingresponsibleAIpractices
Planfuture:IncorporatepreparednessandagilityintogenerativeAIgovernanceand
cultivateinternationalcooperation.
GenerativeAI’scapabilitiesareevolving
alongsideothertechnologies.Governmentsneedtodevelopnationalstrategiesthat
considerlimitedresourcesandglobaluncertainties,andthatfeatureforesight
mechanismstoadaptpoliciesandregulationstotechnologicaladvancementsandemerging
risks.Thisnecessitatesthefollowingkeyactions:
–TargetedinvestmentsforAIupskillingandrecruitmentingovernment
–HorizonscanningofgenerativeAIinnovationandforeseeablerisks
associatedwithemergingcapabilities,convergencewithothertechnologiesandinteractionswithhumans
–Foresightexercisestoprepareformultiplepossiblefutures
–Impactassessmentandagile
regulationstoprepareforthedownstreameffectsofexistingregulationandforfutureAIdevelopments
–Internationalcooperationtoalignstandardsandrisktaxonomiesandfacilitatethesharingofknowledgeandinfrastructure
Introduction
A360°frameworkisneededforresilient
generativeAIgovernance,balancinginnovationandriskacrossdiversejurisdictions.
FIGURE1
A360oapproachforresilientpolicyandregulation
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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.
MakeuseofexistingregulationsandaddressgapscausedbygenerativeAI.
360o
governance
Encouragewhole-of-societygenerative
AIgovernanceandcross-sectorknowledgesharing.
3:Plnf
IncorporatepreparednessandagilityingenerativeAIgovernanceand
facilitateinternationalcooperation.
GovernanceintheAgeofGenerativeAI5
Harnesspast
Greaterclarityandcertaintyregarding
existingregulatoryenvironmentsisnecessarytoaddressemerginggenerativeAIchallengesandopportunities.
1.1
oWithincreasingdigitalizationandagrowingtrend
ofmonetizing
personaland
professionaldata,protectionof
privacyisboth
vitalandcomplex.Policy-makersarelookingtoprioritizeprivacy-preservingconsiderations.
ExamineexistingregulationscomplicatedbygenerativeAIattributes
GovernanceintheAgeofGenerativeAI6
Pillar1
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
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.
GovernanceintheAgeofGenerativeAI7
ISSUESPOTLIGHT1
TraininggenerativeAIsystemsoncopyright-protecteddata,andtensionswiththetextanddataminingexception
Copyrightand
intellectualproperty
GenerativeAIraisesseveralissuesrelatingto
copyrightinfringement,plagiarismandintellectualproperty(IP)ownership(seeIssuespotlight1),
someofwhicharecurrentlybeingconsideredbycourtsinvariousjurisdictions.Rightsrelatedtoprotectinganindividual’slikeness,voiceandotherpersonalattributesarealsoimplicatedby
thecreationof“deepfakes”usinggenerativeAI.
AblanketrulingonAItrainingisuncertainand
judgescoulddeterminethefairnessofcertaindatausesforspecificproductsbasedontheproduct’sfeaturesoroutputs’frequencyandsimilarityto
trainingdata.9Lookingahead,thereisapressingneedforcomprehensiveexaminationofregulatoryframeworksandfornecessaryguidanceon
documentinghumancreativityinthegenerationofcontentasameansofassertingIPprotection.
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.
TABLE1
SelectionofcomplexitiesintroducedbygenerativeAIforexistingregulatoryareas
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
GovernanceintheAgeofGenerativeAI8
Emergingcomplexities(non-exhaustive)
Regulatoryarea
Emergingstrategiesunderconsiderationbyregulators(non-exhaustive)
LegalbasisforuserdatabeingusedtotraingenerativeAImodels
Incidentalcollectionofpersonaldatabyweb-crawlers
Enforcementofdata-minimizationprinciples17andopt-in/outrightsbygenerativeAIprovidersanddeployers18
Clarifyingwebterms-of-serviceagreementsandencouragingprivacy-enhancingtechnologicalmeasuressuchasthe
detectionandredactionofpersonallyidentifiableinformation19
Guidanceforpurposethresholdswithindomain-specificregulations,e.g.financialservices20
Positionstatementshighlightingexpectationsforsafetymeasuresandpreferencesforemergingbestpractices21
Privacyanddataprotection
Specifyingpurposelimitationsfordatacollection
Onlinesafetyandprotectionofvulnerable
groups,especiallyminors,fromharmfuloutputs
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
StakeholderconsultationsonhowgenerativeAIimpactscompetitioninimportantmarkets,e.g.searchengines,
onlineadvertising,cloudcomputingandsemiconductors26
Impactofdownstreamapplicationsoncompetitionacrossseveralsectors
1.2Resolvetensionsbetweenpolicyobjectivesofmultipleregulatoryregimes
oRegulatorsmustaddressemergingtensionsand
mitigatetheriskofundermininglegalcertaintyandrespect
forlegitimateexpectations.
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.
TheintersectionalnatureofgenerativeAI
technologiesandtheapplicabilityofmultiple
regulatoryinstrumentscreatesacomplex
environmentwhereregulatoryframeworksoftenoverlapandconflictduetocompetingpolicy
objectives.Astechnologyevolvesandbecomesmorewidelyadopted,regulatorsmustaddressemergingtensionsandmitigatetheriskof
undermininglegalcertaintyandrespectforlegitimateexpectations.
Addressingtensionsbetweenhorizontalregulations
Multiplehorizontalregulations,whichaimtocreatebroad,industry-agnosticstandards,mayconflictwhentheyimposerequirementsthataredifficult
toreconcileacrossgenerativeAIcontextsor
applications.Forexample,generativeAImodeldevelopersmayhavetroubleidentifyingthe
appropriatelawfulbasisfordataprocessingand
deliveryaccordingtodataprotectionrightsarticulated
GovernanceintheAgeofGenerativeAI9
ChallengesandconsiderationsforgenerativeAIresponsibilityallocation(non-exhaustive)
AsdefinedintheWorldEconomicForum’sDigitalTrustFramework,27maintainingaccountability
andoversightfortrustworthydigitaltechnologiesrequiresclearlyassignedandwell-definedlegalresponsibilitiesalongsideremedyprovisionsforupholdingindividualandsocialexpectations.
GenerativeAIintroducescomplexitiesinto
traditionalresponsibilityallocationpractices,as
examinedinTable2.Policy-makersshouldconsiderwheresupplementaryeffortsareneededtoaddressgapsandwherelegalandregulatoryprecedents
canhelptoclarifygenerativeAIresponsibility.Theissuanceofeffectiveguidancerequires
considerationofhowliabilitywithinthegenerativeAIsupplychaincanvaryfordifferentrolesandactorsaswellasconsiderationofretroactiveliabilities
anddispute-resolutionprovisions.Unresolvedambiguityinresponsibilityallocationcanlimitinvestorconfidence,createanunevenplayingfieldforvarioussupplychainactorsandleaverisksunaddressedandharmswithoutredress.
TABLE2
GovernanceintheAgeofGenerativeAI10
Clarifyexpectationsaroundresponsibilityallocation
1.3
Examplechallenges
Considerationsforpolicy-makers
–Case-basedreview:Policy-makersshould
providegeneralallocationguidancetocultivate
predictability,butincludemechanismsthatallowcasecomplexitiestodeterminepreciseallocation.Requiringactorstoidentifyresponsibilityhand-offsisoneapproachbeingexaminedbyjurisdictions.
–Terminology:Policy-makersshouldcollaborate
toarriveatsharedtermsformodels,applicationsandroles,e.g.inlinewithISO420001fromthe
InternationalOrganizationforStandardization(ISO).
–Regulatorycarve-outs:Policy-makersshouldlimitinstanceswhenusecanleadtounfairadvantages,suchaswheresomeentitiesareabletobypass
crucialsafeguardsandaccountabilitymeasuresorengageinregulatoryarbitrage.
–Proportionality:Policy-makersshouldconsiderthecontrol,influenceandresourceseachactorhasinthegenerativeAIlifecycle,andabilitytoredressissuesresultinginharm.
–Third-partycertifications:Policy-makersshould
considerappropriatenessandnecessityofusingthirdpartiesforarobustAIcertificationsystem
(potentiallydefinedthrough
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