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OECDSocial,EmploymentandMigrationWorkingPapers

No.290

MargueritaLane,

MorganWilliams

DefiningandclassifyingAIintheworkplace

/10.1787/59e89d7f-en

OrganisationforEconomicCo-operationandDevelopment

Unclassified

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English-Or.English

24March2023

DIRECTORATEFOREMPLOYMENT,LABOURANDSOCIALAFFAIRS

EMPLOYMENT,LABOURANDSOCIALAFFAIRSCOMMITTEE

DefiningandClassifyingAIintheWorkplace

OECDSOCIAL,EMPLOYMENTANDMIGRATIONWORKINGPAPERSNo.290

JELcodes:J01,J08,J2,O14

AuthorisedforpublicationbyStefanoScarpetta,Director,DirectorateforEmployment,LabourandSocialAffairs.

AllSocial,EmploymentandMigrationWorkingPapersarenowavailablethroughtheOECDwebsiteat

/els/workingpapers

.

MargueritaLANE:

marguerita.lane@

MorganWILLIAMS

JT03515077

OFDE

Thisdocument,aswellasanydataandmapincludedherein,arewithoutprejudicetothestatusoforsovereigntyoveranyterritory,tothedelimitationofinternationalfrontiersandboundariesandtothenameofanyterritory,cityorarea.

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OECDSocial,EmploymentandMigrationWorkingPapers

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Youcancopy,downloadorprintOECDcontentforyourownuse,andyoucanincludeexcerptsfromOECDpublications,databasesandmultimediaproductsinyourowndocuments,presentations,blogs,websitesandteachingmaterials,providedthatsuitableacknowledgmentofOECDassourceandcopyright

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Acknowledgments

ThispublicationcontributestotheOECD’sArtificialIntelligenceinWork,Innovation,ProductivityandSkills(AI-WIPS)programme,whichprovidespolicymakerswithnewevidenceandanalysistokeepabreastofthefast-evolvingchangesinAIcapabilitiesanddiffusionandtheirimplicationsfortheworldofwork.TheprogrammeaimstohelpensurethatadoptionofAIintheworldofworkiseffective,beneficialtoall,people-centredandacceptedbythepopulationatlarge.

AI-WIPSissupportedbytheGermanFederalMinistryofLabourandSocialAffairs(BMAS)andwillcomplementtheworkoftheGermanAIObservatoryintheMinistry’sPolicyLabDigital,Work&Society.Formoreinformation,visit

https://oecd.ai/work-innovationproductivity-skills

and

https://denkfabrik-

bmas.de/

.

Thisworkingpaperbenefittedgreatlyfrominputfromtheparticipantsoftheexpertworkshopheldon14December2020.Theauthorsthanktheparticipants,listedinAnnexB,forlendingtheirtimeandexpertiseinspeakingtotheOECDforthisproject.HelpfulcommentsandsuggestionsontheworkingpaperwerereceivedfromKatyaKlinovaofthePartnershiponAI,andfromOECDcolleagues,includingStijnBroecke,AngelicaSalviDelPero,AnneloreVerhagen,AnneVourc’h,GlendaQuintini,AndrewGreen,ChloéTouzet,AnnaMilanez,LuisArandaandKarinePerset.ThanksalsotoAssaFofana,whoprovidedpublishingassistance.Anyerrorsoromissionsinthisworkingpaperaretheauthors’own.

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Abstract

ThisdocumentservesbothasaconceptualandpracticalguidefordefiningandclassifyingAI,inordertohelpstakeholdersanalyseandunderstanditsimpactontheworkplace.ItfirstdiscusseshowAIcanbedefinedandprovidesaselectionofAIusecasestohelpstakeholdersidentifyAIanddistinguishitfromotheradvancedtechnologies.ThedocumentthenprovidesaframeworkforclassifyingAIaccordingtoitsimpactontheworkplace,consistingofasetofquestionsintendedtohelpstakeholdersevaluateanyAIapplicationfromaworkplaceperspective(eitheraprioriorexpost)andtopromoteinformeddiscussionsothatAIisimplementedinawaythatempowersandcomplementsworkersandimprovesjobquality,andthatnooneisleftbehind.

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Résumé

Cedocumentsertdeguideconceptueletpratiquepourdéfiniretclasserl'IA,afin

d'aiderlespartiesprenantesàanalyseretàcomprendresonimpactauseindesentreprises.Ilexaminetoutd'abordlamanièredontl'IApeutêtredéfinieetprésenteunesélectiond'exemplesd'utilisationdel'IApouraiderlesacteursàl’identifieretàladistinguerd'autrestechnologiesavancées.Ledocumentfournitensuiteunsystèmedeclassificationdel'IAenfonctiondesonimpactauseindesentreprises.Cesystèmeconsisteenunesériedequestionsdestinéesàaiderlesacteursàévaluertouteapplicationdel'IAdupointdevuedesoneffetsurlefonctionnementdesentreprises(aprioriouaposteriori).Ilviseàpromouvoirundébatéclairé,afinque

l'IAsoitmiseauservicedel'autonomisationdestravailleursetviennelescompléter,qu'elleaméliorelaqualitédel'emploi,etbénéficieàtous.

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übersicht

DiesesDokumentdientalskonzeptionellerundpraktischerLeitfadenfürdieDefinitionundKategorisierungvonKI,umdessenAuswirkungenaufdieArbeitsweltzuanalysieren.Zun?chstwirdanhandvonAnwendungsbeispielenbeschrieben,wieKIidentifiziertundvonanderenTechnologienunterschiedenwerdenkann.ImWeiterenentwirftdasDokumenteineKategorisierungvonKI,dieStakeholdernhelfensollen,anhandeinerReihevonFragenjedeKI-AnwendungimHinblickaufderenWirkungaufdieArbeitsweltzubewerten(entwederapriorioderimNachhinein).DiessolleinefundierteDebattedarübererm?glichen,wieKIaufeineArtundWeiseeingesetztwerdenkann,diedieBesch?ftigungsqualit?tverbessertundArbeitnehmer*innenunterstütztsowiebef?higt,anstattsiezubenachteiligen.

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Tableofcontents

Acknowledgments3

Abstract4

Résumé5

übersicht6

Introduction9

Part1:WhatismeantbyAIintheworkplace?11

DefinitionofAI11

AIusecasesbysector12

Part2:ClassifyingAIaccordingtoitsimpactontheworkplace14

Keyquestionsforjobquantity14

Keyquestionsforjobquality18

Keyquestionsforinclusiveness23

Concludingremarks27

References29

AnnexA.InfluenceontheOECDsurveysofemployersandworkers33

AnnexB.ExpertworkshoponclassificationofAIaccordingtolabourmarketimpact37

AnnexC.SummaryoftheframeworkforclassifyingAIaccordingtoitsimpactonthe

workplace38

TABLES

Table1.IllustrationofAIusecasesacrossvarioussectorsoftheeconomy12

TableA.1.Mappingoftheframeworktoquestionsintheemployerandworkersurveys35

TableAC.1.SummaryoftheframeworkforclassifyingAIaccordingtoitsimpactontheworkplace38

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BOXES

Box1.DifferentiatedapproachestoAIregulationandpolicy10

Box2.Example:AI-assistedshoppingcartincreasesproductivitybutnotenoughtosustainjobquantity17

Box3.Example:AIrobotsmakedistributioncentreworksaferbutmoremonotonous19

Box4.Example:Asmartwristbandleadstofunctioncreep22

Box5.Example:TribulationsoftemporaryworkarrangementsinIntelligentToolsInc.25

Box6.Example:Roadsafetytoolbringsunforeseenconsequences27

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Introduction

AperiodofrapiddevelopmentinArtificialIntelligence(AI)israisingamajorquestionforfirms,unionsandgovernments,namely:howtoimplementAIthatfostersentrepreneurshipandproductivity,whileatthesametimeempoweringandcomplementingworkers,enhancingoccupationalsafetyandhealthandthequalityofjobs,andensuringthatthebenefitsfromAIarebroadlyandfairlyshared?

Thereiscurrentlylittleguidanceonhowtomeettheseobjectives.OnechallengeisthatAIisnotasingle,uniformtechnologythatwillsteerthelabourmarketinoneknowndirection.Inreality,AIcomprisesarangeofdifferentsystems,whichcanimpactworkersindifferentways,frominfluencingthedemandfortheirlabourtochangingtheenvironmentwheretheyworkandtoaffectingtheinclusivenessofthelabourmarketoverall.Fundamentally,theimpactofAIontheworkplacewilldependonthetypeofAI,howitisdeployed,andoncontextualfactors,includingpoliciesandinstitutions.

ThisdocumentservesbothasaconceptualandpracticalguidefordefiningandclassifyingAI,inordertounderstanditsimpactontheworkplace.1Part1examinestheconceptualside,discussinghowAIcanbedefinedandprovidingaselectionofAIusecasestohelpstakeholdersidentifyAIanddistinguishitfromotheradvancedtechnologies.TheaimistoestablishacommonunderstandingofAIintheworkplacetofacilitatediscussionsanddecision-makingabouttheadoption,implementationanduseofAI.

Part2thenprovidesaframeworkforclassifyingAIaccordingtoitsimpactontheworkplace,consistingofasetofquestionsforstakeholderstoconsider.ThesequestionsareintendedtohelpstakeholdersevaluateanyAIapplicationfromaworkplaceperspective(eitheraprioriorexpost),sothatthisimportantdimensionisnotoverlooked.

Theframeworkcontributestoapolicydiscussioncurrentlyattractingalotofattention,whichishowtodifferentiatebetweenAIapplicationswithdifferentriskorimpactlevelsinordertoapplyappropriateregulationsandpolicymeasures.Box1providessomeexamplesofgovernmentsexploringdifferentiatedapproachestoAIregulationandpolicy.AlthoughmuchofthepolicydiscussionisabouthowtoregulatepotentiallyharmfulAI,governmentswillalsowanttosteerinnovationtowardsAIthatenhancestheworkplace,theeconomyandsocietyasawhole.

Theframeworkpresentedhereisintendedtosupportsuchanapproachbyenablingstakeholderstogivedueconsiderationtoworkplacerisksandimpacts.Onerecentpaper(KlinovaandKorinek,2021[1])pointsoutthat,whiledevelopersanddeployerswilloftenagreethatanyAIsystemshouldbehuman-centred,transparentandaccountable,theywilltooeasilyconcedethatAIwilldisruptlabourmarketsandinducejobloss.TheframeworkaimstopromoteinformeddiscussionofthepotentialpositiveandnegativeworkplaceimpactsofAI,sothatAIisimplementedinsuchawayastoempowerandcomplementworkersandimprovejobquality,andsothatallworkerscanshareinthesebenefits.

TheconceptualandpracticalthinkingdevelopedinthisdocumenthasunderpinnedmuchoftheOECD’sotherworkontheimpactofAIontheworkplace.Inparticular,ithasinfluencedthedesignofthe

1SeetheOECDFrameworkfortheClassificationofAISystems(OECD,2022[6])forabroaderframeworkthatclassifiesallAIapplicationsaccordingtothefullsetofOECDAIprinciples,includingthoserelatingtopeopleandplanet;humanrights,privacyandfairness;transparencyandexplainability;robustness,securityandsafety;andaccountability.

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questionnairesusedforemployerandworkersurveystheOECDconductedinthemanufacturingandfinancesectorsof8OECDcountriestocollectnewdataontheimpactofAIintheworkplace(seeAnnexAforfurtherdetails).Anexpertworkshopwasheldon14December2020whichgreatlyinformedthiswork(AnnexB).AnnexCprovidesasummaryoftheframeworkintableformat.

Box1.DifferentiatedapproachestoAIregulationandpolicy

PolicymakersareexploringdifferentiatedapproachestoAIregulationandpolicy

PolicymakersarecurrentlyexploringhowtodevelopregulationandpolicyinawaythatacknowledgesthatdifferentAIapplicationsmayrequiredifferenttreatment.Suchanapproachwouldallowregulationtobetargetedandproportionate,focusingoversightonAIapplicationswiththepotentialtocausemostharmwhileminimisingtheburdenofcomplianceforbenignandbeneficialapplications.Examplesinclude(OECD,2023[2]):

.TheEuropeanCommission,whichisproposingarisk-basedregulatoryapproachthatdifferentiatesbetweenusesofAIthatgenerateminimalrisk,lowrisk,highriskandunacceptablerisk.Forexample,theEuropeanCommissionconsidersallAIsystemsusedin“employment,workersmanagementandaccesstoself-employment”as“highrisk”,whichwouldincludeusingAIforrecruitmentandemployeemonitoring(CounciloftheEuropeanUnion,2022[3]).

.TheCanadiangovernment,whichseekstoestablishmeasurestomitigaterisksofphysicalorpsychologicalharmandbiasedoutputof“high-impact”AIsystems.

.TheUnitedKingdomgovernment,whichproposesanapproachthatisbothrisk-basedandcontext-specific,acknowledgingthatrisksmaydifferwithinandacrosssectorsandovertime.

Determining“high-risk”or“high-impact”AIapplicationsisacomplextaskandregulatorsarelikelytodivergeintheirdeterminations.However,theappealofsuchanapproachliesintheheterogeneityofAIapplications,owingprimarilytoAI’sabilitytobecombinedwithothertechnologiesandtobedeployedindifferentcontexts.

Similarideasarefoundintheeconomicliterature

TheideaofbeingabletodrawalinebetweendifferenttypesofAIisalsofoundintheeconomicliterature:AcemogluandRestrepo(2020[4])finditusefultodifferentiatebetweenthe“rightandwrongkind”ofAIwhenreflectingonthelabourmarketandbroadereconomicandsocialimplicationsofAI.Acemoglu(2023[5])arguesthatwhenmarketsfavourthewrongtechnologies,suchasAIwhichisgoodenoughtoreplaceaworkerbutnotgoodenoughtoincreaseproductivitysubstantially,policymakersmayhavearoletoplayinidentifyingandcorrectingthesystematicdistortionsthatsteerinnovationtowardssuboptimalorharmfuloutcomes.

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Part1:WhatismeantbyAIinthe

workplace?

ThissectiondiscusseshowAIcanbedefinedandprovidesaselectionofAIusecases.TheaimistoestablishacommonunderstandingofAIintheworkplacetofacilitatediscussionsanddecision-makingabouttheuseofAI.

DefinitionofAI

DefiningwhatismeantbyAIcanhelpestablishacommonfoundationforconsideringtheimpactontheworkplace.AusefulstartingpointisthedefinitionestablishedbytheOECD’sAIExpertsGroup(AIGO)(OECD,2022[6]):

AnAIsystemisamachine-basedsystemthatcan,foragivensetofhuman-definedobjectives,makepredictions,recommendationsordecisionsinfluencingrealorvirtualenvironments.Itusesmachineand/orhuman-basedinputstoperceiverealand/orvirtualenvironments;abstractsuchperceptionsintomodels(inanautomatedmannere.g.withmachinelearningormanually);andusemodelinferencetoformulateoptionsforinformationoraction.AIsystemsaredesignedtooperatewithvaryinglevelsofautonomy.

ArecentOECDpaper(2021[7])onAImeasurementinICTusagesurveyscomparestheOECDdefinitiontothoseusedbyotherorganisationsandstatisticalagencies.Highlightedherearesomenotablecommonalitiesacrossdefinitions,withrelevanceforAIintheworkplace:

.ReferencetothecapabilitiesofAI:Definitionstypicallyeitherdescribethesystemasintelligentorlistcognitivetasksthatitcanperform(inthecaseoftheOECDdefinition:makingpredictions,recommendationsordecisions).AI’sabilitytoperformcognitivetasksmeansitcouldtransformoccupationsthathavebeenhistoricallymoreshelteredfromautomation.

.Referencetotheform(s)thatAIcantake:DefinitionsoftendescribeAIasa“system”,“technology”,“machine”or“software”.Thiscanserveasareminderthat,despiteAI’sintelligence,itshouldnotbeanthropomorphised.2

.ReferencetoAI’senvironment:Afewdefinitionsmentionthis,asanodtoAI’sinteractionwiththeworldaroundit.TheOECDdefinitiontreatstheenvironmentasbothaspaceobservablethroughperceptionsandinfluencedthroughactions.Inaworkplaceenvironment,thedatacollectionunderpinningAImaychangehowworkersaremonitoredandmanaged,forexample.

.ReferencetoAI’sautonomy:SomedefinitionsmentionthatAIoperateswithsomelevelofautonomy(andintheOECD’sdefinition,withvaryinglevelsofautonomy).ThiscouldhintatsomepossiblelimitationsofAIandapossibleroleforhumanstocontrol,guideoroverrideAIincertaincircumstances.

2Forfurtherdiscussionofattributinghuman-likeintelligencetoAIsystems,seeWaas(2022[49]).

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AIusecasesbysector

Evenequippedwithadefinition,itcanbedifficultinpracticetodistinguishbetweenwhatisandwhatisnotAI.OneofthemainchallengesisthatAIoftenco-existswith,andisembeddedin,othertechnologieswiththeresultthatitspresencemaybeobscured.Forinstance,workersusingAI-enhancedsoftwaremaybecompletelyunawarethatAIisgeneratingtherecommendationstheyseeontheinterface.Withoutin-depthknowledgeofhowatechnologyoperates,theexistenceofAImayneedtobeinferredbasedonknowledgeofcommonapplicationsofAI,forexample:insoftware(e.g.voiceassistants,imageanalysis,searchengines,andfacerecognition)orsystemsembeddedinhardwaredevices(e.g.robots,autonomousvehicles,dronesorIoTapplications)(MontagnierandEk,2021[7]).AnotherchallengeisthatthemeaningofAImaychangeovertimeasnewtechnologiesemergeandothersrecede.3

Table1

providesasnapshotofreal-worldapplicationsofAIinarangeofeconomicsectors.Thetableisnotintendedtobecomprehensivenortoimply,totakeoneexample,thatallcreditscoringwithinthefinancialsectoriscurrentlyperformedusingAI.Instead,itismeanttodemonstratethevarietyofusesacrosstheeconomytodayandtoprovideconcreteexamplesofhowworkersmayinteractwithAI,inordertoinformtheidentificationofAIandthediscussionintheremainderofthisdocument.

Table1.IllustrationofAIusecasesacrossvarioussectorsoftheeconomy

Sectors

ExamplesofAIusecases

Accommodationandfoodserviceactivities

Revenuemanagementsystems(e.g.usingforecastingtechnologyfordynamicpricing)

Self-servicecheck-in(e.g.usingchatbotsandimagerecognitionofIDandpaymentmethods)

Workforcemanagement(e.g.usingsoftwaretooptimiseschedulingandpredictshortages)

Administrativeand

supportservice

activities

Expenses(e.g.usingimagerecognitiontoaddreceiptstoexpensereports)Hiringtools(e.g.usingfacialrecognitionsoftwaretoanalyserecordedinterviews)Appointmentscheduling(i.e.usingnaturallanguageprocessingtomanageschedules)

Agriculture,forestryandfishing

Agriculturalrobots(e.g.usingrobotstopickandinspectfruit)

Cropandsoilmonitoring(e.g.usingimagerecognitiontoidentifysoildefects)Predictiveanalytics(e.g.usingsatelliteimagestoforecastweatherandrecommendharvestperiods)

Education

Tutoringandcoaching(e.g.usingstudentdatatopersonaliselessonplans)Translation(e.g.usingspeechrecognitiontotranslateandlive-captionlectures)Contentcreation(e.g.usingdeeplearningtocompilestudyguidesandtests)

Financialandinsuranceactivities

Creditscoring(e.g.usingnon-traditionaldatatoassigncreditscore)

Wealthmanagement(e.g.usingrobo-advisorstoprovideautomatedfinancialadvice)

Frauddetection(e.g.usinganomalydetectiontoalertstafftoblockcertainpayments)

Humanhealthandsocialworkactivities

Bedmanagement(e.g.usingsoftwaretostreamlinepatientflowinhospitals)Healthresearch(e.g.usingbiomarkerstopredictpotentialdrugcandidates)Diagnosis(e.g.usingimagerecognitiontoassessandcharacteriseabnormalities)

Manufacturing

Trainingandsupportdevices(e.g.usingsmart-gogglestotrainemployees)

3ThesamechallengesappearintheprocessofdevelopingdifferentiatedapproachestoAIregulationandpolicy,suchasthosementionedin

Box1.

Oneproposedsolution(Madiega,2021[48])istosteertowardsabroaderdefinitionofAI(tocovercomputationsystemsthatcouldgeneratesimilarrisks)andatechnology-neutraldefinition(inordertocover

currentandfutureAItechniques).However,drawingdefinitionstoobroadlycouldleadtolegaluncertaintyfordevelopersandoperatorsofAIsystemsandtoover-regulation.

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Visualinspection(e.g.usingimagerecognitiontocheckitemsforflaws)Productionplanning(e.g.usingsoftwaretopredictdemandandplanproduction)Predictivemaintenance(e.g.usingdatatoindicatewhenmachinesshouldbeserviced)

Professional,scientificandtechnicalactivities

Scientificresearch(e.g.usingimagerecognitiontoidentifywildanimals)

Legalservices(e.g.usingmachinelearningtosearchcontractsforinconsistencies)Architecture(e.g.usingsoftwaretocreatedigitalrepresentationsofstructures)

Publicadministrationanddefence;compulsorysocialsecurity

Predictivepolicing(e.g.usingcrimedatatoguidewhereandwhentodeployresources)

Chatbotsformunicipalitiesandcities(e.g.usingchatbotstoanswercitizens’questions)

Taxadministration(e.g.usinganomalydetectiontoidentifypotentialfraud)

Transportationand

storage

Surveillance(e.g.usingcomputervisiontoensurecompliancewithsocialdistancing)

Traveloptimisation(e.g.usingdatatoforecasttrafficandplanefficienttravelroutes)

Warehousemanagement(e.g.usingcamerasandscannerstotrackinventory)

Wholesaleandretailtrade

Sales(e.g.usingwearabledevicestoconnectemployeestoinventoryinformation)Inventorymana

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