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The Governance of Physical Artificial Intelligence
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Yingbo Li*1,*, Anamaria-Beatrice Spulber2, and Yucong Duan*3,*
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1HainanUniversity
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2Visionogy
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3HainanUniversity
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*Correspondingauthor: xslwen@outlook.com,duanyucong@hotmail.com
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ABSTRACT
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Physicalartificialintelligencecanprovetobeoneofthemostimportantchallengesoftheartificialintelligence. Thegovernance
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3202
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ofphysicalartificialintelligencewoulddefineitsresponsibleintelligentapplicationinthesociety.
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rpA Introduction
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ArtificialIntelligence(AI)hasgrowntobethefundamentaltechnologyintoday’sworld. Overthelastfewyears,notonlyhas
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AIbeenpopularlyappliedintypicalAIapplicationsofinformationandsignalprocessingsuchasNaturalLanguageProcessing
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6
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(NLP),butithasalsoempoweredalltheotherindustriessuchashealthcareandrobotics. MiriyevandKovac1 proposedto
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]IA.sc[ definetheAIusedinRoboticsasPhysicalArtificialIntelligence(PAI)becausePAIinteractswiththephysicalworld,contrary
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tothenotionoftraditionalDigitalArtificialIntelligence(DAI)appliedindigitalinformationprocessing. Fromthisperspective,
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weproposetoextendthenotionofPAItoamuchwiderdomaintoalsoincludeInternetofThings(IoT),orautomaticdriving
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cars. Tothebestofourknowledge,mostresearchonAIgovernanceislimitedtothedomainofDAI,sointhepresentpaperwe
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proposetooutlinethegovernanceframeworkofPAI.
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1v42920.4032:viXra
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The application of PAI
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IntheproposedconceptofPAIbyMiriyevandMirko1,PAIreferstothetypicalrobotsystem. While,weproposetoextendthe
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conceptofPAItocoverallpotentialapplicationswiththebuilt-inAIperceivingandinteractingbetweenthecyberspaceandthe
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physicalworld. BesidestherobotsystemwiththeAIworkinginanintegratedandlimitphysicalenvironment,thedistributed
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intelligentsystemwithAIcapabilityisthetypicalDistributedPAI.AsshowninFig. 1,PAIcouldbeappliedinandinclude
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multipledistributedindustries,suchasIoT,self-drivingcars,agriculture,healthcareandlogistics.
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WeproposetoclassifyPAIintotwooverlappedkindsasshowninFig.1:IndependentPAIandDistributedPAI.Independent
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PAIreferstotheintelligentdeviceandtherobot1. DistributedPAIbecomesmoreandmorepopularwhentheedgecomputing2
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ismatureandeverydeviceisconnectedtothenetworkinthewiderspace. IoTandedgecomputingaretypicalDistributedPAI
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subdomains. SinceitispopularforeveryintelligentsystemtobeonlineandindividualunitsinDistributedPAIhavestrong
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computingcapabilitiesnow,IndependentPAIandDistributedPAIwilloverlapinmultipleapplications3.
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TheIoTisatypicaldistributedsystemwithaspatialdistributionthatrangesfromasmallspacesuchasaroomtoawider
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areasuchasacity. TheIoTisformedofvarioussensorsthatcapturethesignalsandchangesinthephysicalworld. ItsAI
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powercouldhappeninbothserversideandtheedgeside. BasedontheAIanalysis,IoTcoulddirectlyorindirectlymake
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predictionsinthecyberspacetoinfluencethephysicalworld. Forexample,aself-drivingcarneedstofirstperceiverealtime
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roadsituationsandconnecttotheInternetfornavigation,thenadjustthedrivingbehavior. Theagricultureisoneofthemost
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successfulPAIapplications. Thesensorsintheagricultureincludingcameras,temperaturemeter,hygrometer,etc,monitorthe
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growthoftheplantandpredict,forexample,theoptimalpesticideinterventionandthebestharvestingtime. Inthehealthcare
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industry,families,nursinghomesorhospitalscouldusethebiologicalsensorsandthechemicalsensorstomonitorapatient
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andpredictpotentialriskssuchasfallingorunstablesituationsthroughamonitoringcenter. The"lastmile"istheexpensive
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andhardprobleminthelogisticindustry. AtypicaldistributedAIapplicationcouldhelpwithdeliverytasksthroughdelivery
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robotsanddronesconnectedtoandcommandedbythecenterserver. Anotherexampleistheautomaticsortingrobotthathas
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beenusedinthesortingcenterofthelogistics. ThegeneralframeworkofDistributedPAIisdescribedinFig. 2.
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DAImimicsthebraincapabilityoflogicalthinkingandinductioninhumanbrain,toprocessthedataandsignalsperceived
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byhumaneyesandears. Thehumanbrainisonlyresponsibleforprocessingthesignalsandtransmittingcommandstoother
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partsofthebodysuchasmovement,visionperception,soundperception,digestionandetc. Bycomparison,IndividualPAIis
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likeanindividualhumanbody,whileDistributedPAIfurtherextendstheAIcapabilitiesjustlikethehumansocietyiscomposed
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1
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Figure1. TheapplicationsofDistributedPAI
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ofmultiplehumans.
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DuetotheprobabilisticdataprocessingofthecurrentDAI,decisionsfromDAIareunsubstantial,notbeingabletoreduce
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theuncertaintyofapplications. OntheothersideofpromotingtheapplicationofDAI,theexplainablepropertyofcurrentDAI
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posesincreasinggovernancechallengesagainstnegativeandmaliciouspracticeofDAI,includingdatabiasesandAIfrauds,
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etc. ExplainableAItriestoexplainandunderstandtheinternaloperatingmechanismofAI.DistributedPAIinteractswiththe
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physicalworldwithamuchlargerspatialareaandconsequentlyaccumulatesBigDataAIfootprintswhichincludesmuch
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longerinteractiontrajectoriescrossingcyberspaceandphysicalworld. SoexplainableAIappliedinDistributedPAIhasthe
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advantagetorevealtheinternalmechanismofDAIandtheintegratedhuman-cyber-physicalsocialphenomena.
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PAIneedstocombinemultiplestreamsofinformationincludingmaterials,temperature,vision,sound,etc,crossingmultiple
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modalsfrommultiplesensorsasshowninFig.1. Throughthemixofthemultimodalinformation,PAIbuildscompetitive
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capabilitythatusesmultipletypesofinformationwhichallowsittomakebetterdecisionandbetterprecision,inthecontext
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ofimprecisedatacollection,inconsistentinformationandincompleteknowledgescatteringovervariousabstractionlevels.
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Thevarioussourcesofdataandinformationbringmultiplekindsofdata,whichoutperformasinglesourceofdata,tomake
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real-timedecisionsandpredictions. ThisisasignificantfeatureofPAI.
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The governance of PAI
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ThegovernanceofDAIhasbeenchallengedbyresearchersfromafairnesstosocialimpactperspective. DAIhasbeenfacing
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thechallengesofriskandgovernance4from,butnotlimitedto,thefollowingaspects: 1)Thestorageandtransfersecurity;2)
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Thefakedata;3)Thesocialprivacy;4)Thebiasofthesex,gender,andracebecauseofthelimitedtrainingdatasets.
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Asaconsequencetothemulti-sourceperceptionandmulti-dimensioninteractioninamuchlargerspace,PAI,especially
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DistributedPAI,bringsmoreuncertaintyandriskfromthesocialimpacttothetechnologyinfluence:
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• Theexistenceproblem. PAIespeciallyDistributedPAIsuchasIoTneedsmultiplekindsofsensorstointeractwiththe
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physicalworld. IfPAIisdistributedinalimitedspacesuchasafactory,itwillnotencounterchallengingregulation
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problemsbecauseitisinaninternalspace. However,ifthespaceisextendedtoalargerspacesuchasacitywhichisnot
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underoneuniqueregulation,PAIwillfaceproblemsofsocialregulations.
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• Thedataorganizationproblem. Themultiplesourcesofdatafromthephysicalworldofawiderspacewillincrease
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thestructuralconstructionandintegrationcomplexityofthedataandinformation. TheKnowledgeGraphcouldbethe
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potentialsolutionfortheinformationorganizationinthehierarchicalstructure.
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2/4
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Figure2. DistributedPAI
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• CannikinLaw. ThedevelopmentofPAIdependsonatleast5disciplinesofmaterialsscience,mechanicalengineering,
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chemistry,biologyandcomputerscience. Therefore,theslowerdevelopmentofonedisciplinewillcausetheproblemof
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CannikinlawandprohibitthedevelopmentofPAI.
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• Thesocialacceptance. SimilartothedilemmaofDAI,theubiquitousapplicationofPAIwillcausetheworryofthe
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societyregardingtheincreaseofunemployment,broadeningofthegapinincome,theshrinkingofprivacyspace,etc.
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TheacceptancefrommultipleaspectsofthelawandsocietywillinfluencetheapplicationofPAIintheresearch,the
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industryandthesociety. So,theacceptanceofthesocietyandthecorrespondinglegislationisapotentialfactorforPAI.
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WeillustratesabovegovernanceproblemsofPAIinFigure3. ThedevelopmentofPAIhastoresolvethesefourproblems.
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Conclusion
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WehavesuggestedextendingthenotionofPAItoalargerphysicalspacewiththedistributedapplicationswiththenotionof
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DistributedPAI.ThespatialvarietyofDistributedPAIcouldvaryfromaroomspacetoacityspace,whileitsapplications
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includeIoT,agriculture,andsoforth. SincePAI,especiallyDistributedPAI,perceivesandinteractswithdifferentphysical
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entitiesindifferentspaces,thegovernanceissuesincludingtheexistenceproblemhasbeenchallenged. Wehaveputforwarda
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3/4
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Figure3. PAIgovernanceproblems
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frameworkofgovernanceproblemsofPAIhoweverthisisopentofurtherdiscussionssinceitisaresearchtopicapplyingnot
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onlytotheresearchbutalsothedevelopmentofthewholehumansociety.
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References
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1. Miriyev,Aslan,andMirkoKovacˇ."Skillsforphysicalartificialintelligence."NatureMachineIntelligence2.11(2020):
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658-660.
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