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SUPPORTPOOL
OFEXPERTSPROGRAMME
AIAuditing
ProposalforAlgo-scores
byDr.GemmaGALDONCLAVELL
AIAuditing-ProposalforAlgo-scores
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AspartoftheSPEprogramme,theEDPBmaycommissioncontractorstoprovidereportsandtoolsonspecifictopics.
TheviewsexpressedinthedeliverablesarethoseoftheirauthorsandtheydonotnecessarilyreflecttheofficialpositionoftheEDPB.TheEDPBdoesnotguaranteetheaccuracyoftheinformation
includedinthedeliverables.NeithertheEDPBnoranypersonactingontheEDPB’sbehalfmaybeheldresponsibleforanyusethatmaybemadeoftheinformationcontainedinthedeliverables.
Someexcerptsmayberedactedorremovedfromthedeliverablesastheirpublicationwould
underminetheprotectionoflegitimateinterests,including,interalia,theprivacyandintegrityofanindividualregardingtheprotectionofpersonaldatainaccordancewithRegulation(EU)2018/1725and/orthecommercialinterestsofanaturalorlegalperson.
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TableofContents
1.Introduction 4
1.1.Nutriscore 4
1.2.A+++ 4
2.TowardsanAIalgo-score 5
2.1.Existinginitiatives 5
2.2.Proposalforanalgo-score 6
DocumentinitiallysubmittedinJanuary2023,updatedinJune2024
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1.Introduction
AsAIsystemsproliferateandimpactonpeoples’life-chances,thereisaneedtofacilitatepublicawarenessandunderstandingofhowalgorithmicsystemswork.Theproposalbelowdrawsfromtwoexistingmethodologiesofsignificantsocietalimpact:theNutriscoreandA+++.
1.1.Nutriscore
NutriscorereliesonthecomputationofanutrientprofilingsystemderivedfromtheUnitedKingdomFoodStandardsAgencynutrientprofilingsystem(FSAscore).Thecalculationprocessconsistsofthreesteps.Inthefirststep,thenutritionalscoreofthefoodproductisassessed.Thenextstepis
thedeterminationofRayner'sscore,calculatedinthesamewayforallfoodproducts,withtheexceptionofcheese,vegetableandanimalfatsandoils,anddrinks.Thetwoscoresarethenusedtoclassifythefoodproductonthefive-levelNutri-Scorescale.
totalNscore-totalPscore=Nutritionalscore
Productingredientsnegatively(N)affectingtheNutri-Score
Productingredientspositively(P)affectingtheNutri-Score
Highenergydensityper100gorper100ml
Highsugarcontent
Highcontentofsaturatedfattyacids
Highsaltcontent
Contentoffruits,vegetables,nutsandlegumes
Fibercontent
Proteincontent
Rapeseed,walnutandoliveoilcontent
Basedonthisclassification,thesystemawards0to10pointsforenergyvalueandingredientsthatshouldbelimitedinthediet(saturatedfattyacids,sugarandsalt,etc.)and0to5pointsforbeneficialingredientswhoseconsumptionshouldbepromoted(fiber,protein,fruits,vegetables,legumes,nuts,andrapeseedoil).Todeterminethevalueofthelabelofagivenproduct,i.e.theletterA,B,C,DorE,thesumofpointsawardedforthebeneficialingredientsmustbesubtractedfromthesumofpointsgivenfortheingredientsthatneedtobelimited.Theproductisclassifiedinoneoffivevalueclasses(AtoE)basedonthefinalscore,whichmayvaryfrom-15to+40.Thelowerthescore,thebetterthenutritionalvalueoftheproduct.
1.2.A+++
In1992,theCounciloftheEuropeanCommunitiespublishedEUDirective92/75/EC“toenabletheharmonizationofnationalmeasuresonthepublication,particularlybymeansoflabellingandofproductinformation,ofinformationontheconsumptionofenergyandofotheressentialresources,
andadditionalinformationconcerningcertaintypesofhouseholdappliances,therebyallowingconsumerstochoosemoreenergy-efficientappliances.”Since2010,anewtypeoflabelexiststhatmakesuseofpictogramsratherthanwords,toallowmanufacturerstouseasinglelabelforproductssoldindifferentcountries.Updatedlabellingrequirementsenteredintoforcein2021(EU221/340).
Theenergylabelsareseparatedintoatleastfourcategories:1)Theappliance'sdetails:accordingtoeachappliance,specificdetails,ofthemodelanditsmaterials,2)Energyclass:acolorcodeassociatedtoaletter(fromAtoG)thatgivesanideaoftheappliance'selectricalconsumption,3)Consumption,efficiency,capacity,etc.:thissectiongivesinformationaccordingtoappliancetype,and4)Noise:thenoiseemittedbytheapplianceisdescribedindecibels.
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Forinstance,lampsareclassifiedintoclassAif≤0.240.√Φ+0.0103.Φ,whereΦistheluminousfluxinlmandPisthepowerconsumptionofthelampinW.Calculationsandvaluesaredifferentforhomeappliancessuchasovens,fridgesandairconditioners,bulbs,carsortyres.
2.TowardsanAIalgo-score
Theaboveexamplesshowhowusingvisualcuestoinformcitizens/buyersoftheirchoicesisamethodthathasbeentriedandtestedinotherdomains,wheretheregulatorhasplayedasignificantroleinestablishingthemethodologyandsettingupfollow-upboardsthatcontinuouslyreviewthecalculationalgorithmsusedandproposeupdatestoit.
2.1.Existinginitiatives
2.1.1.AIethicslabel
1
ThepossibilityofanAlgo-scorebeingdevelopedtoguidecitizensandbuyersofAIsystemshasalreadybeenexplored.In2019,theAIEthicsImpactGroupatBertelsmannStiftungproposedanAIethicslabel.Theyreviewed100AIethicsguidelinesandproposedsixkeyvaluestoberated:transparency,accountability,privacy,justice,reliabilityandenvironmentalsustainability.ThescoringisobtainedfromtheVCIOmodel(values,criteria,indicatorsandobservables)thatisusedtodefinetherequirementsneededtoachieveacertainrating.
ThelabelincludesoneratingforeachofthevaluescapturedwiththeVCIO-approach.Inordertodeterminethelevelofcompliance(a,B,C,D,E,F,G),thesystemaggregatesobservablesonthebasisofminimumrequirements,thusmovingawayfromtheNutriscoreapproachwherebadpracticescanbeoffsetbygoodpractices.
Observablesarethenconvertedintoindicators.Thoseindicatorsareintheirturnconvertedintocriteria,andthesecriteriaarefinallyturnedintovalues,andviceversa.
2.1.2.DatasetNutritionLabel
TheDataNutritionProjecttakesinspirationfromnutritionallabelsusedinthefoodindustry.Itenhancescontext,contents,andlegibilityofdatasetsbyhighlightingthe‘ingredients’ofadatasettohelpshedlightonwhetherthedatasetis“healthy”foraparticularusecase.ItsformatisclosertoamedicalleafletthanalabelsuchastheA+++inthatitprovidesastructuredandvisualrepresentationofdatasetcharacteristics(includingdescription,date,author,content,sourceandforeseenusecases)andaseriesof“badges”(tovisualisewhetherasystemhasgonethroughethicsreview,ifithandlespersonalinformation,whetherthesystemisfor-profitornon-for-profit,etc.).Italsoincludesan“alert”scalethatisdesignedtohighlightissues,restrictions,andotherrelevantinformationaboutthedatathatmightnotbeobvioustosomeoneunfamiliarwiththedataset.Thesealerts
includeacolourcodethatshowswhetheraspecificrisk/alertcanbemitigated.
1
Fromprinciplestopractice:HowcanwemakeAIethicsmeasurable?(bertelsmann-stiftung.de)
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2.1.3.Singlefocuslabels
Itisalsoworthmentioningtwoexamplesofsingle-focuslabels:theOpenEthicslabel,
2
whichproposesavoluntaryschemefocusedontheopennessofthetoolsandresultsofanAIsystemandsoassignsvaluetousingopenandnotproprietarytrainingdata,opensourcecode,andunrestricteddecisionspaces.Ontheotherhand,LelabelNumériqueResponsable,developedbytheInstituteforSustainableITinpartnershipwiththeFrenchMinistryofEcologicalTransition,ADEME,andtheWWF,isfocusedonissuesofsustainabilityanddigitalenvironmentalimpact.Ithasbeendesignedtobeusedbybothcommunitiesanddigitalservicesbusinessesanditisbasedon4themesand14broadprincipleswhichcoverdiversecommitmentsinareassuchasgovernance,participation,proactivity,inclusivityandsoftwaremanagement.
2.2.Proposalforanalgo-score
Theanalysisaboveshowsthepossibilitiesandlimitationsofexistinglabels,andpointtotheissuesthatneedtobetakenintoaccounttodevelopalabelforAI-relatedtechnicalsystems.
AscoringmethodologybasedontheNutriscoremodelwouldnotworkwhenrankingtechnologicaldevelopmentsasitimpliesthatbadpracticescanbe“compensated”bygoodpractices.Thiswouldprobablybeunacceptableformanystakeholders.AsystembasedontheA+++modelisalsonotanimmediatelyusefulreferenceasitisbasedonsharedandagreedonvaluesofimpact.Namely,electricityconsumptionandnoiseindicators.
AsforthemethodsdevelopedspecificallyforAIsystems,whichhavenotyetbeenimplemented,theyposeseveralchallenges.TheDatasetNutritionLabel,ontheonehand,ismoreofatransparencytoolthanamethodtocomparebetweensystems.Asitoffersmultiplepossibilitiesforgraphicallyrepresentingtechnicalsystems,andasthosesystemsmaybeverydiverse,itishighlylikelythatsystemswouldusenon-comparableindicators.Thisdoesnotmeanthatthemethodproposeddoesnothavevalue,butitsusefulnessdeviatesfromasystemusedtofacilitateconsumerchoice.
TheAIethicslabelisbyfarthemostdevelopedmethodtoassesscompliance.However,itdoesnotlooklikeithasmanagedtogettractionsinceitwasreleasedin2019.Someofitsshortcomingsareprobablylinkedtotheincentivestoadoptsuchamodel,butalsotothefactthatitissomewhatremovedfromlegalcompliancerequirements-eventhoughthesecouldbeemphasized.
Takingthelessonsfromthesepreviousefforts,andthenameandimagerecognitionofexistingsystems,theproposalbelowbeginstosketchthemethodologythatcouldhelppushforwardapracticalproposalforavisualsystemdesignedtopromotetransparency,accountabilityandconsumerchoice.
TheproposaltakesasareferencetheA+++method,andspecifically3ofitsattributes:
-Itisimmediatelyrecognizable
-Itallowsforamainmeasureofspecificvariables,butalsoothericonsthataredeemedrelevant
-Itisamethodthatgeneratesincentivestoimproveinthealphabeticalscale
Additionally,initsuseinappliances,theA+++labelhasproventobeabletoincorporatedifferentmeasuresfordifferentappliancetypes(fromfridgestotyres).Thisopensthepossibilityfordifferenttechnicalsystemstouseslightlydifferentmethods,andthustheuseofthesamelabelandrecognizableimageforrecommendersystems,socialmediaplatforms,LLMsandbiometricssystems.
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OpenEthicsLabel–OpenEthicsInitiative
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Basedontheabove,weproposealabelthatcapturesthree“levels”ofanalysis:
-AIgovernance:appointmentoftherelevantgovernancepositions(DPO,AIofficer,etc),compliancewithrelevantstandards(ISO/IEC42001,23894,23053,24027,etc),documentationofkeyriskassessmentdocuments(DPIA,conformityassessment,environmentalimpactassessment,etc.),transparencydocuments(AIleaflet,etc.),dataprovenancecertifications,andlinkstoopendata/sources.
-Modelfairnessandperformance:DatasheetsforDatasets,Modelcard/s,keymetrics(fairness,robustness,security,accuracy…,etc),keyattributes,experimentaltesting(redteaming,etc.)
-Post-marketmonitoringandauditing:regularbiasaudits,incidentreporting,effectiverecourseandredressmechanismsandmetrics
AnissuethatisnoteasytoexportformtheA+++methodologytoAIistheuseofanagreed-uponmeasureofcalculationsuchaswatts.Therefore,theproposalisforthesystemtoassesstheexistence/complianceofdifferentexercisesandsupportingdocumentation.Havingcompletedspecifictaskswouldallowthosesubjectedtothelabelassessmentt
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