谷歌 -利用 AI 构建科学未来政策框架 A Policy Framework for Building the Future of Science with AI

GoogleFebruary2025

APolicyFrameworkforBuildingthe

FutureofSciencewithAI

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ExecutiveSummary

Introduction:

ANewEraofAI-enabledScientificDiscovery

PillarOne:

Infrastructure—IncreaseAccesstoAIInfrastructure

1.1NationalandInternationalPoolsofData,Models,Compute,andSoftware

1.2DataAccessibilityandSoftwareInteroperability

PillarTwo:

Investment—InvestintheScienceofAI

2.1AIProgramsandInitiativesthatDriveSociallyBeneficialScientificInnovations

2.2InterdisciplinaryResearchtoStrengthenCollaboration

2.3BuildingaStrongPoolofTalent

PillarThree:

Innovation—ImplementPro-ScienceandInnovationLegalFrameworks

3.1HarmonizedRegulationsforResponsibleandReasonableUseofData

3.2RegulationsthatFacilitateResponsibleAIProgress

Conclusion

Appendix:

IllustrationsofAI’sTransformationalImpactonScience

01–ExecutiveSummary

ExecutiveSummary

Artificialintelligence(AI)isusheringinaneweraofscientificdiscovery,

revolutionizinghowweconductresearch,andacceleratingthepaceof

scientificbreakthroughs.AI’sabilitytoprocessvastamountsofdata,iden-tifypatterns,andgeneratenovelhypothesescanhelpscientistsanswerquestionsaboutproblemsthatwereoncethoughttobeunsolvablein

ourlifetimes.

Thesearenotpromisesprojectedintoahazy

future.AIisalreadyadvancingscienceandchang-inglivestoday.Machinelearningandprediction

technologiesarehelpingdiagnose

geneticdis-

eases

,

identifycancer

earlier,

developvaccines

,

predictweather,

wildfires

,and

floods

,andaccel-erate

progresstowardssustainabledevelopment

goals(SDGs)

.Behindthesepracticaltoolsare

AI-basedapproachestofundamentalscientific

researchinnumerousfields,including

physics

,

neu-

roscience

,

earthsciences

,

oceanography,

space

exploration

,

fusionenergy,

and

climate

science

,

amongothers.

Followingthesuccessesoftoday,thereismuch

moretobegainedfromAIinscientificbreak-

throughstomorrow.Governmentsaroundthe

worldcantakecriticalstepstoempowerscientiststodiscovernewdrugs,findtreatmentsforcancer,detectandmitigatenaturaldisasters,drive

towardsustainabledevelopmentgoals(SDGs),andmuchmore.

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI3

01–ExecutiveSummary

Thispaperoutlinesthreespecificpolicypillars–the“threeI’s”–thatgovernmentscanpursuetoensureAIpositivelyimpactsscienceandbenefitseveryone:

•Infrastructure—IncreaseAccesstoAI

Infrastructure:

High-qualityscientificdataandcomputationalresourcescanunlockAI-poweredscien-

tificsolutions.Toaddresstheunevenglobaldistributionoftheseresourcesforscientistsandtofosterinternationalcollaboration,

policymakersshouldestablishnational–

andaninternational–centerstoprovideAI

toolsandresourcesforadvancingscience.

Thesecenterswouldprovideaccesstodata,computational,andeducationalresourcesforleveragingAIforscientificwork.

•Investment—InvestintheScienceofAI:

Sustainedgovernmentfundingiscrucialforambitious,long-termscientificresearch,suchasspaceexplorationordevelopingcarbon

managementtechnologies.Togetthere,

governmentsshouldcreatealistofpriority

areastodirecttheirfundingandcreatepublicchallengesforsolvingthemostpressing

issues.Novelpublic-privatepartnershipsandfundingmodelscanplayanimportantroleinfosteringathrivingAI-for-scienceecosystemandbuildingastrongpooloftalent.

•Innovation—ImplementPro-ScienceandInnovationLegalFrameworks:

Sciencethrivesoncollaborationandthe

openexchangeofinformation.Globallegal

frameworkscanprotectthemarketplaceofscientificideas.Governmentsshouldwork

togethertocreateharmonized,interoperableregulationstoencouragecontinuedscientificprogress,especiallyinareaslikecopy-

right,privacy,andcross-borderdataflows.GovernmentsaimingtoleadontheuseofAIforscienceshouldalsocraftimmigrationpoli-ciestoattractandretainAI-skilledtalent.

Therecommendationsinthispaperarebased

onlessonslearnedfrommanyyearsofscientific

researchacrossGoogleandGoogleDeepMind,andbuildona

recentessay

1,whichexploreshowAIistransformingeveryscientificdiscipline.Bytakingdecisiveactionalongthese“threeI”policypillars,governmentscanharnessAItounlockscientific

advancement,establishtheircountriesaslead-ersandbeneficiariesofthisprogress,andworktogethertotackleglobalchallenges.Ifwebuildthisenablingpolicyenvironment,wecanreal-izeAI’sremarkablepotentialtoachievescientificbreakthroughs.

1Aspartofourefforttoexpandanddeepenpublicdialoguearound

scienceandAI,GoogleDeepMindco-hostedthe

AIforScienceForum

withtheUKRoyalSocietyinlateNovember.Aspartofthisevent,

Googlealsoannounceda$20millionfundforAIinSciencetodrive

AI-enabledscientificdiscoveryandincubatemoreachievementsthatwillimprovethelivesofmillionsofpeople.

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI4

02

Introduction:

ANewEraofAI-enabledScientificDiscovery

02–Introduction:ANewEraofAI-enabledScientificDiscovery

Sciencehasbeenthecornerstoneofhumanprogress,fromGalileo’s

telescoperevealingthecosmostotheLargeHadronCollider’spotentialtorevolutionizephysicsandourunderstandingofmatter.Ithasempoweredustounderstandourworld,whetheratthesubatomicleveloritsplaceinthevastexpanseoftheuniverse.Scienceisnotjustapursuitof

knowledge;itisfundamentaltoimprovingeverydaylife,drivinginnovation,andshapingthefutureforeveryone.

Manyoftheconfoundingproblemsinscience

benefitfromtheuseofadvancedcomputationaltechniquesenabledbyAI,thusmakingAIapow-erfultooltoassistscientistsintheirendeavors.

ThecurrentrevolutioninsciencedrivenbyAIis

notaboutreplacinghumanscientists,butabout

augmentingtheircapabilitiestoanunprecedenteddegree.AI’struepowerliesinitsabilitytodramat-icallyacceleratethescientificprocess,sometimescondensinghundredsoreventhousandsofyearsoftraditionalexperimentationandresearchinto

afewmonthsordays,inareaslike

drugdiscov-

ery,

materialsscience

,and

diseasediagnosis

.

Moreover,AItoolsaremakingcomplexanalysesofvastamountsofdatapossibleandaccessibletoawidercommunityofresearchersthaneverbefore,fosteringcollaborationandopeningupentirelynewavenuesofinquiry.Inessence,AIisnotjustmakingsciencefaster,it’smakingitbroader,deeper,andmoreaccessible,usheringinaneraofdiscovery

withthepotentialtoaddresssomeofhumanity’smostpressingchallenges.

TheglobalpublicseesvalueincurrentapplicationsofAIandismostexcitedbyAI’sabilitytobenefitsocietybypoweringscientificdiscovery,advancinghealthcareandmedicine.7in10peoplegloballyexpectAItohaveapositiveimpactonscience(72%)and

medicine(71%)leadingalistofpromisingapplications,suchasagriculture(60%)andcybersecurity(57%).

Source:

Google-IpsosstudyonglobalpublicperceptionsofAI

(Jan2025)

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI6

02–Introduction:ANewEraofAI-enabledScientificDiscovery

Today,AIusedinnaturalsciencesisaccelerat-

ingdiscoveriesatanunprecedentedpace.For

example,instructuralbiology,itusedtobethat

x-raycrystallographywasthefastestrouteto

insightsaboutthestructureofproteins.Asingle

experimentcouldtakeyearsofworkandcost

$100,000,dependingontheprotein.Now,GoogleDeepMind’s

AlphaFold

,whichpredictsthe3D

structureofproteins,hasledtoapublicly-available

ProteinStructureDatabase

thatprovidesinstant

accessto200millionpredictedproteinstructuresforfree.Thisdatabaseisavailablepubliclyand

hasreceivedmorethan2.5Musersfromover190

countriestoday.

AlphaMissense

,whichbuildson

AlphaFold,predictsthepathogenicityofmissensevariants—singlelettersubstitutionsinDNA,poten-tiallyacceleratingdiagnosisandthedevelopmentoflife-savingtreatmentsforconditionslikecancer.Furthermore,AIistransformingmaterialsscience,asdemonstratedbyGoogleDeepMind’s

GNoME

,whichhasdiscoveredmillionsofnewcrystal

structures,acceleratingadvancementsinareas

likebatteryandsemiconductortechnology.GNoMEsuccessfullydiscovered2.2Mnewcrystals-equiv-alenttonearly800yearsworthofknowledgefromclassicalresearchtechniques.ImagineAIpower-ingmorescientificdiscoverytoolslikeAlphaFold,AlphaMissense,andGNoMeintheyearstocome

anditseffectonacceleratedprogress.

Inclimatescienceandsustainability,AIis

provingtobeaninvaluabletoolformodeling,

forecasting,andmitigationefforts.AIenhancestheanalysisofvastclimatedatafromsourceslikesatellitesandweatherstations,leadingtomoreaccurateclimatemodels,suchas

NeuralGCM

,

whichsignificantlyoutperformstraditional

physics-basedmodelsinspeedandaccuracy.

NeuralGCMmodelsarepublicly-availabletothescientificcommunitytobuildupon.AIalsoaidsinpredictingnaturaldisasterslike

floods

,enablingadvancedwarningsandpreparedness.Google’sfloodforecastingAImodelpredictsfloodsinover100countries,helpingapopulationofmorethan

700millionpeople.Additionally,AIisbeingused

for

wildfiredetection

.Google’swildfiredetectionAI

modelsprovideamapofreal-timeboundariesof

largewildfiresevery10–15minutes,currentlyavail-

ablein27countriesandexpandingtomore.

FireSat

,

anongoingprojecttobuildanAI-poweredsatellite

constellation,aimstodetectwildfiresanywhere

aroundtheworldwithintwentyminutesandto

allowscientistsandAIexpertstostudyfirepropa-

gation.AIcanaccelerateclimateresearchtomove

ustowardasustainablefutureand

accelerateprog-

resstowardsthe

SDGs.Infact,AIhasthepotential

tohelp

mitigate5-10%

ofglobalgreenhousegas

(GHG)emissionsby2030—theequivalentofthe

totalannualemissionsoftheEuropeanUnion.

AIisalsoopeningnewavenuestoscientificappli-cationsintheenergysector,fromharnessing

renewableenergysourcestothepromiseof

nearlylimitless,cleanenergyfromnuclearfusion.Thevariabilityandunpredictabilityofrenewable

energysourceslikewindandsolarhastraditionallybeenachallengeinoptimizingthepowergrid.AIisaddressingthischallengebyenablingreal-timedataanalysisandpredictivemodeling,forecastingenergyproductionfromrenewablesourceswith

highaccuracy.

Smartgrids

useAItodynamically

balancesupplyanddemand,optimizeenergy

storage,andmanagedistributedenergysources,

therebymitigatingtheimpactoffluctuationsin

renewableenergygeneration.AIisalsoplayingacrucialroleinnuclearfusionresearch,fromdiscov-eringhowto

containtheplasmainatokamak

to

optimizingplasmaperformance

inanuclearfusionreactor.

HealthcarepresentssomeofthemostpromisingusecasesforAI.AdvancesinAIpromiseastep-

changeimprovementinbothdiseasedetectionandtreatment,especiallyinlow-resourcecommunitiesandregionsoftheworld.AI-poweredtechnologieshavealreadyhelpedscientists

developvaccines

,diagnose

geneticdiseases

,and

identifycancer

earlier.

AIcanaccuratelyinterpretretinalscanstodetectdiabeticretinopathy,apreventablecauseofblindnessthataffectsroughly100millionpeople.

Google’s

floodforecastingAImodel

predictsextremeriverineeventsin

over100

countries

andareaswhere700millionpeoplelive.Thismodelisintegratedinto

Google’sFloodHubplatform

,GoogleSearch,andGoogleMapsforeveryonetouse.

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI7

02–Introduction:ANewEraofAI-enabledScientificDiscovery

MedGemini

isanotherexampleofdemocratizingaccesstohigh-quality,personalizedhealthcarewith

generativeAI

.

Quantum

isanotherareawherewe’rebeginning

toseeconstructivefeedbackloopsbetweenAI

andscientificdiscovery.Recentachievementsin

quantumprocessors

andquantumcomputingare

openingthepossibilityofstudyingquestionsthat

werepreviouslytherealmofsciencefiction,like

studyingthecharacteristicsof

traversableworm-

holes

andopeningupnewpossibilitiesfortesting

quantumgravitytheories.AIisadvancingourprog-

ressinquantumphysicsandquantumcomputing,

evenasquantumishelpingadvanceresearchinAI.

Incredibly,theseremarkableadvancements,

unprecedentedinhumanhistory,representjustthebeginningofAI’spotentialcontributionstoscience.Thereismuchmorethattheglobalscientificcom-munitycandotounlockthefullpotentialofthis

technologytobenefithumanity.

Butscientistscan’tachievethesebenefitsalone.Theyrelyonanecosystemthatgovernments,in

partnershipwithacademiaandindustry,canculti-vate—anenvironmentthatprovidesmuch-neededinfrastructure,robustfunding,asteadypipelineofskilledtalent,andrelevanteducationandtrain-ingprograms.Beyondinfrastructureandother

resourceinvestments,governmentscanaddresssocieties’mostpressingissuesbyestablishingpro-innovationpoliciesthatenablefoundationalscientificandtechnologicalbreakthroughs.

WithoutpoliciesaimedatfosteringAI-drivensci-entificprogress,countriesriskbeingleftbehind

asothernationsdriveinnovationandeconomic

growth.BecausetheunderlyingAItechnology

empoweringscientificadvancementsevolves

rapidly,regulatoryframeworksneedtobetech-

nology-agnosticandadaptabletokeeppaceandavoidbecomingobsolete.Wesharepolicymakers’commitmenttomanagingAI’sriskswithappro-

priateguardrailsandweemphasizethe

needfor

abalancedregulatoryapproach

that

prioritizes

research,innovation,scienceandtechnology

whileestablishingregulationstoaddressrisks.

2

Investment

InvestintheScienceofAI

Sustainedgovernmentfundingandnovelpublic-privatepartnershipsforpursuingambitiousscientific

goals

3

Innovation

ImplementPro-InnovationLegalFrameworks

Harmonized,interoperablereg-ulationstoencouragecontinuedscientificprogressandattractinginvestment

ThispolicypaperisdesignedtoserveasablueprintforpolicymakersaroundtheworldtoestablishpoliciesthatunlockAI’sbenefitsforscientificprogress.Weoutlinepolicyrecommendationsacrossthreepillars:

1

Infrastructure

IncreaseAccesstoAIInfrastructure

NationalandinternationalresourcecentersthatprovideAItoolsand

resourcesforadvancingscience

Together,wecanworktosolvechallengesthatweoncethoughtwereinsurmountable.Butfirst,weneedapolicyenvironmentthatenablesthetransformativepowerofAIforscientificdiscovery.

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI8

02–Introduction:ANewEraofAI-enabledScientificDiscovery

NaturalSciences

Connectomics

Mappinga3D,nanoscale-

ClimateScience&Sustainability

FloodForecasting

AnAImodelthatreliablypre-dictsextremeriverineeventsatuptoafive-dayleadtime.

resolutionmapofapieceofthehumanbraintoalevelofdetailneverpreviouslyseen.

Energy

TORAX

Anopensourceplasmacoresimulator,whichenablesnewdirectionsforplasmascenariodesignandacceleratesthe

researchinthefusionspace.

Mathematics

AlphaGeometry

Solved83%ofallhistoricalInternationalMathematicalOlympiad(IMO)geometryproblems.

AIis

accelerating

scientific

progress

Additionalexamplesbelow*

HealthSciences

BreastCancerPrediction

AnAI-poweredsystem,whichintegratesintobreastcancerscreeningworkflowstohelp

radiologistsidentifybreastcancerearlierandmore

consistently.

Education

LearnLM

Afamilyofmodelsfine-tunedforlearning,basedonlearningscienceprinciples.

QuantumComputing

Willow

Cracksakeychallengein

quantumerrorcorrectionthatthefieldhaspursuedforalmost30years.

*ForadditionalexamplesofAI-drivenscientificbreakthroughssee

Appendix

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI9

03

PillarOne:

Infrastructure—IncreaseAccesstoAIInfrastructure

1.1NationalandInternationalPoolsofData,Models,Compute,andSoftware

1.2DataAccessibilityandSoftwareInteroperability

03–PillarOne:Infrastructure—IncreaseAccesstoAIInfrastructure

AIadoptioninscientificcontextsisparticularlychallengingduetoseveralfactors,suchasaccesstohigh-quality,specializeddata,constraintsonaccesstocomputingpower,andtheneedforinterdisciplinarycollabora-tionamongAIanddomainexperts.

Lackinganorchestratedinfrastructurefor

AI-poweredscientificresearchanddevelopment

(R&D),scientistsmustspendsignificanttimeandefforttocoordinatedataandmodelaccess,securecomputingpower,andbecomeproficientwithAI

tools,allofwhichdetractsfromtheircoreresearchactivities.AlthoughmostscientistswillnotneedtotraintheirownlargeAImodel,theywillneverthe-lessneedaccesstoresourcestofine-tunelarge

modelsonscientificknowledge,runsimulationstogeneratehigh-qualitydata,or

train(oftenrelatively

small)

AImodelsontheirspecializeddata.

Loweringtheentrybarrierstodeveloping,using,anddeployingscience-focusedAItechniques

isessentialformaximizingaccesstoresources

forscientistsaroundtheworld,includinginless-well-resourcedinstitutionsorcountries.Asthe

RoyalSocietyexplainedinitsrecent

AIinScience

report

,“ScientistsfromdiversedisciplinesrequireaccesstoinfrastructuretoadoptmorecomplexAItechniques,processhighervolume[s]andtypesofdata,andensurequalityinAI-basedresearch”.Thereisthereforeagrowingneedtoexpand

accesstocomputecapacity,data,AImodels,soft-ware,andtoolstoawiderrangeofresearchersinordertoacceleratecollaborative,AI-driven

scientificresearch.

Worldwide,manygovernmentshaverecognized

thisneedandhavebeguncreatingnational

resourcesanddatarepositoriesforAIresearch.Forinstance,

INDIAai

servesasacentralizedrepositoryofAIdatasetsacrosscriticalsectorslikehealth-

care,agriculture,finance,andeducation,aiming

todemocratizeaccesstohigh-qualitydataand

spurinnovation.IntheU.S.,

D

aggregates

datasetsfromvariousgovernmentagencies.Effortsfromtheprivatesector,suchasGoogle’s

Data

Commons

,hasalsocontributedtodemocratizingdataaccessbycentralizingandstreamliningpub-liclyavailabledatafromdiversesources.Academicinstitutionsalsohavecollaboratedandestab-

lishedjointdatarepositories,likethe

NationalData

Platform

,toboostresearcheraccesstobothdataandfunding.Morerecently,anindustry-academiacollaborationhasresultedinalarge-scalescientificdatarepository,called

TheWell

,whichcontains

15TBofphysicssimulationscoveringdiverse

scientificdomains.Althoughtheseeffortshave

increaseddataavailability,thereisstillmuchtobe

donetostreamlineaccesstovariousdatasites,

models,priorscientificart,andsimulationtoolsforscientificresearch.

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI11

03–PillarOne:Infrastructure—IncreaseAccesstoAIInfrastructure

Scientificdiscoverytypicallyreliesheavilyon

simulatingphysicalphenomena.High-performancecomputationalmodelsandsimulations,combined

withdatafromexperimentsandobservations,areessentialtoadvanceourunderstandingofphysicalsystemsandprocesses.Buildingsolutionstosimu-latecomplexsystemshasbeenoneoftheprimarymissionsofthescienceandengineeringcommu-

nityoverthepast50years.Scientistsare

already

leveragingAI

togeneratereliablesimulationsacrossvariousfields,suchasaerospace,automotive,

electronics,andoptics.Theycanalsoaccelerate

dataselection,curation,andevenscientificdatagenerationthroughsimulations.Althoughmany

toolsexistforbuildingsimulations(e.g.,Ansys

mul-

tiphysicssimulation

),thepowerofAIisnotyetfullyharnessedtotransformlarge-scalesimulationof

complexphenomenainphysics,biology,chemistry,andotherscientificdomains.

PlatformsthatenablethesharingofAImodelsarealsoessentialforfosteringanopenecosystemthatacceleratesAIadoptionandencouragescollabo-

rationacrossdiversefields.Forinstance,

VertexAI

Studio

and

HuggingFace

facilitateaccesstoAI

modelsandrapidprototyping.However,tofully

leverageAIforscientificprogress,newinnovationsareneededtoprovideseamless,AI-readyplatformsforscientificresearchanddiscovery.Below,we

recommendpolicyoptionstoestablishandexpandaninfrastructuresupportiveofAI-powered

scientificresearch.

1.1NationalandInternationalPoolsofData,Models,Compute,andSoftware

CreatenationalAIforscienceresourcecenterstomakedata,AImodels,computecapacity,

softwareandtoolsaccessibleforscientific

research.Thesenationalresourcecenterscouldalsocoordinatewithaninternationalcenter

designedtofacilitatetheuseofAIforglobalscientificcollaborationandprogress.

Countriesmustbuildtheinfrastructurenecessarytoempowertheirscientistswiththetoolsthey

needtobedramaticallymoreeffectiveinsolv-

ingpressingchallengeslikediseaseeradication,sufficientsuppliesofenergy,andfoodsecurity.AccomplishingthiswillrequiremakingAI-enabledresearchtoolsandresourcesmoreaccessible

tomorescientistsinmoreplaces.Public-private

partnershipstobuildinfrastructureforscienceisanenablerforAI-poweredscientificprogressbyreducingunnecessaryobstaclestoinnovationandfosteringbroadercollaborations.

TheU.S.government,inpartnershipwiththe

privatesector,hasstartedtopilotthe

National

AIResearchResource(NAIRR)

,aresearchinfra-

structuredesignedtodemocratizeaccesstoAI

R&D.Byprovidingcomputational,data,software,andtrainingresources,NAIRRaimstofacilitate

AIresearch.Whilecurrentlyinitspilotphaseand

requiringfurtherfundingtoachieveitsfullpoten-tial,NAIRRservesasavaluablemodelfornations

seekingtoestablisharobustinfrastructurefor

AI-poweredscientificresearch.Recently,theUKinits

AIOpportunitiesActionPlan

laidoutitsstrategytoexpandthecapacityofitsAIResearchResource(AIRR)byatleast20xby2030.Atthegloballevel,theUNhas

recommended

aGlobalFundforAIandaCapacityDevelopmentNetwork,whichaimto

addresstheunderlyingcapacityandcollaborationgapsforcountrieswithlimitedAIresourcesand

provideaccesstoAIexpertise,computingpower,andtrainingdata.Governmentscouldbuildon

thesemodelstoincreaseaccesstoresourcesforscientificresearchbothnationallyandglobally.

Infrastructuresupportiveofscientificresearch,

however,requiresresourcesbeyondjustcomputetoempowerscientistsfromdiversebackgrounds

toeffectivelyaccessdata,conductexperiments,

compareexistingsolutions,andbuilduponprior

scientificwork.Nationalscienceresourcecen-

ters—andaninternationalanalogue—could

encompasshigh-performancecomputing(HPC)

clusters,sharedscientificdatasets,AImodels(e.g.,thoseusedforclimatemodeling),toolsforsimu-

lationsanddatageneration,andutilitysoftware

thatenableseamlessintegrationofAIsolutionsin

scientificresearch(e.g.,

managingdatadependen-

cies

).Althoughthescientificcommunityhasmadestridestowardsintegrateddatadeliveryandaccessandsharedstorageandcomputingresources

forscientificdata(forexample,seethe

National

ScienceDataFabric

),governmentsshouldnot

stopatthesefewefforts,butcontinuetodedicatefundingandworktowardexpandingsucheffortstomeetscientificdemand.

GcceAPolicyFrameworkforBuildingtheFutureofSciencewithAI12

03–PillarOne:Infrastructure—IncreaseAccesstoAIInfrastructure

Manyscientificbreakthroughshaveresultedfrominternationalcollaboration.Aglobalpoolof

sharedresourcesforscientificresearchwould

fostersuchcollaborationindifferentfields.This

poolwouldenablescientiststoaccessdata,

collaborateglobally,efficientlyexecuteAI-basedexperiments,andadvanceresource-heavyscien-tificdiscoveriestowardssolvingthemostpressinglocalandglobalissues.AninternationalAIfor

scienceresourcecenterwouldprovideinfrastruc-turefornationalcenterstosharebestpractices

andcoordinateresourceneedsinthepursuitofAI-poweredscientificdiscovery.

AIforscienceresourcecenterscouldundertakearangeofactivities.Forexample,theycould:

•Issueperiodicrequestsforproposalsin

priorityresearchareasthatwouldallowscien-tistsandorganizationstoapplyforcompute

time.

•Solicitproposalsfocusedoncreatinghigh-qualityscientificdatasetswheregapsexist.

•Hostpublicchallengesthatnecessitatecollab-oration,creativity,andaccesstodiversedata.

•Provideeducationalresourcestoempower

scientistswhoarenovicesinAItoleverageAItools.

•Pooldatafromdiversegeographies,econo-mies,andculturestocreaterepresentative,

highqualitydatasetsforuseinkeydisciplinese.g.healthcare.

Leveragepublic-privatepartnershipstobuildtrainingmaterialsforscientiststouseAI

infrastructure.

NavigatingadvancedAItools,nationalorglobal

computationalresources,orhyper-scalesuper-

computersisnottrivialforthosewhoseexpertiseliesoutsideofAI.TutorialsaimedatscientistscouldguidelearnersfrombasicAIskillstomanaging

l