生成式AI展望-斯坦福人類-AI中心 -Generative AI - Perspectives from Stanford HAI - How do you think generative AI will affect your field and society going forward

March2023

GenerativeAI:

Perspectivesfrom

StanfordHAI

HowdoyouthinkgenerativeAIwillaffectyourfieldandsocietygoingforward?

1

TableofContents

3

4

Introduction

6

UpendingHealthcare,fromPatientCaretoBilling,CurtLanglotz

AI’sGreatInflectionPoint,Fei-FeiLi

ThePotentialsofSyntheticPatients,RussAltman

7

8

10

PoetryWillNotOptimize:CreativityintheAgeofAI,MicheleElam

13

TheNewCambrianEra:‘ScientificExcitement,Anxiety’,PercyLiang15

ACalltoAugment–NotAutomate–Workers,ErikBrynjolfsson

AnAIWindowintoNature,SuryaGanguli

TheNewToolsofDailyLife,JamesLanday

11

GenerativeAIandtheRuleofLaw,DanielE.Ho

16

18

TheReinventionofWork,ChristopherD.Manning

InEducation,a‘DisasterintheMaking’,RobReich20

SolvingInequalitiesintheEducationSystem,PeterNorvig21

Introduction:

ThecurrentwaveofgenerativeAIisasubsetofartificialintelligencethat,

basedonatextualprompt,generatesnovelcontent.ChatGPTmightwrite

anessay,Midjourneycouldcreatebeautifulillustrations,orMusicLMcould

composeajingle.MostmoderngenerativeAIispoweredby

foundation

models

,orAImodelstrainedonbroaddatausingself-supervisionatscale,

thenadaptedtoawiderangeofdownstreamtasks.

Theopportunitiesthesemodelspresentforourlives,ourcommunities,and

oursocietyarevast,asaretheriskstheypose.Whileontheonehand,they

mayseamlesslycomplementhumanlabor,makingusmoreproductiveand

creative,ontheother,theycouldamplifythebiaswealreadyexperienceor

undermineourtrustofinformation.

Webelievethatinterdisciplinarycollaborationisessentialinensuringthese

technologiesbenefitusall.ThefollowingareperspectivesfromStanford

leadersinmedicine,science,engineering,humanities,andthesocialsciences

onhowgenerativeAImightaffecttheirfieldsandourworld.Somestudy

theimpactoftechnologyonsociety,othersstudyhowtobestapplythese

technologiestoadvancetheirfield,andothershavedevelopedthetechnical

principlesofthealgorithmsthatunderliefoundationmodels.

3

4

AI’sGreatInflectionPoint

Fei-FeiLi,SequoiaCapitalProfessorintheComputerScienceDepartment;DenningCo-DirectorofStanfordHAI

540millionyearsago,thenumberofanimalspeciesexplodedinaveryshorttimeperiod.Therearemanytheoriesastowhathappened,butonehascapturedmyattention:thesuddenonsetandensuingevolutionofvision.Today,visualperceptionisamajorsensorysystemandthehumanmindcanrecognizepatternsintheworldandgeneratemodelsorconceptsbasedonthesepatterns.Endowingmachineswiththesecapabilities,generativecapabilities,hasbeenadreamformanygenerationsofAIscientists.Thereisalonghistoryofalgorithmicattemptsatgenerativemodelswithvaryingdegreesofprogress.In1966,researchersatMITdevelopedthe“SummerVisionProject”toeffectivelyconstruct“asignificantpartofthevisualsystem”withtechnology.Thiswasthebeginningofthefieldofcomputervisionandimagegeneration.

Recently,duetotheprofoundandinterconnectedconceptsofdeeplearningandlargedata,weseemtohavereachedaninflectionpointintheabilityofmachinestogeneratelanguage,image,audio,andmore.WhilebuildingAItoseewhathumanscanseewastheinspirationforcomputervision,weshouldnowbelookingbeyondthistobuildingAItoseewhathumanscan’tsee.HowcanweusegenerativeAItoaugmentourvision?Thoughtheexactfigureisdisputed,

deathsduetomedicalerror

intheU.S.isasignificantproblem.GenerativeAImodelscouldassisthealthcareprovidersinseeingpotentialissuesthattheymayhaveotherwisemissed.Furthermore,ifthemistakesareduetominimalexposuretorare

GenerativeAI:PerspectivesfromStanfordHAI

situations,generativeAIcancreatesimulatedversionsofthisraredatatofurthertraintheAImodelsorthehealthcareprovidersthemselves.

Additionally,beforeweevenstartdeveloping

newgenerativetools,weneedtofocusonwhat

peoplewantfromthesetools.Inarecentprojectto

benchmarkroboticstasksbyourlab,beforeeven

startingtheresearch,theprojectteamdidalarge-

scaleuserstudytoaskpeoplehowmuchtheywould

benefitifarobotdidthesecertaintasksforthem.

Thewinningtaskswerethefocusoftheresearch.

Endowingmachineswith

thesecapabilities,generative

capabilities,hasbeena

dreamformanygenerations

ofAIscientists.

Tofullyrealizethesignificantopportunitythat

generativeAIcreates,weneedtoalsoevaluatethe

associatedrisks.JoyBuolamwiniledastudytitled

“GenderShades,”

whichfoundAIsystemsfrequently

failtorecognizewomenandpeopleofcolor.Study

resultswerepublishedin2018.Wecontinuetosee

similarbiasingenerativeAImodels,specificallyfor

underrepresentedpopulations.

5

AI’sGreatInflectionPoint(cont，d)

GenerativeAI:Perspectives

fromStanfordHAI

Theabilitytodeterminewhetheranimagewas

generatedusingAIisalsoessential.Oursocietyisbuilt

ontrustofcitizenshipandinformation.Ifwecannot

easilydeterminewhetheranimageisAIgenerated,

ourtrustofanyinformationwillerode.Inthiscase,we

needtopayspecialattentiontovulnerablepopulations

thatmaybeparticularlysusceptibletoadversarialuses

ofthistechnology.

Theprogressinamachine’scapabilitytogenerate

contentisveryexciting,asisthepotentialtoexplore

AI’sabilitytoseewhathumansarenotable.But

weneedtobeattentivetothewaysinwhichthese

capabilitieswilldisruptoureverydaylives,our

communities,andourroleasworldcitizens.

6

ThePotentialsofSyntheticPatients

GenerativeAI:Perspectives

fromStanfordHAI

RussAltman,KennethFongProfessorintheSchoolofEngineering;ProfessorofBioengineering,ofGenetics,ofMedicine,andofBiomedicalDataScience;AssociateDirectorof

StanfordHAI

Itisoftendifficulttogetlargenumbersofpatientsinclinicaltrialsanditiscrucialtohavearealisticgroupofpatientswhodonotreceiveatherapyinordertocompareoutcomeswiththosewhodo.ThisisoneareawithinbiomedicalresearchwheregenerativeAIoffersgreatopportunities.GenerativeAIcouldmakeclinicaltrialsmoreefficientbycreating“synthetic”controlpatients(i.e.,fakepatients)usingdatafromrealpatientsandtheirunderlyingattributes(tobecomparedwiththepatientswhoreceivethenewtherapy).Itcouldevengeneratesyntheticoutcomestodescribewhathappenstothesepatientsiftheyareuntreated.Biomedicalresearcherscouldthenusetheoutcomesofrealpatientsexposedtoanewdrugwiththesyntheticstatisticaloutcomesforthesyntheticpatients.Thiscouldmaketrialspotentiallysmaller,faster,andlessexpensive,andthusleadtofasterprogressindeliveringnewdrugsanddiagnosticstocliniciansandtheirpatients.

Inthepast,wehaveused“historicalcontrols”whicharepatientswhodidnothavethebenefitofthenewdrugordiagnostic–andcomparedtheiroutcomestopatientswhoreceivedthenewdrugordiagnostic.Syntheticpatientscouldmatchtherealpatientsmorerealistically;theyarecreatedusingknowledgeofcurrentmedications,diagnostictools,andstandardsofpracticethatwerelikelydifferentinthehistoricalsituation.

Inthesettingofmedicaleducation,generativeAIcouldallowustocreatepatientsthatareveryrealisticandcouldallowmedicalstudentstolearnhowtodetect

diseases.Theabilityforgenerativemodelstocreatemanyvariationsonathemecouldallowstudentstoseemultiplecasesofthesamediseaseandlearnthewaysinwhichthesepatientscanvary.Thiscouldgivethemmoreexperienceinseeingadiseaseandprovideanearlyunlimitedsetofcasesforthemtopracticeiftheyfindthatcertaindiseasesaremorechallengingforthemtorecognizeanddiagnose.Thesesamegenerativemodelscouldalsointeractwiththestudentsandgivethempracticeelicitingsignsandsymptomsthroughconversationalinteraction.

Thiscouldmaketrials

potentiallysmaller,faster,and

lessexpensive,andthuslead

tofasterprogressindelivering

newdrugsanddiagnostics.

Withopportunitycomesworry.Ifsyntheticpatientsaregeneratedfromdatathatdoesnotreflectthepopulationofpatientsreceivingthedrug,thepatientsmaybebiased.Moreworrisome,however,isthateventherealpatientsreceivingthedrugwillnotreflectthefullpopulation,andsosyntheticcontrolscouldjustimprovetheuseofthedrugsforasubsetofpatientsandnotall–leadingtoinequity.

Whilegenerativetechnologiescanbeveryusefulin

acceleratingscientificdiscoveryandprogress,care

mustbetakeninselectingthedatausedtogenerate

patientsandthemodelsmustbeexaminedvery

carefullyforbiasesthatmayleadtodisparateimpact.

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GenerativeAI:PerspectivesfromStanfordHAI

PatientCaretoBilling

UpendingHealthcare,from

CurtLanglotz,ProfessorofRadiology,ofBiomedicalInformaticsResearch,and

ofBiomedicalDataScience;DirectoroftheCenterforArtificialIntelligencein

MedicineandImaging(AIMI);AssociateDirectorofStanfordHAI

Oneofthebenefitsofourhealthcaresystemisthatpatientscanseeavarietyofspecialistphysicianswhoareexpertsinspecificmedicaldisciplines.Thedownsideofoursystemisthatthesespecialistsoftenaren’tacquaintedwiththepatientstheyareseeing.Imagineaworldinwhichaspecialistyouareseeingforthefirsttimehasalreadyreadasuccinctsummaryofyourhealthcareneeds,createdbygenerativeAI.Duringthepatientvisit,achatbotbasedonafoundationmodelcouldserveasthephysician’sassistanttosupportmoreaccuratediagnosisandtailoredtherapyselection.Agenerativemodelcoulddraftaclinicnoteinrealtimebasedonthephysician-patientinteraction,leavingmoretimeforface-to-facediscussion.Inthebackoffice,generativemodelscouldoptimizeclinicschedulingorsimplifygenerationofmedicalcodesforbilling,diseasesurveillance,andautomatedfollow-upreminders.Thesenewcapabilitiescouldimprovetheaccuracyandefficiencyofpatientcarewhileincreasingpatientengagementandadherencetotherapy.

Recentfederallegislationgivespatientstherighttoaccesstheirentiremedicalrecordindigitalform.Asaresult,patientsareincreasinglyencounteringcomplexclinicaldocumentsthatcontainobscuremedicalterms.Whenapatientreturnshomefromaclinicvisit,afoundationmodelcouldgeneratetailoredpatienteducationmaterialsandexplaintheircareplanattheappropriatereadinglevel.

Machinelearningmodelsinmedicinearecritically

dependentonlargemedicaldatasetsthatcontain

examplesofdisease.

Wehaveshown

howdiffusion

models,atypeoffoundationmodel,canbemodified

tocreaterealisticclinicalimagesfromtextprompts.

Ourresultsdemonstratethatsynthetictrainingdata

producedbythesemodelscanaugmentrealtraining

datatoincreasediagnosticaccuracy.Thisformof

syntheticdatacouldhelpsolvemachinelearning

problemsforwhichtrainingdataisscarce,suchasthe

detectionandtreatmentofuncommondiseases.

Duringthepatientvisit,a

chatbot…couldserveasthe

physician’sassistanttosupport

moreaccuratediagnosisand

tailoredtherapyselection.

Finally,generativeAI’swell-reportedchallenges

withfactualcorrectnessareparticularlyproblematicinmedicine,whereinaccuraciescancauseseriousharm.Recentproblemsinmedicineincludeincorrectdifferentialdiagnosisandinvalidscientificcitations.Weareworkingto

improvethefactualcorrectness

ofmedicalexplanationsfromthesemodelssotheycanachieveanaccuracythatissuitableforsafeclinicaluse.

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AnAIWindowintoNature

SuryaGanguli,AssociateProfessorofAppliedPhysics;AssociateDirectorof

StanfordHAI

Scientificideasfromthestudyofnatureitself,intheformofnonequilibriumthermodynamicsandthereversaloftheflowoftime,leadtothecreationatStanfordofthefirst

diffusionmodel

,akeykerneloftechnologythatformsthebasisofmanysuccessfulAIgenerativemodelstoday.Now,inavirtuouscycle,AIgenerativemodelsarewellpoisedtodeliverconsiderableinsightsintonatureitself,acrossbiological,physical,andmentalrealms,withbroadimplicationsforsolvingkeysocietalproblems.

Forexample,

generativemodelsofproteins

canallowustoefficientlyexplorethespaceofcomplexthree-dimensionalproteinstructures,therebyaidinginthesearchforproteinswithnovelandusefulfunctions,includingnewefficaciousmedicines.Generative

AIisstartingtobeexploredinthe

quantumrealm

,enablingustoefficientlymodelstronglycorrelatedstatesofelectrons,withthepotentialofadvancingourunderstandingof

materialsscience

and

quantum

chemistry

.Theseadvancescouldinturnleadtothecreationofnewmaterialsandcatalyststhatcouldplayaroleinefficientenergycaptureandstorage.Simplegenerativemodeling,intertwinedwithclassicalnumericalsolvers,hasalsomadekeyadvancesinaccurateandfastlargescale

fluid

mechanicalsimulations

,whichwhenscaledup,couldaidinclimatemodelingandweatherforecasting,therebycontributingtoadeeperunderstandingofourchangingclimateanditsramifications.

GenerativeAI:PerspectivesfromStanfordHAI

Inabeautifulrecursion,thegenerativeAImodelsthat

wehavecreatedcanalsoactasscientificwindows,

notonlyintothephysicalworldbutalsointoour

own

minds

.Forthefirsttime,wehaveAIsystems

thatcanmodelhigh-levelcognitivephenomena

likenaturallanguageandimageunderstanding.ManyneuroscientistsandcognitivescientistshavecomparedtheneuralrepresentationsofbothdeepnetworksandAIgenerativemodelstoneurobiologicalrepresentationsinhumansandanimals,oftenfindingstrikingsimilaritiesacrossmanybrainareas.Examplesincludethe

retina

,the

ventralvisualstream

,

motor

cortex

,

entorhinalcortex

fornavigation,

cortical

language

areas,andneuralgeometriesunderlying

few

shotconceptlearning

.Theoftensimilarstructureofartificialandbiologicalsolutionstogenerativetaskssuggeststheremaybesomecommonprinciplesgoverninghowintelligentsystems,whetherbiologicalorartificial,modelandgeneratecomplexdata.

AIgenerativemodelsarewell

poisedtodeliverconsiderable

insightsintonatureitself,

acrossbiological,physical,

andmentalrealms,with

broadimplicationsforsolving

keysocietalproblems.

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AnAIWindowintoNature(cont，d)

GenerativeAI:Perspectives

fromStanfordHAI

AnexceedinglyinterestingandprofoundquestionarisesintheforthcomingageofscientificcollaborationbetweenhumansandAIsystemsastheyworktogetherinalooptoanalyzeourcomplexbiological,physical,andmentalworlds:WhatdoesitmeanforahumantoderiveaninterpretableunderstandingofacomplexsystemwhenanAIprovidesasubstantialpartofthatunderstandingthroughpredictivemodels?Issuesregarding

explainableAI

willlikelyrisetotheforewhenafundamentallyhumanscientificendeavor,namelyunderstandingourworld,ispartiallyachievedthroughtheuseofAI.HumanscientistswillnotbecontentwithuninterpretableAI-generatedpredictionsalone.Theywilldesirehumaninterpretableunderstanding,inaddition.

Finally,todreamevenbigger,whiletoday’sgenerativeAIhasaccesstoimmenseglobalscaletrainingdataspanningimages,text,andvideofromtheinternet,itdoesnothavedirectaccesstoourownthoughts,intheformofneuralactivitypatterns.However,thisneednotalwaysbethecase,givenremarkablenewneuroscientificcapacitiestorecordmanyneuronsfromthebrainsofanimalswhiletheyviewimages,aswellastoperformMEG,EEG,andfMRIfromhumansastheyexperiencetheworldthroughrichmultimodalsensoryexperiences.Suchcombinedneuralandreal-worlddatacouldthenpotentiallybeusedtotrainnextgenerationmultimodalfoundationmodelsthatnotonlyunderstandthephysicalworldbutalsounderstandthedirectimpactthephysicalworldhasonourmentalworld,intermsofelicitedneuralactivitypatterns.Whatmightsuchhybridbiological-artificialintelligencesteachusaboutourselves?

Overall,thefutureofgenerativeAIasawindowinto

nature,andtheuseofthiswindowtosolvesocietal

problems,isfullofpromise.Wecertainlydolivein

interestingtimes.

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TheNewToolsofDailyLife

JamesLanday,AnandRajaramanandVenkyHarinarayanProfessorintheSchoolofEngineeringandProfessorofComputerScience;ViceDirectorofStanfordHAI

GenerativeAI:Perspectives

fromStanfordHAI

Asweallknow,AIistakingtheworldbystorm.Wewillbegintoseemanynewtoolsthataugmentourabilitiesinprofessionalandpersonalactivitiesandworkflows.Imagineasmarttutorthatisalwayspatientandunderstandsthelevelofknowledgethestudenthasatanypointintimeonanysubject.Thesetutorswillnotreplaceteachers,butinsteadwillaugmentthestudentlearningexperience–givingstudentsamorepersonalizedinteraction,focusinginareaswheretheymightbeweaker.

Indesign,pictureatoolthatassistsaprofessionaldesignerbyriffingofftheirinitialdesignideasandhelpingthemexploremoreideasorfillindetailsontheirinitialideas.GenerativeAIwillalsounleashlanguage-basedinterfaces,whetherwrittenorspoken,asamorecommonwayofinteractingwithoureverydaycomputingsystems,especiallywhenonthegoorwhenoureyesandhandsarebusy.ImagineanAlexa,Siri,orGoogleAssistantthatcanactuallyunderstandwhatyouaretryingtodoratherthanjustansweringsimplequeriesabouttheweatherormusic.

WhilegenerativeAIcreatesmanyexcitingopportunities,weknowfrompastAIdeploymentstherearerisks.In2016,anAI-basedsoftwaretoolusedacrossthecountrytopredictifacriminaldefendantwaslikelytoreoffendinthefuturewasshowntobebiasedagainstBlackAmericans.Weneedtoensurewearedesigningthesetoolstogetthemostpositiveoutcomes.Todothis,weneedtodeeplydesignand

analyzethesesystemsattheuser,thecommunity,andsocietallevels.Attheuserlevel,weneedtocreatenewdesignsthataugmentpeoplebyaccountingfortheirexistingworkflowsandcognitiveabilities.Butwecan’tjustdesignfortheuser.Weneedtoconsiderthecommunitythatthesystemimpacts:thefamilies,theinfrastructure,andthelocaleconomy.But,eventhatisnotenough,weneedtoanalyzetheimpactstosocietyatlarge.Weneedtobeabletoforecastwhathappensifthesystembecomesubiquitousandfromthestartdesignmitigationsforpossiblenegativeimpacts.

Changesthatareunderpinned

bygenerativeAIareonlynow

startingtobeimaginedby

designersandtechnologists.

Ouruserinterfacetocomputinghasbeenfairlystatic

overthelast30years.Inthenext5–10years,we

willseearevolutioninhuman-computerinteraction.

ChangesthatareunderpinnedbygenerativeAIare

onlynowstartingtobeimaginedbydesignersand

technologists.Nowisthetimetoensurethatweare

criticallythinkingabouttheuser,thecommunity,and

thesocietalimpacts.

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PoetryWillNotOptimize:CreativityintheAgeofAI

MicheleElam,WilliamRobertsonCoeProfessorintheSchoolofHumanitiesandSciencesandProfessorofEnglish;AssociateDirectorofStanfordHAI

In2018,theprofessionalartworldwasupendedwhentherenownedChristie’sauctionhouse

soldanAI-

augmentedwork

,“PortraitofEdmondBelamy,”forthewildlyunexpectedsumof$435,000.Thatsale,whichcamewiththetacitimprimaturoftheestablishedartcommunity,generatedmuchgnashingofteethandhand-wringingintheartssectoroverwhatartificialintelligencemeansforthecreativeindustry.

Sincethen,thegeniehaslongfleditslamp:GenerativeAIhasenabledvisualartofeveryknowngenreaswellas

AI-augmentedpoetry

,fiction,

filmscripts

,

music

and

musicals

,

symphonies

,AI-curatedarthistories,andmuchmore.

ThefurorovertheChristie’ssalemaynowseemquaint–itoccurredbeforeDALL-E,LensaAI,ChatGPT,Bing,tonamejustafew–butitheraldedmanyoftoday’sincreasinglyferociousdebatesoverthenatureofcreativityandthefutureofworkforthecreativeindustry.Itanticipatedthecurrenthornet’snestofethical,political,andaestheticconcernsthatgenerativeAIposesforthearts.

Someoftheseconcernshavebeenproductive:GenerativeAIhasencouragedmanyofthosewhoselivelihoods,andinmanycasestheiridentities,dependontheirartisticproductionstoconsideranew–andinnewways–perennialquestionsaboutfoundationalaestheticnormsandvalue:Whatdo

GenerativeAI:PerspectivesfromStanfordHAI

weidentifyas“art”?Whatcountsas“good”art?Isartistrydefinedbyhumanagencyorautomation?Justwhoorwhatcanmake“art”?Andwhodecides?GenerativeAIraisesimportant,thornyquestionsaboutauthenticity,economicvaluation,provenance,creatorcompensation,andcopyright.(TheGettyImageslawsuitagainstStableDiffusionisjustthetipofaniceberg.)Italso,arguably,normalizesextractiveandexploitativeapproachestocreatorsandtheirwork;amplifiesbiasesofeverykind;exacerbatesalreadyurgenteducationalandnationalsecurityconcernsarounddeepfakesandplagiarism,especiallyintheabsenceofcongressionalregulation.

Shouldtheprinciplesof

efficiency,speed,and

so-calledblessingsofscale

applysounequivocallyto

creativeprocesses?Afterall,

poetrydoesnotoptimize.

Perhapsthemostpressingconcern,intermsofnationalsecurity,isthatgenerativeAImighttakeadvantageofthefactthattheartshavealwaysshaped–forgoodorill–thecivicimagination,thatstories,films,plays,imagesshapeourperceptionofourselves,ofourphysicalandsocialrealities.OneofthemostfamousdisagreementsbetweenPlatoandhisstudentAristotlewasoverthepotentiallydangerouspowerof

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PoetryWillNotOptimize:CreativityintheAgeofAI(contd)

GenerativeAI:Perspectives

fromStanfordHAI

poesytoinfluencebeliefsandworldviews.Thispoweriswhyfascistregimesfirstdoawaywiththeartistsandintellectuals:becausetheyholdswayoverourmindsandthusouractions.

SomeclaimthatgenerativeAIisdemocratizingaccesstocreativeexpressiontothosetraditionallybarredfromitbylackofstatusorwealth.Butdoclaimsto“democratization”and“access”function,ineffect,asindustrycoverfor

rushingacommercialapplication

“intothewild”

(i.e.,tothepublic)withoutthetime-intensiveworkofensuringethicalguardrails?

IsAIsimplyaneutralifpowerfulassistivetoolforthearts–akintopen,paintbrush,orphotography?Isit“

blitzscaling

”creativity,orinEmadMostaque’s

choice

description

,relievingour“creativelyconstipated”worldwithAItechnologiesthatcanhaveusall