Linux基金会2026生成式AI时代开源软件开发研究报告项目社区的机遇与挑战

□

THE

RedHat

Research

LINUX

FOUNDATION

DpenSSF

DLNEUPE58O月PFOJSEAJV

:FUTUREWEI

□LFAI&DATA

Technologies

NavigatingOpen

SourceSoftware

DevelopmentintheGenerativeAIEra

ChallengesandOpportunitiesforProjectCommunities

October2026

SamBoysel,TheLinuxFoundationAnniLai,GenerativeAICommons

ForewordbyBrianProffitt,RedHat

NavigatingOpenSourceSoftwareDevelopmentintheGenerativeAIEra

AdoptAIfor

contributiontriageHalfofallmaintainers

leverageAIforbugchecksandcodereview.But1in4donotuseitatall.

01010

00100

Filterlow-qualityPRs1in4incomingcontributionsareAIslop.Thisrateincreasesto31%forlargerprojects.

Streamline reviewcyclesLowqualitycontributions andincreasedvolume compoundtostrainmaintainers'reviewtime.

PrepareforgenAI

contributionatscale

59%ofmaintainers

(69%inlargeprojects)

seerisingcontributionvolumefromAI.

Buildcontribution

scalableverificationsystems

Policyandtoolingcanshiftreviewburdensbackto

contributors,increase

PRquality,andreduce

maintainerburnoutrisk.

Establishclear

AIgovernance

Only1in3projectshave

aformalpolicythatallowsAIcontribution.

Investinnew

contributormentorshipThemajorityofmaintainers

stateAIdemandsmore

contributorguidance,notless.

Require

pre-submissiontesting

3of5OSSdevelopers

alreadythoroughlytestAI-assistedcontributionsbeforesubmitting.

Standardize

AIcontributionattribution

Currently,only3in10

alwaysdiscloseAIassistanceincontributionsand

2in10neverdo.

AddressAI

governancerisksfirstWhilecurrentbarriersare

technical,improvingmodelprovenance,trainingethics,anddataprivacyaremoreimportanttoAIholdouts.

ReinvestAIgains backintoOSS GenerativeAIletscontributorsspendmoretimeaddressingtechnical

debt,developingnewfeatures,andupskilling.

CaptureAIefficiencyinOSSdevelopmentHarnessupto50%time

savingsacrosscoding,reviewing,andissue

reporting.Maintainersbenefitfromefficientprojectdiscourse.

Copyright◎2026TheLinuxFoundation|October2026.ThisreportislicensedundertheCreativeCommonsAttribution-NoDerivatives4.0InternationalPublicLicense.Pleasecitethisresearchreportwhenusingtheinfographics.Seecitationguidanceonthereport'sbackpage.

Contents

Foreword 4

Executivesummary 6

Introduction 7

TheimpactofgenAIonprojectandmaintainers 8

Increasedreviewtimesandriskofmaintainer

burnoutgreatestinlargeprojects 8

AIslopnowapproachesoneinfourPRs 9

Contributionvolumekeepsgrowingfastestatscale 11

MaintainersuseAItohelpwithAI 11

MostprojectsstilllackanAIcontributionpolicy 12

Verificationstillreliesontrustratherthantooling 13

AIlowersbarrierstoentrybutcanerodecommunitytrust 14

HowgenAIisusedinOSSdevelopment 16

GenerativeAIreducescontributionbarriers

butprojectguardrailsprovideimportantmoderation 16

AItoolshavebecomestandardbutmodel

provenanceremainstopofmind 18

MostcontributorsreviewAIcodeclosely

yetattributeitinconsistently 20

Non-adoptersseetrustproblemsasfixable,

technicalproblemsasinherent 22

ProductivityimpactsofgenAI 23

GenerativeAImakesOSSdevelopmentfasteracrosstheboard 23

Timesavingsshrinkastaskcomplexityrises 25

Savedtimeflowsintotechnicaldebtandnewfeatures 26

Conclusion 27

Methodology 29

Surveydemographics 30

OSSdevelopment 30

GenerativeAIexperience 34

Maintainerdemographics 35

Abouttheauthors 36

Acknowledgments 36

Foreword

Overthelastthreedecades,Ihavewatchedopensourceprojectsandcommunitiesabsorbonedisruption

afteranother:theriseoftheweb,thearrivalofthemobilephoneandthecommensurateriseofbigdataandcloud-nativecomputing.Inallofthesetechnologicalwaves,communitieshavemanagedtoadaptinwaysthathavemadethemstrongerandmoreefficient.GenerativeAlisthenewestofthesewaves,anditmayverywellbethemostconsequentialyet.Whatmakesitdifferentiswhereitlands.Opensourcehasalwaysdependedasmuchontrust,collaboration,andsharedlaborasitdoesonthecode.SowhenatechnologylikeAlbeginsreshapinghowcontributionsarewritten,submitted,andvetted,itlandsrightintheheartofhowopensourcecommunitiesfunction.

ForRedHat,ourconvictionissimple:thefutureofAlshouldbeopen.Itshouldbebuiltintheopen,governedtransparently,andshapedbycommunities,ratherthandictatedbyasinglevendor.AnAlecosystemthatisvendor-neutralandcommunity-drivenistheonlydurablepathtomodelsandtoolingthatpeoplecaninspect,trust,andimprove.

Muchofthediscussiontodatehasbeenanecdotal:endlesstalesof"Alslop,"overwhelmedmaintainers,and

erodingtrust.WhathasbeenmissingfromtheconversationaboutAlandopensourceisrigorousdata.ThisSurveyonGenerativeAlandOpenSourceSoftwareDevelopmentsurveyof234contributorsandmaintainersevolves

thoseimpressionsintomeasurement,anditisexactlythekindofempiricalworkopensourcecommunitiesneedtonavigatewhat'scomingnext.

Twoofthissurvey'sfindingsdeservespecialattentionbecausetheydon'tfallintoeasynarratives.Thefirstis

thatgenerativeAldoesnotaffectallprojectsequally.Largeandsmallprojectsareaffectedinfundamentally

differentways.Forlargerprojects,maintainerburnoutdisplacescodequalityastheprimaryconcern,becomingthetopissueforprojectswithmorethan50contributors.Thelargestprojectsreportthelongestreviewtimes,thehighestshareoflow-quality"Alslop"contributions,andthefastest-growingcontributionvolume.Scale,inotherwords,amplifiestheburdenratherthandisbursingitacrossmorehands.Themostvisible,criticalprojectsinourecosystemareabsorbingthebruntofthisgenerativeAlwave,andtheyareamongtheoneswecannotaffordtoseeburnout.

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAERA|4

Thesecondinterestingfindingispotentiallyanotherpintopopthehypeballoon:theproductivitydividendofgenerativeAldropsastasksgrowmorecomplex.Thesurveyshowsdramatictimesavingsonwell-defined,

task-orientedworklikecodeauthoring.Butthosegainsdecreasesteadilyastheworkgetsintocoordination,judgementandopen-endeddiscussion.Onthehardesttasks,asignificantshareofdevelopersreportneedingmoretimethanbeforewhenusingAl,notless.

Thisreallyshouldn'tcomeasasurpriseforanyonewhounderstandshowAltoolswork.Alisagreatacceleratoroftheroutine,butthecritical-thought,dificultworkatthecoreofanyprojectstillreliesonhumanexpertise,andthedatashowsit.Thedatashowsthatwhentimeissaved,i'sbeingreinvestedintoprojectsbypayingdowntechnicaldebt,buildingnewfeatures,andonboardingnewcontributors.

Together,theseandtheotherfindingsofthissurveypointtoaconclusionthatmakesalotofsense:thatthe

communitiesmanagingthisincominggenerativeAlwaveareneitheroutrightbanningorwholeheartedly

adoptingAI.Communitymembersaredoingtheharder,morevaluableworkofbuildingthepolicy,verification,

andmentorshipinfrastructurethatletsthebenefitsofAlberealizedwithoutlosingthemostimportantpartofanopensourcecommunity:trustandquality.

MythanksgotoSamBoyselandAnniLaifortheircarefulwork,toHilaryCarterandherLinuxFoundation

Researchteamforthissurvey'srigor,andtoeveryparticipantwhosharedtheirexperience.Thepicturethatemergesfromthissurveyisneithertheutopiaortheapocalypsewehearbandiedaboutintheever-polarizedmedia,but,rather,somethingmoreuseful:ameasuredlookatwheretheopensourcecommunityand

generativeAlactuallystands.Ilookforwardtothediscussionsthatthisreportwillfoster.

BrianProffitt

SeniorPrincipalCommunityArchitect-StrategicInsights,RedHatOpenSourceandAlProgramOffice

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAlERA|5

Executivesummary

GenerativeAI(genAI)isalreadyhavingaprofoundimpactonopensource

software(OSS)development,sparkinganexplosionofAI-assistedcontributionsthatraisesurgentconcernsaboutcodevolume,quality,andtheincreasing

burdenontime-constrainedmaintainers.Despitetheseproblematictrends,

therearepotentialupsidesincludingincreasedproductivityandbringingnew

contributorsintotheecosystem.Toproviderobustempiricalevidencetothe

evolvingdiscussionaboutgenAIandOSS,wedeveloped,fielded,andanalyzedasurveyof234OSScontributorsandmaintainers.Thisresearchexplores

exactlyhowgenAIisbeingdeployedinOSSworkflows,howitalterscontributiondynamics,andhowprojectleadersarenavigatingthecomplexintersectionof

newopportunitiesandemergingchallenges.

OurfindingsindicatethattheimpactofgenerativeAIonprojectsandworkflowsmostoftendependsonprojectscale.Largerprojectswithcoordinatedmaintainerteamscurrentlybeartheheaviesttotaladministrativeburden.Theseteamsfacesurgesincontributionvolume,withlargeprojectsreportingthatupto31%of

incomingcontributionsarelowquality“AIslop.”Consequently,64%ofmaintainersontheseprojectsreportextendedreviewperiodsandciteburnoutastheir

primaryconcern.WhileprojectleadersgenerallyagreethatAIeffectivelylowersthebarriertocontribution,thisaccessibilitycomesatthecostofdecreased

communitytrust,highermentorshipdemandsfornewcontributors,andahighlyfragmentedlandscapeforAIcontributionpoliciesandverificationmethods.

Despitethesefrictionpoints,generativeAIremainsapowerfulproductivityacceleratoracrosstheopensourceecosystem.ContributorsandmaintainersreportthatthesetoolsreducethetimerequiredforOSSdevelopment,

withaveragetimesavingsrangingfrom19%to52%dependingonthetask.

Maintainersspecificallybenefitfromhighlyefficienttechnicaldiscussionsand

proposalreviews,savingbetween25%and40%oftheirtime—gainsthat66%ofrespondentsreinvestdirectlyintoaddressingtechnicaldebt.Furthermore,

genAIemboldensdeveloperstoexploreunfamiliartechnologiesandcontributetonewprojects.Crucially,wefindstrongevidenceofconscientiousadoption:61%ofcontributorsconductdetailed,line-by-linereviewsandfullfunctionaltestingofAI-generatedcodebeforesubmission,and80%emphasizetheimportanceofunderstandingtheunderlyingsourcemodelandtrainingdatalineage.

ToresolvethecoretensionssurroundingtheuseofgenAIinOSSdevelopment,projectsmustmovefromreactivemanagementtointentionalcontribution

policyandworkflowdesign.Successfulcommunitiesareestablishingclear,

transparentguidelinesthat,insteadofforbiddinggenAIornaivelyaccepting

allgenAIresults,passthereviewburdenbacktocontributorsbymandating

responsiblegenAIusage,standardizinggenAIattribution,andexplicitlydefiningexpectationsforsubmittedcode.Simultaneously,maintainersshouldconsiderusingAIthemselvestocombatgrowingworkloads,fightingfirewithfireto

reclaimvaluablebandwidth.Crucially,projectleadersmustrecognizethatwhileAIlowersentrybarriersandacceleratestechnologyadoption,itcannotreplacehumanknowledgeandmentorship;sustaininglong-termcommunityhealth

requirescontinuedinvestmentinhands-onguidanceandcontributionnormsthatwelcomenewcomerswithoutsacrificingqualityorerodingtrust.

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAIERA|6

Introduction

ThetransformativeimpactthatgenAlhasonsoftwaredevelopmentishardtooverstate.Byreducingthe

humancapitalandtimetogeneratefunctionalcode,thesenewtoolscansignificantlyinfluenceworkflowsfornoviceandveterandevelopers.Buttheseforcesnowcomeagainstlongstandingnormsandpracticesinopensourcesoftware(OSS)development,wherethesocialaspectofcollaborationoftenmattersatleastasmuchastechnicalskills.ReportsofAl-assistedcontributionsfloodingOSSprojectshavesparkedconcernsaboutcodequality,maintainers'workload,andtheerosionoftrustwithincontributorcommunities.Projectcommunitiesaresearchingforwaystocontinuecreatinghigh-qualityOSS,andmostacknowledgethatAl-assisted

developmentisheretostay.

WestartbyillustratingtheimpactofgenAlusingabroadsampleofOSSprojectsandmaintainer

perspectives,ratherthanrelyingsolelyonanecdotalevidence.It'simportanttofirstestablishtheextenttowhichgenAlchangescontributionvolumeandquality,howthisvariesacrossdifferentprojectscales,andwhatthismeansformaintainers'workload.ThestudyalsoexploreshowmaintainerssetAlcontribution

policies,verifyAl-assistedcontributions,anduseAltoassistwithcontributionreview.

Inthenextphaseofthestudy,weinvestigatehowOSSdevelopersareusinggenAltoolsandhowthesetoolshaveinfluencedcontributionbehavior.ThesurveyasksrespondentswhatspecificOSSdevelopmenttaskstheyusegenAlfor,whatkindofprojectstheycontributeto,andhowtheyverifyandattributeAl-assisted

contributions.WealsoexplorewhysomedeveloperschoosenottousegenAl,andwhatfactorsmightpersuadethemtoadoptitinthefuture.

Finally,weexaminetheproductivityimpactsofgenAlonOSSdevelopment.ThesurveyasksrespondentstoestimatehowmuchtimetheysaveonvarioustaskswhenusinggenAl,howtheseeffectsvaryacrosstasksandcontributorroles,andhowtheyreinvestthatsavedtime.ThissectionprovidesinsightsintohowgenAlisreshapingtheOSSdevelopmentlandscape,andwhatthismeansformaintainers,contributors,andthebroaderOSScommunity.

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAERA|7

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAIERA|8

TheimpactofgenAIonprojectandmaintainers

MaintainerssitatthereceivingendofthegenAIcontributionwave,andtheir

experienceofitisshapedalmostentirelybyprojectscale.Manylargeprojectsareundertremendousstrainduetoamassiveinfluxoflow-qualityAI-generatedcontributions.Bothelevatedvolumeandincreasedverificationburdens

compoundtoerodemaintainers’precioustimeandincreasetheriskofburnout.Inthissection,wepresentsurveyevidenceconfirmingthetollgenAIhason

maintainerworkloadandcontributionquality.Welinktheseeffectstorisingcontributionvolume,projectAIcontributionpolicy,andtheverificationandreviewmethodsmaintainersuseforAI-assistedcontributions.

Increasedreviewtimesandriskofmaintainerburnoutgreatest

inlargeprojects

TogetasenseoftheoverallimpactofgenAIonOSSmaintainers,webeginbyidentifyingthetopconcernsAI-assistedcontributionsraiseformaintainers.Wetakecaretosegmenttheresultsbyprojectsize,sincescaleisamajorfactorinhowmaintainersexperiencetheAIcontributionwave.

Maintainerscitedegradedcontributionqualityastheoverarchingproblem

withAI-assistedcontributions,butasprojectsgrowinsize

1

,thatconcernis

compoundedbyanevenmorepressingone:maintainerburnoutbecomes

thedominantissueinlargeprojects(thosewithmorethan50contributors).

Thissuggeststhatrisingcontributionvolumeistranslatingdirectlyintoreviewer

fatigueratherthanbeingabsorbedpainlessly(Table1).

Theclearestsignofstrainistime:AI-assistedcontributionsaremeasurably

lengtheningthereviewprocessforthemaintainerswhohavetoevaluatethem.Leadandco-maintainersbeartheheaviestburden,reportingthehighestratesofincreasedreviewtime(Figure1).Solomaintainersstandoutastheonlyrolewherereducedreviewtimeapproachesorexceedsthesharereportinganincrease,likelyafunctionofthesmaller,morefamiliarcontributorbasethey

typicallymanage.Scalecompoundstheeffect:largeprojectsseeamarkedly

higherincreased-reviewshare(64%)thansmall(46%)ormedium(55%)projects,confirmingthatthelargest,mostvisibleprojectsareabsorbingthebruntoftheaddedworkload.

TABLE1:MAINTAINERBURNOUTBECOMESTHETOPCONCERNFORLARGERPROJECTS

CONCERNRANK

SMALLPROJECTS

MEDIUMPROJECTS

LARGEPROJECTS

1st

Contributionquality[51%]

Contributionquality[50%]

Maintainerburnout[63%]

2nd

Securityconcerns[40%]

Increasedtechnicaldebt[35%]

Contributionquality[60%]

3rd

Contributionvolume[35%]

Maintainerburnout[35%]

Contributionvolume[43%]

Source:SurveyonGenerativeAIandOpenSourceSoftwareDevelopment.Q36xQ29.Numberofrespondents=133

1Throughoutthisreport,weusethefollowingdefinitionsforprojectsize:Smallprojects=fewerthan10contributors.

Mediumprojects=11to50contributors.Largeprojects=morethan50contributors.

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAERA|9

FIGURE1

AI-assistedcontributionfarmorelikelytoincreasereviewtimesforlargeprojectsandleadmaintainers

Source:SurveyonGenerativeAlandOpenSourceSoftwareDevelopment.

Q39xQ28×Q29.Numberofrespondents=174.

17%

Allmaintainers

64%

Largeprojects

46%

Small

21%

projects

55%

projects

Medium

20%

Co-maintainers

Solomaintainers

32%

23%

AIslopnowapproachesoneinfourPRs

Behindthatrisingreviewburdenliesaquality

problem.“Alslop”arelowqualityAl-generated

contributionsthatareunlikelytobeworththe

reviewtimetheydemand.Largeprojectsarefocalpointsforincreasedcontributionenergy,andthisiswheremaintainerconcernsaremostelevated.

Onaverage,25%ofincomingPRsareestimated

tobeAI-generatedlow-qualitycontributions

(Figure2).Thisburdenagainscaleswithsize:largeprojectsreportasubstantiallyhighermeanslop

sharethansmallormediumprojects(31%vs.23%and20%),confirmingthatscaleamplifiesexposuretolow-effortAlsubmissionsratherthandiluting

itacrossalargerreviewerpool.Rolealsomatters

independentofprojectsize.Co-maintainersreportthehighestmeanslopshareamongroles(29%),

nearly6percentagepointsaboveleadandsolo

maintainers,possiblyreflectingbroadercontributor

networkswithlessdirectoversightthanasinglelead

maintainercantypicallyprovide.

Leadmaintainers

29%

PercentageofprojectormaintainersegmentbyimpactofAI-assistedcontributionsonaveragereviewtime

Increasedreviewtime■Reducedreviewtime

61%

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAIERA|10

FIGURE2

1in4incomingPRsisAIslop.Largeprojectswith

co-maintainerteamsreceivethehighestpercentage

Source:SurveyonGenerativeAlandOpenSourceSoftwareDevelopment.Q38×Q28×Q29.Numberof

respondents=111.Thetoppanelshowsthesampleaverageforallrespondents.Themiddlepanelsegmentsmaintainersbythesizeoftheirproject.Thebottompanelsegmentsrespondentsbythetypeofmaintainer.

Allmaintainers25%

Largeprojects

23%

Smallprojects

20%

Mediumprojects

Co-maintainers

24%

Solomaintainers

23%

Leadmaintainers

AverageestimatedpercentageofincomingPRs

thatarelow-qualityand/orAI-generated

NotallOSSprojectsreceivesloporcontinuetoreceiveslop.CurlprojectleadDanielStenbergreportedin2025thatthecurlprojectwas

beingoverwhelmedbyAlslopinvulnerabilityreports²,yetbyApril2026hereportedthat

thecurlprojecthad“stoppedgettingAlslopsecurityreports”andwereinsteadgetting“anever-increasingamountofreallygoodsecurityreports,almostalldonewiththehelpofAI"3.ThissuggeststhatasAlmodelsgetbetter,andasprojectspushbackagainstAlslop,slopcanbereducedovertime.However,projectsmustmakeclearthatAlslopisnotacceptable,andthatAl-generatedwork(suchasvulnerabilityreports)mustbecarefullyvalidatedbefore

beingsubmittedtoprojects.

2DanielStenberg,"DeathbyaThousandSlops,"DanielStenberg'sBlog,July14,2025,

https://daniel.haxx.

se/blog/2025/07/14/death-by-a-thousand-slops/.

3DanielStenberg

,Linkedlnpost,April2,2026.

/posts/danielstenberg_

hackerone-share-7446667043380076545-RX9b/

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAIERA|11

Contributionvolumekeepsgrowingfastestatscale

Underlyingboththeworkloadburdenandthequalityconcernsjustdescribedisabasicshiftinscale:thesheeramountofincoming

contributions.Theincreasedvolumeoflow-qualitycontributions

compoundstheproblemforalreadyoverworkedmaintainers.

Mostprojectshavewitnessedagrowthincontributionvolumesince

theriseofgenAl:59%ofmaintainersreportanincreaseandonly4%a

decrease(Figure3).Thisisevidenceagainstoutrightcontributioncollapse,

butalsotherawfuelbehindtheworkloadandqualitypressuresdescribed

above,sinceloweringthecostofparticipationdrawsinmoresubmissionswithoutnecessarilyimprovingthem.Thatgrowthisnotevenlydistributed,however.Itscaleswithprojectsize:69%oflarge(51+contributor)projectsreportanincrease,comparedwith57%ofsmalland52%ofmedium

projects.Aligningwithelevatedburnoutriskinlargeprojects,higher-

visibilityprojectsareabsorbingadisproportionateshareofthenew

AI-assistedcontributiontraffic.Smalprojects(lessthan10contributors)

tellamessierstory,mirroringsolomaintainerswiththewidestvarianceofanysegment—40%reportnochangeatallalongside21%seeinggrowthofmorethan50%,asplitthatikelyreflectshowmuchasingleactive

Al-assistedcontributorcanskewthenumbersatthatscale.

MaintainersuseAItohelpwithAI

Maintainersneednotfacetheserisingchallengeswithoutassetsoftheirown.SomearefightingfirewithfirebyusingAlthemselvestoassistwithmaintenanceworkloads.Whilecertainlynotareplacementformaintainerexpertise,skilledoperatorscanleverageAltoolstomoreefficientlyreview

themountingbacklogofcontributionproposalsastheygrowinboth

volumeandcomplexity.

FIGURE3

AI-assistedcontributionvolumeincreasesmostforlargerprojects

Source:SurveyonGenerativeAlandOpenSourceSoftwareDevelopment.Q37,segmentedbyQ29(projectsize,collapsedtoSmall/Medium/Large).Numberofrespondents=111.

Largeprojects69%

Smallprojects40%57%

Mediumprojects5%一43%52%

PercentageofprojectsineachsizesegmentreportingchangesincontributionvolumeduetogenerativeAluse

NochangeIncreased

contribution

volume

Decreased

contribution

volume

MostmaintainersuseAItounderstandincomingcontributions[58%]orcheckforlogicbugs[48%],turningthesametechnologythatisdrivingup

contributionvolumeintoapartialcounterweightagainsttheaddedreview

burden.Still,23%usenoAltoolsforcontributionvettingatall(Figure4),so

ameaningfulminorityarechoosingtoabsorbthegrowingreviewloadwithentirelymanualmethods.

NAVGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAERA|12

FIGURE4

3outof4maintainersareactivelyusingAItoolstomanageAI-assistedcontributions

Source:SurveyonGenerativeAlandOpenSourceSoftwareDevelopment.Q33.Numberofrespondents=92.Totalresponses=193.

UsingLLMstoexplain/summarizecomplexlogicinproposedcontributions

48%

CheckingforlogicbugsoredgecasesviaAlchat/IDE

Automatedvulnerabilityscanning

39%

(e.g.,Snyk,GitHubCodeQL)

38%

verifythecontribution

Generatingtestcasesto

23%

NoAltoolsareusedtovetcontributions

PercentageofrespondentsthatusethismethodtovetAI-generatedcontributions

FIGURE5

Only1in3OSSprojectshaveaformalpolicyallowingAIcontribution

Source:SurveyonGenerativeAlandOpenSourceSoftwareDevelopmentQ30.Numberofrespondents=119.

35%

32%

23%

10%

Percentageofrespondentsby

AIcontributionpolicystatus

Al-assistedcontributionspermittedNoAlcontributionpolicyandnoneplanned

PlantoimplementanAlcontributionpolicy

Al-assistedcontributionsnotpermitted

MostprojectsstilllackanAIcontributionpolicy

Givenrisingvolume,reducedquality,andotherconcerns

aboutAl-assistedcontribution,anaturalquestion

iswhetherprojectshaveformalizedanyresponse.

Contributionpoliciescantakemanyformsandlevelsof

formalization,fromoutrightbanstodetailedguidelinesforresponsibleuse.Moreover,projectssimplyvaryin

termsoftheirpolicyresponsetoAl-assistedcontributions,withnosingleapproachdominatingthelandscape.

MostprojectshaveyettostandardizepolicyforgenAl

contribution.Only35%ofprojectshaveaformalpolicypermittinggenAIuse,32%havenopolicyandnoneplanned,and10%explicitlyprohibitit(Figure5).ThisimpliesthatamajorityofprojectsnavigateAl-assisted

contributionsonanadhoc,case-by-casebasis.But

momentumisshiftingtowardsformalization:23%of

projectsplantoimplementanAlcontributionpolicy

sometimeinthefuture.FormalAlusagepoliciessetclearexpectationsforcontributorsandreducesomereviewoverheadformaintainers.

Wherepoliciesdoexist,theytendtofocusonmakingAlusevisibleratherthanrestrictingitoutright.Existingpoliciesmostcommonlyaddresstransparencyand

disclosurerequirements[76%]andcontributorreviewresponsibility[76%],whilelicensingandcopyrightis

coveredinonly39%ofcases(Figure6),agapthatleavesmanyprojectsconfusedaboutissuesleastamenabletoinformal,trust-basedresolution.

NAVIGATINGOPENSOURCESOFTWAREDEVELOPMENTINTHEGENERATIVEAIERA|13

GenAIpoliciescanhelpresolvelegaluncertainty:Inmanyjurisdictions

(includingtheEUandUS),worksgeneratedentirelybyAlwithouthumancreativeinputcannotbecopyrighted.Ifit'sacopyofsomethingalreadycopyrighted,it'sstillcopyrighted.CourtcasesconfirmingthisincludeBartzv.AnthropicPBCandKadreyv.MetaPlatforms,Inc.TheLinuxFoundationhas"GuidanceRegarding

UseofGenerativeAlToolsforOpenSourceSoftwareDevelopment"4that

discussestheseissues.Thatsaid,suchcopyingisrelat