PreSuit

Detect and Prevent Law Suits Before They Are Filed

RalphC.Losey∗

PreSuit™iswhatIcallmymethodofusingartificialintelligencepowereddocumentreviewsoftware,anddataanalytics,tomonitoracorporation’semail,andotherESI,inordertopickuponearlywarningsignsofwrongfulactivity.ItisaplayoffthetermPreCrimefromtheMinorityReportmovie.Theearlydetectionofpossiblelawsuitsagainstacompanyallowslegalcounseltotakeimmediatecorrectiveactionandpreventsuitsbeforetheyarefiled.Itisthenextstepintheapplicationofbigdataanalyticstocorporatecompliance.Iamnowworkingonperfectingnewtechniquesinthisareaandhopetoofferfullydevelopedproductsandlegalservicessoon.ThisarticleprovidesbasicinformationonmyideasaboutPreSuit.

BirthofaNewLegalComplianceMethodUsingAIandBigDatatoDetectand

PreventLawSuitsBeforeTheyareFiledIannouncedthisidea,anddisclosedsomeofthebasicsofthemethods,inPreSuit:HowCorporateCounselCouldUse“SmartData”toPredictandPrevent

∗Nationale-DiscoveryCounselandshareholderofJacksonLewisP.C..AlloftheviewsexpressedhereareLosey’sownpersonalopinions,andnotnecessarilythoseofhislawfirmorclients.Loseyisalsothepublisherofe-DiscoveryTeam.com,authoroffivebooksone-discoveryandoverfiftyarticlesonpredictivecoding.

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Litigation(February9,2014).Aboutamonthlater,aJapanesevendorthatalsodoesbusinessintheU.S.,UBIC,announcedthereleaseofnewpredictivecodingtypesoftwaredesignedforthisactivity,calledEmailAuditor.Themethodsbuiltintothesoftwarearesimilartomyown.AtaboutthesametimetheRichmondJournalofLaw&TechnologypublishedanarticlebyJasonR.BaronandBennettB.Borden,whichincludesadescriptionofessentiallythesameidea.FindingtheSignalintheNoise:InformationGovernance,Analytics,andtheFutureofLegalPractice,20Rich.J.L.&Tech.7(March14,2014).Thisisobviouslyanideawhosetimehascome.Alsoseemyarticle,ShouldLawyersBeBigDataCops?whereIexploresomeoftheprivacyissuesandotherconcernsinusingBigDataanalyticstopredictillegalbehavior.OnJune18,2015,BennettBordenbecametheChiefDataScientistofhislawfirm,DrinkerBiddle.Thisisprobablythefirstsuchappointmentintheworldforalawfirm,butcertainlywillnotbethelast.Bennett’sappointmentcoincidedwithhisearningaMastersofSciencedegreeinBusinessAnalyticsfromNYU.Bennett’sfirmbiographyexplainshisnewrole:

Bennett’sground-breakingresearchintotheuseofmachine-basedlearningandunstructureddatafororganizationalinsightisnowbeingputtoworkindata-drivenearlywarningsystemsfordetectingandpreventingcorporatefraudandothermisconductatDBRclients.Asoneoftheworld’sfirstlawyer/datascientists,Bennettalsobuildsmachine-basedlearningmodelstotransformandimprovelegaloutcomesinkeycorporateeventsincludingmergersandacquisitions,informationgovernanceprogramdevelopmentandenforcement,litigationandinvestigations,andbusinessintelligence.

InJuly2015,IdiscoveredtwopatentapplicationsfiledbyretiredattorneyNelsonBrestoff,andWilliamH.Inmon,thesocalled“FatherofDataWarehousing,”totrytopatentasimilarideaintheguiseofabusinessmethod.Theirso-calledinventionuseswhatis,inmyopinion,asimplekeywordsearchapproachtoemailanalysis.SeeU.S.PatentApplicationsentitledSystemandMethodforIdentifyingPotentialLegalLiabilityandProvidingEarlyWarninginanEnterprise,20130297519and20140244524.Inmyviewtheseapplicationsdescribeanidea,notanactualpatentableinvention.Moreover,theactualmethodsdescribedfortheirearlywarningsystemofillegalactivitiesbysearchofcorporateemaildonotseemnovel.Still,thedescriptionsoftheideaspresented,whichtheycallanoutgrowthofpreventivelaw,areinteresting.Brestoffappearstobeanarticulate,earlyadvocatefortheseideas.SeeBrestoff’sshortarticleDataLawyersandPreventiveLaw(LTN,10/25/12)whereinhewrote:

DatalawyerscoulduseBigDatatoavoidlawsuitsaltogether,whichalsomeanstheycanhelptoavoidaratherlargesetofcosts:thefeespaidto

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outsidecounsel,thecostsofe-discoverywhenlitigationhappens,theregulatorypenalties,andthedamagesawards.Allofthatavoided.Thinkofit.Preventonedeath,onereallyseriousinjury,onemajorinvestigation,oroneclassaction—evenasmallclassaction—andsuchasystem,operatedbyadatalawyerpracticingpreventivelaw,willbeaddingagreatdealofvaluetoanorganization.

Icompletelyagree.IalsolookforreleaseofabookbyBrestoffandInmoninlate2015,tobeentitledPreventingLitigation:An“EarlyWarning”SystemtoGetBigValueOutofBigData.

PreSuitisanOutgrowthofPredictiveCodingThekindofpredictiveanalytics,PreSuit,thatIamworkingonisbuiltonAI-enhancedsearchmethodswithlegalSMEinput.Ihaveperfectedthesebasicmethodsinhighstakeslitigation(includingtheDaSilvaMoorecase)andscientificresearchandtesting,includingTREC2015.SeeMr.EDR,AIEnhancedReviewandLegalSearchScience.Thesemethodsaredesignedtousethepowerofartificialintelligencetoleveragetheinsightsoflegalexperts.SeeMonicaBay,EDI-OracleStudy:HumansAreStillEssentialinE-Discovery(LTN,11/30/2013).Mycurrentsearchmethodsarebasedonleveragingtheknowledgeoflegalexpertsbyactivemachinelearning.Thesemethodscanbecustomizedtofitthecultureandneedsofparticularorganizationsandenhancedbycustomdataanalytics.AlthoughPreSuitmethodsbuildongeneralpastexperienceandknowledge,theyareintendedtobeindividualizedtodetecttheuniquethreatsofparticularinstitutions,andadapttotheuniquelanguagetheyuse.Ultimatelymygoalistodevelopanevenmoreautomatedsystembasedonavarietyofdataanalytictechniques,includingunsupervisedmachinelearningwithreducedhumaninvolvement.Thisshouldnotonlyimproveperformance,butalsodecreaseoperationalcostswhileincreasingprivacyprotections.

Themethodsdevelopedtodatecanbeusedwithanynumberofactivemachinelearningdocumentclassificationsoftware.Thesoftwaremust,however,ataminimum:

1. Allowformultimodalinput,asperthesearchpyramidshownright.

2. Containfourcylindersofsearchenginesfortraining:expert-judgmental,uncertainranked,high-probabilityrankedand

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random.SeeLosey,R.,PredictiveCoding3.0.3. Haveareliabledocumentrankingsystembasedondegreesofprobability,

notsimpleyes-no,andbeveryadaptivetoinclusionofnewdata.4. Becapableofveryhighspeedprocessingoflargedatasets.5. Allowforclose,intuitiveinteractionbetweenthecomputerandhuman

trainersandSMEsintheactivemachinelearningprocess.SeePredictiveCoding3.0;ReinventingtheWheel:MyDiscoveryofScientificSupportfor“HybridMultimodal”Search.

Thereareothersoftwarecriteriathatcanfacilitatetheapplicationofpredictivecodingforcompliancepurposes,buttheyrequireamoretechnicaldiscussion.

DataAnalyticsforPurposesofCorporateComplianceistheNextBigThingintheLaw

Iunderstandfromconversationswithmanyattorneys,corporatecounsel,andvendors,aswellasfromreadingtheFindingtheSignalintheNoise,thatseveralotherattorneysandcompaniesarenowbeginningtodevelopdataanalyticsforpurposesofcorporatecompliance.Mostaresoftwareagnosticmethods.Someusethegeneric,descriptivenameforthisofemailanalytics.JasonBaronandBennettBordenhavenamedtheirmethodEarlyWarningSystem,orEWS,andapplyit,likeIdo,tomorethanjustemail.Hereistheirshort,butinterestingdisclosureofEWSatpages29-30ofFindingtheSignalintheNoise:

AnEWSisatrickythingtoimplement,andrequirescarefulconsiderationofmanyfactors,employeeprivacyattheforefront.However,withcarefulplanning,policydevelopment,andtraining,aneffectiveEWScanbedesignedandimplemented.Predictiveanalyticsapplicationscanbetrainedtosearchforindiciaoftheconduct,language,orfactorsacrossinformationsystems.Thespecificsystemstobetargetedwillvarydependingonwhatisbeingsoughtandthesystemsmostlikelytocontainitandwillvarygreatlyfromcompanytocompany.But,whenproperlytrainedandtargeted,wehavefoundthesesystemstobeveryeffectiveindetectingandevenpreventingmisconduct.Webelievethatthisuseofpredictiveanalyticswillbecomeoneofthemostpowerfulapplicationsofthistechnologyinthenearfuture.

IagreewithJasonandBennettonallofthis.PreSuithasthepromisetobecometheultimatetoolforcorporatecompliance.Itmakesitpossibletodetectmisconductintheworkforceearlyenoughtoallowforcorrectiveactiontoavoidlitigation.ItreliesontheuseofwhatIcall“legalsmartdata,”whichisESIthatincludesaprobabilityofconnectionwithwrongfulconduct.ThismaysoundlikeMinorityReportsciencefiction,butAI-enhancedreviewnowmakesthiskindofbigdataanalysispossible.SeeMr.EDR(reportsonaccomplishmentsofmyteam’sparticipationusingKrollOntrackpredictivecodingsoftwareinthe2015TRECTotalRecallTrackresearchsponsoredbytheU.S.NationalInstituteofScienceandTechnology.)

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ImportanceofPrivacyConsiderationsIalsoagreewiththecommentofBennettandBaronontheimportanceofemployeeprivacyconsiderations.Ittakescarefulplanningandimplementationnottocreateachilling,bigbrotheratmosphere.Thisisnotonlybadforemployeemorale,but,asapracticalmatter,makesdetectionofillegalactionsmoredifficult.CaremustbetakennottoencouragebadactorstoexploitBYODandotherpolicies,andemployotherstratagems,tohidetheirillegalactivitiesfromcorporatedataanalytics.Openandfreecommunicationsarenotonlygoodforbusiness,butalsogoodforuseofPreSuitasanext-generationcompliancetool.Privacywillinpartbesafeguardedbythefactthatonlyacomputerwillanalyzeallcommunications.Inotherwords,adisinterestedartificialintelligencewillbereadingemployeeemails,nothumans.FleshandbloodhumanintelligencewillonlybecomeinvolvedandreademailsiftheAItriggersanalert.Eventhen,tofurtherprotectprivacy,Iproposethatthisfirst-lineofhumanreviewbelimitedtooutsidetrustedfiduciaries,namelyoutsidelegalcounsel.Theattorneyswillhaveahighdutyofconfidentialityandtheirworkwillbeprotectedbybothattorney-clientprivilege,andwork-productconfidentialityprivilege.Theattorneyreviewwillonlyscanthehighprobabilitydocumentsandmetadatathattriggeranalert.Thesealertsanddocumentsshouldbeveryfewinnumber,atleastaftertheprogramisestablished.(Theymaynotbefewinnumberatfirst,aspartofinitialset-upandtrainingofthesystem,orifthereareseriousproblemsrevealedatcommencement.Buteventually,thenumberofalertssoundedbyhighprobabilitydocumentsandmetadatapatternsshouldbecomerelativelysmall,eveninthelargestorganization.)Thecorporationitselfwouldonlybecomeinvolvedifthethirdpartyfiduciariesconfirmproblematiccomplianceissuesrequiringintervention.Fullprivacyprotectionrequiresthatthefirstlevelofhumanreviewthisbedonebyoutsidelegalcounsel,notin-housecomplianceofficers.Thissetsupthehighestlevelsofsecrecypossibleunderattorney-clientprivilege.Byusingattorneysasthefirsthumanmonitors,andasgatekeepersfordeterminingwhetherfurtherdisclosuretomanagementisappropriate,thehighestlevelsofconfidentialityarepossible.Properuseof

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theattorneyclientprivilege,andalsotheattorneywork-productprivilege,canprotectbothemployeeprivacyandemployerprivacyaswellascorporatetradesecrets.Theattorneyconfidentialityprivilegeswill,inmostcircumstances,protectagainstforceddisclosuresofanyillegalconducttothegovernmentandotherregulatorybodies,aslongaspromptcorrectiveactionsaretaken.Italsoprotectsagainstdisclosuretocompetitors,plaintiff’scounsel,andthegeneralpublic.ThewholepointofPreSuitistoenforcelegalcompliancewithoutpublicdisclosureandlitigation.Privacyisakeycomponentoftheentireprogram,whichiswhyIbelievethatconfidentialitybound,outsideattorneycontroliscritical.

HowPreSuit™WorksPreSuitascurrentlyconceivedmonitorsanorganization’semailcommunications,andotherESI,toidentifycorrespondence,connections,andmetadatathathaveahighprobabilityofassociationwithillegalandwrongfulactionsofallkinds,includingdiscriminatoryconduct,otherkindsoftortsandstatutoryviolations,breachofcontract,fraud,tradesecrettheft,etc.Thiscouldbedoneinreal-time,orperiodically.PreSuitwilluseartificialintelligenceprogrammedbylegalexpertstofitaparticularorganization.Withthistypeofexpertinputyoucancreatelegalsmartdata.Thisdatathentrainstherestofthesystemandranksalldocumentsaccordingtoprobabilityofconnectionwithvariousillegalactivities.GeneralcounselcanthentakeappropriatecorrectiveactionswhenhighprobabilitydocumentationofvariousactivitiesisidentifiedandconfirmedbyoutsidelegalcounselSomecompaniesandinsurersarealreadydoingthisusingmoresimplistictechnologies,suchaskeyworddetection,dataclustering,andunsupervisedmachinelearning,andsomedataanalytics.Nowwithactivemachinelearning,whichisatypeofpredictivecoding,orasIprefertocallit,AI-Enhancedreview,itismucheasiertodetectwrongsinthemaking.Itcanbeaccomplishedbyactivemonitoringofentire

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enterpriseemailandotherESI.ItisallamatterofknowinghowtoobtainandusewhatmanycallSmartDatatoserveasanearlywarningsystem,apredictorofbehaviorbasedonanalysisofpatternsandmetadata.MyapplicationofLegalSmartDatawillrevealemergingpatternsofwrongfulconductbeforetheyripenintolitigation.Iamnowworkingonadditionaldataanalytictechniquestoenhance,expandandmorefullyautomatethesefunctions.PresuitisthenextlogicalsteptotheapplicationofartificialintelligencetoBigDataandtheLaw.ItiswheretechnologyandComputerAssistedReviewareinevitablytakingtheLaw.Yes,ittakessignificantfundstosetupandoperatesuchaprogram,butthepotentialsavingsandotherbenefitsofpredictionandpreventionoflawsuitsaremind-boggling.

WhatisLegalSmartData?SmartDatagenerallyisinformationthathasbeenenhancedbypredictiveanalytics.(ForwhatothersoutsideofthelegalprofessionhavetosayaboutSmartDataseethisCDNetwebcast,andalsoseehere,here,here,here,andhere.)MostcommentatorsagreethatthewholepointofBigDataistoobtainSmartData.InthatsenseSmartDataisthesmall,useableSignalintheNoise.ThereareallkindsofSmartData,butforpurposesofpredictinglitigation,weareconcernedwithLegalSmartData.Thisisdatathathasbeenprobabilityrankedasrelevantorirrelevanttodifferentlegalcausesofaction.ItconsistsofdocumentsandotherESIcommonlyassociatedwithvarioustypesofillegalactivity.ThiskindofLegalSmartDatarevealspatternsofemergingwrongfulconduct.Itisinformationthatcanbeusedtodetectandpreventillegalactivities.Tobespecific,acomputerfile,suchasanemailorattachment,becomessmartforthesepurposeswhenithashadanextralayerofmetadataaddedtoitthatreliablyrankstheprobablerelevanceofthatfiletooneormorelegalissues.Thus,anemailwouldbesmartinthesenseitknowsithasa90%probabilityofbeingevidenceofacertainissue,suchasagediscrimination,orconsumerfraud,oremployeetheft.Dataisnotlegalsmartifithasnoprobabilityrankingrelatedtomisconductofsomekind.

PredictiveCodingExampleFromCurrente-DiscoveryPracticeAsanexample,whenIcompleteanactivemachinelearningtrainingofasetofcorporateemailaspartofadocumentreview,alloftheemailandattachmentshaveanextrametadatafieldaddedthatrankstheprobablerelevance,orirrelevance,toasetofoneormorelegalissues.(Thefinalreviewandproductionsaremadebasedontheseprobabilitymetadata.)Aspermycustom,whereappropriatetherewouldalsobeprobabilityrankingsforhigh-relevanceandprivilege.

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ThesubjectmatterexpertworkintrainingthesystemtransformedtheemailintoSmartData,datathatknowsitsprobabilityofrelevance.Thedataisassmart,asgood,aswasastheSMEonthesubject.Inotherwords,thedegreeofintelligenceofthedatawoulddependinpartonthedegreeofexpertiseoftheSME.WastheSMEaworldauthorityontheseissues,orjustthebestavailableatthetime?Hereiswheretheexpertiseonallemployeerelatedissuesofmylawfirm,JacksonLewis,isacriticaladvantage.Thedataisalsoassmart,asgood,astheworkputintothetraining.Inotherwords,thedegreeofintelligenceofthedatawoulddependinpartonthequalityofthehumantraining.Wasthetrainerqualified,experienced?Hereiswheremyparticularbackgroundinpredictivetrainingisanadvantage.Thedataisalsoassmart,asgood,asthesoftwarethatimproveduponthetrainingwork.Inotherwords,thedegreeofintelligenceofthedatawoulddependinpartonthequalityofthesoftware.Themachine—thealgorithms—enhancethenaturalintelligenceputintothedatabythehumanSME.Wasitthebestavailablesoftware?Diditperformwellonthisdata?ItypicallyuseEDRsoftwarebyKrollOntrack,whichrecenttestshaveshownworksexceedinglywellwiththePredictiveCoding3.0methodologyIuse.Degreeofsubjectmatterexpertise,humanskillintraining,andcomputerskillinanalysis–allthreefactorsimpactthequalityofanypredictivecodingproject.

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ThequalityofthepredictivecodinginturnimpactstheeffectivenessoftheresultantSmartLegalDatatotrainnewdataasitentersthesystem.Sotoowouldotherelements,suchasthediversityordistinctivenessofthepriororadditionaldata,orthelegalissuesinvolved.Werethesecommonissues,ortoouniqueforfurtherapplications?SmartLegalDatathatresultsfrommostpredictivecodingprojectscanandshouldbereusedtotrainnewdataasitislatercreatedandaddedtotheclient’ssystem.TheSmartLegalDatafromapriorcasewouldhavetobemodifiedsomewhattoeliminateinsignificantdistinctiveness,andculledsoastoonlyincludekeyprobabilityranges,butthisisnottoodifficult.ThemodifiedSmartLegalDatacouldthenbeusedastrainingdatatoranknewemailandattachmentsastoprobablerelevance.AtthispointtheSMEwouldjustplayasecondaryandoccasionalroleforqualitycontrolpurposes.Thetrainingcouldproceedautomaticallyinanunsupervised,oratleastsemi-supervised,manner.(ThatpartwillbemoredifficulttosetupandiswhatIamworkingonnow,alongwithmoregeneraldataanalytictechniques.)Whenpatternsemergesuggestingthatanewcauseofactionmaybedeveloping,alertsaresounded.Ourlawfirmisadvised.Whereaproblemisconfirmed,wediscretelyintervene.Presuithasavertedyetanotherlawsuit.TheultimateinLitigationReadinessistoeliminatesuitsbeforetheyhappen,toknowabouttheminthepresuitstage.Thisisnowpossibleinanongoingvirtuousfeedbackmachine-trainingloopthattakesSmartDatafromoldsuitsorinvestigationstotrainalldataincorporateESIsystems.

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OnceanSMEtrainsdatainthecourseofalawsuit,andmakesitsmart,theSME’smindhas,toacertainextent,imprinteditselfonthedata.Inourcurrentlegalpracticewhenanoldsuitisoverweflushthatintelligenceaway.Thecriticaldocuments,theSmartLegalData,arenotsavedforreuse.ThatisahugewasteofSMEintelligence,effort,andmoney.Instead,thekeycomponentsoftheSmartDatashouldbesaved,andimprovedupon,nurtured,andgrown.TheAIenhancedSmartDatashouldbeaddedbacktothecorporateESIsystems.TheSmartDatashouldbeusedagain,andagain,totraintherestofthedata.Itshouldbeusedasanindicatortodetectthesameandsimilarlegalissues.Forexample,onceyouhavecreatedSmartDataonfraud,keepitinthesystemtodetectmorefraud.Literally,ittakesathief’sdatatocatchathief’sdata.Iamremindedofthepopularsaying:Foolmeonce,shameonyou.Foolmetwice,shameonme.Thereislittledoubtthiswillwork,ifdonecarefullyandwithinputfromtherightscientistsandtechnologistsinthearea.BennettBorden’sinitialreportsarealsoencouraging.Thiswillnotaneasyundertaking,buttheresultsshouldbeincredible.ItisaprofoundexampleofwhatMIT’sBrynjolfssonandMcAfeewriteaboutintheirbook,TheSecondMachineAge.

LitigationAvoidanceByEarlyDetectionofRelevantDataYoucancallPresuitanaspectofInformationGovernance,ifyouwant,andsomelikeBordenandBaronalreadyare.ButIcallPresuitanaspectofLitigationReadiness(thefirststepintheEDBP).Itisthecompleteavoidanceoflitigationbyidentifyingandcorrectingwrongfulactionbeforeitfestersintoalawsuit.Nipitinthebud.Forexample,itcouldbeusedtodetectsexualharassmentintheworkplaceassoonasitbeginstomanifestinemailsortexts.BringtheemployeestoH.R.for

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counselingbeforeachargeisfiled.Thinkofthesavings;notonlymonetary,butmentalandemotional.Presuitandothersystemslikeitwillchangeeverything.

UsingSmartDataanalyticscandrasticallyreduceemploymentlitigation,butthatisjustthebeginning.Thesamecouldbeappliedtoalmostalllitigationthatnowplaguesbusinessandgovernment.Forafewexamplesconsidergovernmentfalseclaimsactcases,fraud,tradesecrettheft,patentinfringement,conspiracy,foreigncorruptpractices,etc.Anywrongfulactivitycarriedoutbyanemployeeinanenterpriseleavestracesinthecompany’sinformationsystem.UnderaPresuitprogramcomputersystemsareenhancedwithSmartDatatoidentifythesepatternsandalertmanagementtoinvestigate.Thelongertheprogramisinplace,thebetteritwillbecome.Aleveloneinvestigationbyoutsidecounselservingasgatekeepermayshowthatthecomputeralertwasafalsealarm,inwhichcasethecomputeranywaylearnsfromthepatterndetectionerror,andnoharmisdonetotheemployee.Conversely,ifthepatternwascorrectandconfirmedbyfurtherinvestigation,thencorrectiveactioncanbevoluntarilytaken.Themisconductcanbestoppedbeforeitgetsoutofhand.Employeescanbecounseledandretrained.Whereappropriatetheycanbedisciplinedorfired.Theentireincidentcanbekeptconfidential,cloakedbyattorneyclientprivilege.Insomeextremecasesanemployermaywanttoreporttheconducttothepoliceoraregulatorybody.Thisbecomestheirchoice.Theseremediesarefarbetterthanourcurrentsystemwherein-housecounseloftendonotknowofaproblemuntilaftersuitisfiled,oragovernmentsubpoenaisserved.Believeme,problemsareeasiertosolve,andfarlessexpensive,whenyoudonothavethehelpofplaintiff’scounselorthegovernment.

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NationalSecurityAgencyExampleForpurposesofquietinganynaysayerswhomaythinktheseproposalsarefarfetched,considertheexampleoftheNationalSecurityAgency.TheNSAessentiallytriestotaketheBigDataofallworldcommunicationstofindtheSmartDatarevealingpatternsofterroristactivities.TheNSAusessomemetadatakeywordsearchestoslightlyreduceamountofdata,butthenprimarilyreliesonpredictivedataanalyticstofindhighvaluetargets.InthecaseoftheNSAwhentheirSmartDatashowsprobableterroristactivities,moredirectsurveillanceandcorrectiveactionstepsaretriggered,warrantsareissued,andhumanagentsmoveintoaction.Thatisprecrimeinactiontotrytostopterrorism.Stillskeptical?Thenconsiderthemanypolicedepartmentsaroundtheworldthatareusingdataanalytics.ItisalsousedbytheU.S.DepartmentofHomelandSecurity.SeeegTheMinorityReport:UsingPredictiveAnalyticstopreventthecrimefromhappeninginthefirstplace!(IBM);InHotPursuitofNumberstoWardOffCrime(NYTimes);Policeembracingtechthatpredictscrimes(CNN);U.S.CitiesRelyingonPrecogSoftwaretoPredictMurder(Wired).Forageneralsummary,includingtheprivacyandethicalissues,seemyarticle,ShouldLawyersBeBigDataCops?.ThesamebasicsearchprocessesthatthepoliceandNSAusearealreadyavailabletocorporatecounselforPresuit.SmartDatasystemscanbesetuptoalertlegalcounseltoalltypesofpotentiallitigationtriggeringactivities.ThepredictiveanalyticssoftwaremaynotbeassophisticatedastheNSA’s,butcanworkverywell,especiallywiththemuchsmallervolumesofdatathatmostcorporationshavetodealwith(comparedtotheNSA).Forcorporatecounsel,thecompany’svaststoresofdatacanbetransformedintousefulSmartData.Again,thishappenswhenthedataisprobabilityrankedbyanongoingprocessofSMEmachinetrainingandotherdataanalytics.ThenthedatabecomesSmartandcanrevealprobableundesiredconductbyemployees,andbycontractorsdoingbusinesswiththecorporation.Itcouldbediscrimination,orfraud,oranynumberofcorporatetortsorbreachofstatutoryorcontractualduty.Thesesametechniquescanbeusedinevaluationsofcorporatemergersandothertransactions.Whenthesignalsaredetectedfromthenoiseofcorporateinformation,thenmoredirectlegalinvestigationsaretriggered.Correctiveandremedialactionsaretakenwhereappropriate.Themisconductisstopped.Damagesaremitigated,ifnotavoidedentirely.Mostimportantly,theexpense,publicdisclosure,andharassment

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oflitigationhasbeenavoided.Yourcomputerdoorshavenotbeenopenedtofishingbyplaintiff’scounselorthegovernment.

ConclusionPresuitisapowerfulnewtoolforcorporategoodcitizenshipthatwillbecomingyourwaysoon.ThepredictiveanalyticsfromrecyclingLegalSmartData,andotherdataanalytictechniques,willempowerlegalcounseltoidentifyandcorrectemployee(andrelatedparty)misconductbeforealawsuitisfiled.Whenwidelyadoptedbusinesseswillsavehundredsofbillionsofdollarsayearinwastedlitigationcosts.Weedingoutmisconductearlywillalsosignificantlyimproveemployeemorale,assumingtheprogramisethicallyadministeredwithafullsuiteofprivacysafeguards.Presuitcanfreeacompanytoactinaccordwithitsidealsandallowallofitsemployees,especiallyitsuppermanagement,tooperateatpeakefficiencyandproductivity.TobesuccessfulaPresuitprogramshouldnotonlycomplywiththeminimumrequirementsofthelaw,butshouldgofurthertosafeguardtheprivacyrightsandindividuallibertiesofallemployees.Apowerfulearlywarningsystemofemployeemisconductsuchasthismustnotstifleemployeecreativityandfree-flowing,honestcommunications.MyconcernsabouttheethicalcomponentsofPresuit,andcommitmenttoavoidthepotentialdarksideofBigBrotheremployeesurveillance,arecoremotivationsbehindmyefforts.Letmeknowifyouareinterestedinlearningmore.Iamstillintheearlytestingphasesandsoyoucangetinonthegroundfloor.Ifyourannuallitigationbudgetissevenfiguresormore,thisprogramwillbeofsubstantialbenefit.Theraceiswonbytheswift.Anyin-houselitigationcounselorcomplianceofficersinterestedinassistinginthetestingphasesnowunderwayshouldemailmeatRalph.Losey@jacksonlewisdotcom.

“Thegreatestvictoryisthatwhichrequiresnobattle.”―SunTzu,TheArtofWar