Successfully Managing the Legal Issues of AI Adoption Kemp ......Nov 09, 2016 · Case study 1 –...
Transcript of Successfully Managing the Legal Issues of AI Adoption Kemp ......Nov 09, 2016 · Case study 1 –...
SuccessfullyManagingtheLegalIssuesofAIAdoption
KempITLawBreakfastSeminar
London9November2016
• 09.05– 09.25:TheapplicationofAI/cognitivecomputinginlegalservicesandcompliancemarkets,TimHarty,GlobalHeadofActionableIntelligence,ThomsonReuters
• 09.25- 09.45:LegalIssuesinAI– casestudies,DeirdreMoynihan,KITL• 09.45- 10.00:coffee/networking• 10.00– 10.20:novellegalissuesandkeypointstowatchoutfor,RichardKemp,KITL• 10.00– 10.30:Q&A,discussion• 10.30:sessioncloses
Agenda
The Application of Artificial Intelligence in Legal & Compliance
Tim Harty, Thomson Reuters
REUTERS / Firstname Lastname
Covering
• Introduction to Artificial Intelligence / Cognitive Computing
• Application of Cognitive Computing in Legal and Compliance
• Cognitive Computing at Thomson Reuters
The Fourth Industrial Revolution
Disruptive, pervasive, fast evolving and line-blurring
• Artificial Intelligence• Robotics• 3-D printing• Biotechnology• Cloud computing• Internet of Things• More...
What is AI / Cognitive Computing?
Cognitive systems understand human expressions – textual, verbal, visualBy reasoning about the actual intention or problem being addressed They learn how to recognise patterns of meaning through examples and feedbackAnd they interact with humans on their own terms
… and do so at scale.
Cognitive systems aim to amplify
human cognition
The simulation of human thought processes in a computerised model
• Information need• Events (triggers)• Exploratory• Experience-based
Find
• Model-based• Hypothesis
generation• Inferring/Reasoning• Evaluation
Analyse• Scenario generation• Optimization• Answering• Deciding• Advice
Decide
The simulation of human thought processes in a computerised model
What is AI / Cognitive Computing?
Component Technologies
Natural Language Processing – Machine Learning – Search/Q&A – Knowledge Base –Inference Engines – Deep Learning
AI Examples – Controlled Experiments
Act like a chess master (1997)
Act like a Jeopardy contestant(2011)
Act like a Go champion(2016)
• Moore’s Law – computing power doubles every two years
• What happens when AI starts training itself?
AI Examples – Coming in From the Wild?
Act like a driver
Act like a teenager
Act like an assistant
• Pervasive
• Taking action
• Garbage-in, garbage-out
Components of AI are already in use legal & compliance
Answer compliance questions Conduct more thorough legal research
Find relevant documents Identify hidden risks
Suggest research avenues and documents based on understanding of your research path
Technology assisted review tags relevant documents based on a trained seed set
Contract management systems that transform documents into structured data and provide actionable intelligence on risk levels
Natural language Q&A over complex and shifting regulations
Near Term Legal & Compliance Examples
Legal Assistant Solve Disputes
Technology assisted decision support, such as to suggest the best order in which to renegotiate a series of corporate contracts
Online dispute resolution systems use previous decisions to improve on settlements
Looking Ahead
Persistent Assistant Automate ComplianceRecommend Legal Strategies
Coming in the not too distant future
• Accelerate the development of Cognitive solutions by providing dedicated focus and resources
• Explore and develop in house capabilities in the rapidly developing field of cognitive computing
• Act as a clearing house for potential applications of cognitive computing across Thomson Reuters
• Based in Toronto, Canada, with satellite teams in business hubs
Led by Khalid Al-Kofahi, Head of R&D for Thomson Reuters
Thomson Reuters has a unique combination of assets to develop differentiated Cognitive Computing solutions
Thomson Reuters – Centre for Cognitive Computing
Data
Data
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Cognitive computing enables TR to automate and accelerate knowledge work
Cognitive ComputingInputs
Finde.g. What regulatory obligations were created last month?
Comparee.g. How do those obligations relate to pre-existing obligations?
Understande.g. What happens if I don’t comply with these obligations?
Decidee.g. What do I have to do to comply with these obligations?
Tasks
Machine Learning
Natural Language Processing
Knowledge Models
+Reasoning
Engines
Data
Taxonomies
Dictionaries
What are we heading?
Intelligent Agents that understand the domain, the task and learn from the user. Always on, responsive and proactive
• Answer questions
• Analyse scenarios
• Measure risk
• Provide advice
Big questions remain to be answered
• What are the likely impacts on business models?
• What are the impacts on legal & compliance careers?
• Who are the winners, who are the losers?
• What should organisations be doing to prepare?
DeirdreMoynihan,KITL
• Casestudy1:legalservices• Casestudy2:autonomousvehicles• Casestudy3:smartcontracts
LegalissuesinAI:casestudies
• UKMarketforLegalServices
• £30bnUKindustry• 2%ofGDP• SubstantialinvestmentinAIinlegalservicesin2015/2016
Casestudy1– AIinLegalServices
• AIdevelopingasatooltosupportrepetitive,processintensive,standardisablecomponentsoflegalwork:
• Corporateandfinanceduediligence• E-discovery• Contractreview,draftingandanalysis
Casestudy1– AIinLegalServices
• 4maincharacteristicsoflegalservicesAI:
• Naturallanguageuserinterface• Contextawaremachinelearning• Abilitytogenerateevidencedbasedresponses• Cognitiveanddynamic
Casestudy1– AIinLegalServices
• RegulatorybackgroundforLegalServices
• SolicitorsRegulationAuthority• Clients’Regulators• SRA’sCodeofConduct– Outsourcing• TermsofEngagement• Insurance
Casestudy1– AIinLegalServices
Casestudy2- vehicles
HandsOn,EyesOn
HandsTemporarilyOff
HandsOff,EyesOff
Casestudy2- vehicles
Source:adaptedfromOECDInternationalTransportForumpaper,‘AutonomousandAutomatedDriving– Regulationunderuncertainty,page11,http://www.itf-oecd.org/automated-and-autonomous-driving
Typesofsensorsrequiredforanautonomousvehicletoreplicatehumanskillsandexperience:
Casestudy2- vehicles
• UKRegulatoryApproach
• DfT hassetuptheCentreforConnectedandAutonomousVehicles
• RegulationReviewFeb2015• CodeofPracticeforTestingJuly2015• ConsultationJuly2016
• PermissibletotestautonomousvehiclesintheUKwithoutlicenseorpriornotification
• Needto(i)amendinsurancelegislation,(ii)clarifyprovisionsrelationtothebuildanduseofnew/neartomarkettechnologies,(iii)provideguidancetodriversregardingsafeandappropriateuseofautonomousvehicles
Casestudy2- vehicles
Casestudy3– smartcontracts
• Blockchain
• TechnologybehindBitcoin• Comprehensive,alwaysuptodate,distributedrecordorledgerofwhoholdswhatorwhotransferredwhattowhom
• Worksthroughcryptography• Eachuserhasacompleteandcurrentcopyoftheblockchain
Casestudy3– smartcontracts
• Smartcontracts
• Softwarecoderepresentingaself-executingcontractasanarrangementthatacomputercanmake,verify,executeandenforceautomaticallyunderspecifiedconditions
• Benefitsincludelowercosts,latencyanderrorrates• Evolutionnotrevolution
Casestudy3– smartcontracts
• Issues
• Regulatoryissuessurroundcommercialadoptionofblockchaintechnology• Technologyisfragmentedandcommonstandardsneedtobeagreedandadopted• Scalability• Needtorepresentcontractualrulesassoftware• Relationshipsbetweensoftwarebuilders,operators,contractingpartiesandotherusers• Ensurethatsmartcontracthasthesamestatusascurrentcontractualforms
Casestudy3– smartcontracts
DeirdreMoynihan
RichardKemp,KITL
• Somecommonmisconceptions– agency,entitiesandlegalpersonality• ContractingforAI:whataretherisksandhowaretheybestmanaged• Regulation– disappearingdownathousandfoxholes?
AI– novellegalissuesandkeypointstowatchoutfor
• AnthropomorphisingAI– the‘IRobot’fallacy• Thinkbigdataandsoftwareratherthanhumanandbrain
• Imputingrightsanddutiesfromactions– the‘agencyfallacy’• AnagentmustbeapersonandanAIsystemisnotofitselfaperson
• The‘entityfallacy’:platformsandDAOspossessseparatelegalpersonality• Asmartcontractplatformwillbeoperatedby,butisunlikelytobe,aperson
AI– somecommonmisconceptionsclarified
• WhatinterestsshouldAIregulationprotect?• “AIhasapplicationsinmanyproducts,suchascarsandaircraft,whicharesubjecttoregulationdesignedtoprotectthepublicfromharmandensurefairnessineconomiccompetition”(USFutureofAIReport,Oct2016)
• Shouldexistingregulatorystructuresbeadaptedornewonesputinplace?• “Ifan[AI-related]riskfallswithintheboundsofanexistingregulatoryregime,thepolicydiscussionshouldstartbyconsideringwhethertheexistingregulationsalreadyadequatelyaddresstherisk,orwhethertheyneedtobeadaptedtotheadditionofAI”
AIandregulation
• Howshouldregulatoryburdensbekeptproportionate?• “whereregulatoryresponsestotheadditionofAIthreatentoincreasethecostofcompliance,orslowthedevelopmentoradoptionofbeneficialinnovations,policymakersshouldconsiderhowthoseresponsescouldbeadjustedtolowercostsandbarrierstoinnovationwithoutadverselyimpactingsafetyormarketfairness”
• Whatroleshouldcentralgovernmentplay?• “itistoosoontosetdownsector-wideregulationsinthisnascentfield”(UKHoC selectcommitteereport,Oct2016
• UKfavourssettingupaCommissiononAIandaRASLeadershipCouncil• USreportadvocatescommongoalsforgovernmentandagencies
• AI,the4th industrialrevolutionandBrexit– badtimingfortheUK?
AIandregulation
• Autonomousvehicles– theUK’sapproach• Ensuretherearenoobstaclestotestingvehicletechnology• Consultwidely• BreakregulatoryelementsdownintobitesizeschunkstopragmaticallyalignregulationtoADASandAVSdevelopment
• Legalservices• BoughtinAIfallswithinthecurrentregulatorystructureasoutsourcing(O7.10)• AllotherSRACodeofConductrequirementsapplyanyway
AIregulation:autonomousvehiclesandlegalservices
• Commercialcontractsforthedevelopment,provisionanduseofB2BAIsystemsbetweendeveloper/licensor/providerandlicensee/customer
• Largelyindistinguishablefromothersoftwarecontracts,whetherprovidedon-premiseasalicenceorintheCloudasaservice.
• Smartcontracts– morecomplex• Codingthecontractualecosystem– ‘Chittyoncontractsincode’• Developer/platformoperatoragreement• Platformoperator/useragreement
AIandcontractlaw
• Copyright• ‘Inthecaseofaliterary,dramatic,musicalorartisticworkwhichiscomputer-generated,theauthorshallbetakentobethepersonbywhomthearrangementsnecessaryforthecreationoftheworkareundertaken’(s.9(3)CDPA)
• ‘computer-generated’means‘thattheworkisgeneratedbycomputerincircumstancessuchthatthereisnohumanauthorofthework’(s.178CDPA)
• Patents• Computerimplementedinventionscontributingtothetechnicalfieldofknowledge(potentiallypatentable)beyondcomputerprogramassuch(notpatentable)(Macrossan,etc)
• Ifpotentiallypatentable,‘“inventor”meanstheactualdeviseroftheinventionand“jointinventor”shallbeconstruedaccordingly”‘(s.7(3)PA)
• Solution• Legislatecontractuallyforownership,assignment,licensingofcomputergeneratedworksandcomputerimplementedinventions
AIandIPlaw:computergeneratedworks&implementedinventions
• Negligence• Thecommonlawduty‘tobecareful’• ‘thecategoriesofnegligenceareneverclosed’• LikelytoapplytomostAIs?
• Nuisance• Interferencewiththeuseorenjoymentofland• AIrunningamokanalogisedtostrayinganimal?• Rylands vFletcher – escapeof‘dangerousthing’?
• Productliabilityandbreachofstatutoryduty• Willfollowregulation?
AIandtortlaw
RichardKemp