Artificial Intelligence and the Law.pdf

Learning the role of artificial intelligence in law

1. ARTIFICIAL INTELLIGENCE
AND THE LAW
DR. BUKOLAO. OCHEI
DEPARTMENT OF PUBLIC LAW

2. Learning Objectives
1.Understand Artificial Intelligence (AI), have a basic definition of AI and know the
major branches of AI
2.Understand Machine Learning (ML) and the components of ML, appreciate the
advantages and Disadvantages of ML and understand the limits of AI
3.Have an overview of the History of AI and the Law and discuss AI within law and
legal studies
4.Have an appreciation of the Benefits and Shortcommingsof AI within the Law
5.Consider current and policy issues on AI

3. Artificial Intelligence Generally
1.What is AI?
Rules, Logic and Knowledge Representation
Approach
Machine Learning Approach
Hybrid Approach
2. Artificial Intelligence and the Law
➢History of Artificial Intelligence and the Law
➢Artificial Intelligence in Law Today
3. Current Policy Issues in Artificial Intelligence
and the Law

4. What is Artificial Intelligence
AIisthetheoryanddevelopmentofcomputersystemsabletoperformtasksnormally
requiringhumanintelligence.
ArtificialintelligenceisusingcomputerstoSolveProblemsormakeautomated
decisionsfortasksthatwhenhumansdothemtypicallyrequireintelligence.
Suchasplayingchess,drivingcarsortranslatinglanguages.Thesearealltasksthat
arethoughttohavehigherordercognitiveprocesseswhenpeopledothem
Ifacomputercansolveproblemsthatareconsideredasrequiringcognitive
processes,itisregardedasanAItask.
However,itmustbeunderstoodthatcomputerssolvetasksdifferentlyfromhumansas
AItasksinvolvetheautomationofactivitiesthatinvolvehumanintelligence.

5. Limits of Artificial Intelligence
We don’t have Strong AI
Computers that think at a level that surpasses humans
Computers that engage in Abstract thinking
i.e. thinking that Artificial Intelligence can discuss points of law and facts
ThereisnoStrongAItoday–strongAIwouldbecomputersthatcanthinkatalevel
thatmeetsorsurpassespeopleorcomputersthatcanengageinabstractreasoningand
thinking,conversationinarbitrarytopics.Today’smostadvancedAlgorithmscannotthink
norreplicatehumanhigherorderofcognitivereasoningasatwoyearoldhasmore
advancedcognitiveabilitiesthanmostadvancedAItoday

6. Artificial Intelligence
AI is predominantly pattern-based AI; this involves the use of algorithms to search large amounts
of data or patterns that can be channeled and used. The formal name for this is, Machine
Learning.
Pattern-based AI is a very formidable tool that has been used to automate many processes today;
such as language translation, fraud detection, driving and even fraud detection.
In limited domains, the current AI technology can do wonderful things, it is however not unlimited
in what it can do.
It also includes the ability of computers to adapt to new circumstances and is regarded as a
combination of different abilities
Although pattern based AI is the dominant mode of AI currently, there is also the rules-based
logical AI systems which is used to a lesser extent.

7. What Artificial Intelligence Currently Is
AI is the theory and development of computer systems
able to perform tasks normally requiring human
intelligence, such as:
Visual perception
Speech recognition
Decision-making
Language translation

8. Major Branches and Approaches to AI
AI can be roughly divided into two large groups
i.Computer Logic and Rules-Based (XR)
Approach
ii.Machine Learning (Pattern-Based) Approach

9. Logic, Rules and Knowledge Representation
Based AI
Rulesandknowledgebasedsystemsarepartofalargercategoryof
ArtificialIntelligencealsoknownasknowledgerepresentation.
Theaimofknowledgerepresentationistomodelrealworldprocesses
orsystemsinwaysthatacomputercanuseandprocess.
Thismeansthatprogrammersorgroupsofengineersobservereal
worldtasks,ofteninvolvingexperts,whichhascertainrealworld
constraintsandrules.
Thentheyattempttomodelthatrealwordprocessincomputerformin
termsofcomputerrulesandrelationships

10. A good example of this AI within law-is the ‘Turbotaxexpert system software’ for tax
assistance which people use to assist them in tax related issues. For instance, the
‘Turbotax’ software can compute tax liability in terms of Personal Income Tax Laws. The
‘Turbotax’ software is an example of a knowledge representation based version of AI.
ThecompanythatcreatedTurbotaxendeavoredtomodelsomethingoutthere-
personalincometaxlaw,asetofrealworldconstraintsonpeople’slegalliabilitiesand
duties–theymodeledpeoples’personalincometaxlawasasoftwareinawaythatit
representsthelogicandthemeaninginthelaws.
Theprogrammers,inconsultationwithlawyersandaccountantsstudiedthepersonal
incometaxlawsandreducedittoasetofrulesandattemptedtotranslatetherulesinto
asetofcomprehensiblerulesthatthecomputercouldunderstand.Thisisknownasan
expertsystemwhereknowledgeofexpertssuchaslawyersandaccountantshasbeen
reproducedcomputationallyandpatternedtoproducerealworldresultssuchastax
liability

11. What Machine Learning Is
Algorithms that find patterns in data and infer rules
on their own
Learn from data and improve over time
Use the patterns to automate or predict
In this context, it is best to consider ML as a group of
things as opposed to a single thing

12. Uses of Machine Learning
Self-driving
Netflix, Showmax–automated
recommendations
Google translate –computer translation

13. Characteristics of Machine Learning
1.Learning–algorithmsarespecificallydesignedto“learn”.Theyarelearningbecausetheyimproveon
theirperformanceovertime,oftenbybeingshowngoodandbadexamplesofwhattodo.
AIcanapplydifferentformsoflearningsuchaslearningbytrialanderror,memorizingindividualitemsand
procedures,knownasrotelearning,also,generalization;applyingpastexperiencetoanalogousnewsituations
2.PatternDetection-Muchofmachinelearningcanbethoughtofaspatterndetectionsystems
designedtodetectnon-obviouspatternsofbehaviororcorrelationsinlargeamountsofdata.These
patternsarethengeneralizedandusedinothercontextstomakeusefuldecisions.
3.Data-Machinelearningrequiresdata,often,largeamountsofdatatodetectthepatternsthatcanbe
usedtoautomatedecisions.Inlaw,thiscanbeaproblembecausenotalotoflegalinformationis
availableinhighlyprocessibleform,muchofitisbehindpaywallsornon-accessiblestructures.
4.Self-Programming-MLisregularlyconsideredasself-programming,becauseself-programmingagents
recorddatainmemoryastheylearnandthisprogramcancontroltheexecutionoflearneddataas
sequencesofinstructions

14. Key Note on ML
IntelligentResultswithoutintelligence-MLingeneraldoesnothavethecognitiveabilities
ofhumans,itthereforeachievesthe“intelligence”requirementthroughproxiesorstand-
ins.
Whenproxiesandstand-inscanbefound,thecomputerdoesnothavetounderstandthe
deepconceptuallayerinordertomakeadecision.
AIdoesnotknowthemeaningofwordslike“free”or“spam”
Itgets“intelligent”automatedresultswithoutintelligencebyfindingsuitableproxiesand
patternstomakeusefulautomateddecisionswithoutactuallyhavingunderlyinghigher
ordersofhumanintelligence.

15. The Proxy Principle for Automation
It has to do with detecting patterns that can serve as proxies for some underlying cognitive task.
Hybrid Systems
AlthoughtherearetwomajorAItechniques–LogicandRulesBasedApproach,andMachine
Learning(PatternBasedApproach),maysuccessfulAIsystemsarehybridsofMLandRules-Based
Hybrids.
Anexampleofthisisself-drivingcarswhichemploybothapproacheseffectively.
HumanIntelligence+AIHybrids
ThereisamisunderstandingthatAIisreplacinghumans,butthatisnottrue,rather,itismosttimes
bettertothinkaboutitasenhancinghumans.Also,manysuccessfulAIsystemsworkbestwhen;
Theyworkwithhumanintelligence
AIsystemssupplyinformationforhumans
ManyAIsystemshavehumansintheloop

16. Human Intelligence + AI Hybrids Contd.
WithacombinationofhumanintelligenceandAIHybrids,humansareable
tomakebetterdecisions.Forinstance,althoughacomputermaybethe
bestcomputerplayerintheworld,acombinationofHumanIntelligenceand
AIcanbeatmanyofthebestcomputerprogramsbecausethehumanchess
playersabilitiesarebeingenhancedbythecomputers.
AlthoughAIisoftenthoughtofasbeingautonomous,manyAIsystemsstill
havehumansintheloop.Theideaisthatacomputerwilloftenaskforhelp
fromahumantomakeajudgmentdecisionoranabstractconceptualization
aboutanareawherethecomputerisnotabletoperform.
Assuch,AIsystemsarenotfullyautonomous.

17. Ways AI Will Benefit the Law
AIcanbehelpful;itcanenableimprovementinproductsandservices,notreplace
humansthatusethem.Itcanimproveproductivityandefficiencythroughtheuseof
softwarethatcandraftdocuments,improvesearchandextractionofrelevantcontent
foranalysis–KIRA,COINC,RAVEL
Itcansavetime,moneyandimproveefficiencybymanagingemails,billingsand
productivity.
Inthecontextoflegalresearchandanalytics,AIiscapableofsiftingthroughmillionsof
legalprecedentstofindrelevantcaselawinseconds,itcanalsoreviewjudges
sentimentsinanyissueoflawandalsoanalyseopposingcounsel’sstyleandreasoning
onspecificissues,basedonhispastrepresentations.
AccordingtoAruda’sTEDTalk,ROSS(asoftwaredevelopedbyaNIgerian)canreadovera
millionpagesoflawinseconds,findtheexactpassagesneeded.Thisisanexampleofhow
AIlevelstheplayingfieldwhenitcomestoresearch.
Itmakesyouproactiveasopposedtodefensive,itconnectsthedotsandgivesan
advantage.

18. History of Artificial Intelligence and Law
Early thinkers
GottfriedWilhelmLeibniz(1600’s)–oneoftheco-inventorsofcalculus,wasbotha
mathematicianandalawyer.Asfarbackasthe17
th
century,Leibnizpostulatedthatlaw
couldbemademorepredictable,moremeasurable,moreuseful.ThisistheheartofAIin
law,usingcomputationalandmathematicalformulatomakelawmoreunderstandableor
accessible,predictable,manageableanduseful.
Leibnizcontributedtomathematics,aswithmanylawyerswhohavemadeimportant
contributionstomathematics.Forinstance,themathematicalconceptofLinearalgebra
whichisbasicallythemathematicalbackboneofmostofmachinelearningcurrently,was
foundedbylawyers;ArthurCayleyandJamesSylvesterwerebothlawyersand
mathematicians.
Thereisalongtraditionoflawyersinfluencingmathematicsintheinterconnectivity
betweenlawandtechnology

19. Pre-AI Modern Era
Lee Loevinger(Jurimetrics)-The real modern era of AI in law started prior to the emergence of
computing and can be said to go back to Loevingerwhose idea of jurimetrics evolved in the 1940’s
Era of Knowledge Representation
The heart of AI and Law started in the 1960-1980’s where we can see the early pioneers of AI and Law
such as Ashley K; McCarthy, T. (coined the term ‘Artificial Intelligence); Gardner, A.; Hefner C.;
Rissland, E.; Sussland, A.; Allen, L.; Sergot, M. Kowalski, R.; Winkels, R.; Sussland, R.; Governatori,
G.; ShannonC.
ManyoftheearlypioneersofAI,whowerecomputerscientistsstartedtheideaofrepresentinglules
tolaw.Here,therewereattemptstomodellegalargumentsformallyinwaysthatcomputerscould
understand.Theyendeavoredtomodellegislationandregulationsinwaysthatcomputerscould
understand,throughlegaltextextractionandstatutorymodelling.
Someimportantideascomeoutofthepre-modernera,suchasJURIXandIAAILwhichstillexist
today.TheyareconferencesdedicatedtoAIandLaw.
MostoftheAIinresearchoccurredinEurope,Italy,Netherlands,EnglandandGermany.Theywere
thehotbedsofAIandcontinuetobeso,eventillnow.

20. Present Era –2000 till date, the Legal Tech and Machine Learning Era
Innovations in AI continued into the 21
st
century and led to the founding
the following
Codex
Legal Tech Startups such as those in Nigerialike LawPadi, Lawyardand on
the internationalarena, like, Ravel Law, Luminance, Enoron, Farewell, and
Lexoo
Legal Analytics and predictions (eg. LexMachina)

21. Three Categories of AI in Law Today
TherearethreecategoriesofAIinlawcurrently:
1.AdministratorsofLaw–thesearepeoplewhocreateandapplythelaw;Judges,Legislators,
governmentofficialsandregulators
2.PractitionersofLaw–legalpractitionersandothersinterpretingoradvocatinginthelegal
system.Hereweseee-discoveryandtechnologyassistedreview,legalanalytics,venueanalysis
andcaseoutcomepredictionscomeintoplay.Also,legaldocumentassembly,automated
documentanalysisanddiligence,naturallanguageprocessing(NLP)oflegaldocuments,
computablecontracts,legalresearch,lawfirmmanagement,casemanagement,docketingand
workflowsystems
3.UsersofLaw-ordinaryindividualsorbusinessesthathavetocomplywiththelaw,suchas;
i.BusinesseswhichhavetocomplywithregulationsuchastheGeneralDataProtectionRegulation
(GDPRandtheNigerianDataProtectionRegulation(NDPR2019).Theyalsoutilizecomputable
contracts,expertsystems,automateddisputeresolutionandautomatedlegaldocuments.
ii.Therearealsoordinarypeoplewhoutilizelegalexpertsystems,legalchatbotsandautomated
legalself-help,automatedlegaldocumentassembly,amongstothers

22. Shortcomings of AI/What AI is Bad AT
It raises ethical questions as deep learning algorithms which are the basis of
many of the most advanced AI tools are only as smart as the data they are
given in training.
There is a potential for human bias which must be monitored closely
There is always a need for the indispensable human element in AI
Also, AI cannot replace the following –Judicial Roles, Client engagement,
development in areas of institutional voids ( AI cannot develop new business
areas such as medical law, sports law, construction law etc), and government
relations, such as developing legislation and regulations.
These require an understanding of people, government and even the political
landscape. AI cannot do these.

23. ShortcommingsContd.
AI cannot perform abstract, conceptual tasks , as such, lawyerly tasks involving are less
susceptible to being swept away by AI.
i.Abstract thinking
ii.Problem solving/ Advocacy
iii.Client counselling
iv.Human emotional intelligence
v.Policy analysis
vi.Creative thinking
vii.Big picture strategy.
All these tasks are less likely to be subject to AI’s automation in the near future, given the limit of
the current AI technology. As such, these are the areas that intending lawyers should focus on.

24. Ways AI Will Benefit the Law
AIcanbehelpful;itcanenableimprovementinproductsandservices,notreplace
humansthatusethem.Itcanimproveproductivityandefficiencythroughtheuseof
softwarethatcandraftdocuments,improvesearchandextractionofrelevantcontent
foranalysis–KIRA,COINC,RAVEL
It can save time, money and improve efficiency by managing emails, billings and
productivity.
Inthecontextoflegalresearchandanalytics,AIiscapableofsiftingthroughmillionsof
legalprecedentstofindrelevantcaselawinseconds,itcanalsoreviewjudges
sentimentsinanyissueoflawandalsoanalyseopposingcounsel’sstyleandreasoning
onspecificissues,basedonhispastrepresentations.
According to Aruda’sTED Talk, ROSS (a software developed by a NIgerian) can read over
a million pages of law in seconds, find the exact passages needed. This is an example of
how AI levels the playing field when it comes to research.
It makes you proactive as opposed to defensive, it connects the dots and gives an
advantage.

25. Current Policy Topics with AI and the Law
These are what AI researchers and others are considering about AI today
Automation of Legal Jobs
SometasksinlawthatweretraditionallydonebylawyersarebeingautomatedbyAI.Lawyersare
nowdoingamixtureoftasksthatrunfromhighlyabstracttotheroutineandmechanical.The
mechanicallegaltaskswilllikelybeautomatedoncethereisanunderlyingstructureorpatternthat
canbeharnessed.
CreationofNewLegalJobs
Justastechnologyistakingaway,itwillalsogiveandthishasbeenaconstantintheevolutionof
man.Forinstance,humancalculatorswerereplacedbycomputersinthe1950’s.
Intheshortterm,somejobswillbelostinlawduetoAI,butnewjobsalsoemerged,createdbyAI;
computergamedesigner,webprogrammer,systemsanalystsetc.
ItbecomesnecessarytothinkaboutthesocialimpactofAInotjusttolawbuttotheNigerian
societygenerally