Artificial intelligence tools in legal work automation: The use and perception of tools for document discovery and privilege classification processes in Southern African legal firms

Date
2021-03
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: The field of artificial intelligence is revolutionizing the way things are done. A significant number of innovations have been notable in many fields, ranging from medicine, media, agriculture, transport among others. This thesis presents a theoretical and practical analysis on the role artificial intelligence plays in shaping legal systems. Notable innovations in the use of artificial intelligence in the legal sector have been experienced in countries such as the USA, Germany, the United Kingdom, Australia, and China among others. These innovations seek to improve operational efficiencies of justice delivery. Artificial intelligence has been used to predict decisions of certain cases, to model and design cases in order to produce a certain outcome, elsewhere it has been used in drafting contracts or in reproducing certain outcomes in similar types of cases.This thesis therefore seeks to understand the extent to which artificial intelligence algorithms are currently being utilized in the field of the law. It further seeks to map and define existing tools, the nature of their operations and how they are being employed. To this end, a selection of artificial intelligence platforms that are available to the legal profession have been considered in this study. These include platforms such as Rave Law, Deligence, Lexis Nexis, Ross Intelligence, Do Not Pay, Aletras and Lex Machina. Lastly, this thesis has sought to discover the extent to which such platforms are used in Zimbabwe and South Africa, and whether there is already any understanding and appreciation of their benefits.The thesis focuses on two primary aspects of the court process in which such platforms can be of service, namely privilege classification and document discovery. These are studied within the context of the court process taking into account the stages in which they occur, so that their key elements are identified. This approach has been taken because the procedures of privilege classification and document discovery are an integral part of the generic and standard court process for such procedural steps do not exist in isolation. The thesis adopted a mixed methods approach in gathering the evidence and the results of which informed the findings. A key informant interview guide was developed, which was administered to participants, some who were involved in the designing of artificial intelligence platforms and others who worked for companies marketing such programmes. In addition to the key informant interview, a structured questionnaire also was administered to law firms to map out their understanding of the applicability of artificial intelligence in the law and to revealcurrent usage patterns. Results from the data analysed suggest that there is generally a low uptake of legal artificial intelligence tools in Zimbabwe and South Africa. However, law firms have started to adopt artificial intelligence technologies to help improve legal service delivery. Results indicate the general appreciation of artificial intelligence algorithms in improving legal service delivery among lawyers; however, these results also show evidence of fears among lawyers that artificial intelligence is going to replace human beings, there is a feeling among respondents that artificial intelligence will take away their work and that such a threat should be resisted. This thesis concludes by providing recommendations for effective utilization of artificial intelligence tools in the law. It suggests that developers should better inform prospective users to raise awareness to the potential of their systems and thus encourage their uptake.There is also need for a general training of users to ensure maximum utilization. Additionally, this thesis recommends customization of legal artificial intelligence platforms at common law jurisdiction level in order to ensure that the law, which is unique to each jurisdiction, is available in a customized format so that it may meet the requirements of each legal system at a local level.
AFRIKAANSE OPSOMMING: Die veld van kunsmatige intelligensie revolusioneer die manier waarop dinge gedoen word en 'n beduidende aantal innovasies kan in ‘n verskeie velde, onder ander van medisyne, media, landbou, tot vervoer, bespeur word. Die tesis bied 'n teoretiese en praktiese ontleding van die rol wat kunsmatige intelligensie in die regspraktyk speel. Opvallende innovasies in die gebruik van kunsmatige intelligensie in die reg sektor is reeds in lande soos die VSA, Duitsland, die Verenigde Koninkryk, Australië en China beskryf. Hierdie innovasies poog om die bedryfs doeltreffendheid van die lewering van geregtigheid te verbeter. Kunsmatige intelligensie is byvoorbeeld ingespan om beslissings van sekere sake te voorspel, om sake te modelleer en te ontwerp vir bepaalde uitkomste, elders word dit in diens van die opstel van kontrakte of die weergee van resultate in soortgelyke hofsake. Die tesis poog om te verstaan tot watter mate kunsmatige intelligensie algoritmes tans gebruik word in die regsdomein in Suider-Afrika. Bestaande instrumente en die aard van hul aanwending word in die tesis omskryf en definieer. 'n Seleksie van kunsmatige intelligensie platforms wat tot die regsberoep se beskikking is word beskryf en vergelyk. Dit sluit platforms soos Rave Law, Deligence, Lexis Nexis, Ross Intelligence, Do Not Pay, Aletras en Lex Machina in. Laastens probeer die tesis om vas te stel tot watter mate sulke platforms in Zimbabwe en Suid-Afrika gebruik word, en of daar in regsfirmas begrip en waardering vir die moontlike voordele van kunsmatige intelligensie is. Die tesis fokus op twee primêre aspekte van die hofproses waarin sulke platforms van diens kan wees, naamlik pre-regsklassifikasie en dokument-ontdekking. Dit word binne die konteks van die hofproses, met inagneming van die stappe wat gevolg word, bestudeer om die kern-elemente te identifiseer. Hierdie benadering is gevolg omdat die prosedures van pre-regsklassifikasie en dokument-ontdekking 'n integrale deel van die standaard hofproses is en sulke prosedurele stappe gevolglik nie in isolasie beskou kan word nie. Die tesis het 'n gemengde metode benadering gebruik om data in te samel vir die uiteindelike bevindinge. Onderhoude is gevoer met sleutel-informante wat bestaan uit ontwerpers van kunsmatige intelligensie platforms en verteenwoordigers van maatskappye wat sulke platforms aan regsfirmas bemark gestuur. Bykomend tot hierdie onderhoude, is ‘n gestruktureerde vraelys aan verteenwoordigers van regsfirmas gestuur om data oor hulle siening van die toepaslikheid van kunsmatige intelligensie in die regswese en huidige stand van die gebruik van sulke stelsels in te samel. Resultate dui in die algemeen op 'n lae opname van kunsmatige intelligensie instrumente in die breëre regswese in Zimbabwe en Suid-Afrika is. Regsfirmas het egter kunsmatige intelligensie tegnologieë begin gebruik om regsdienste te verbeter. Resultate onder prokureurs dui op 'n algemene waardering vir kunsmatige intelligensie algoritmes om regsdienslewering te verbeter. Die resultate toon egter ook dat baie respondente vrees dat kunsmatige intelligensie mense se werk sal wegneem en dat so 'n bedreiging weerstaan moet word. Die tesis sluit af met aanbevelings vir die effektiewe gebruik van kunsmatige intelligensie instrumente in die regte. Daar word voorgestel dat ontwikkelaars voornemende gebruikers beter moet inlig oor die potensiaal van stelsels om sodoende wyer opname aan te moedig. Verder moet die algemene opleiding van gebruikers verbeter word om volle benutting te verseker. Daarbenewens word aanbeveel dat die regsplatforms vir kunsmatige intelligensie op jurisdiksievlak van gemene reg aangepas word om te verseker dat die wet, wat uniek is vir elke jurisdiksie, in 'n aangepaste formaat beskikbaar is sodat dit aan die plaaslike vereistes kan voldoen.
Description
Thesis (MA)--Stellenbosch University, 2021.
Keywords
Confidential business information -- Law and legislation, Machine learning, Artificial Intelligence -- Law and legislation, Data mining, Knowledge discovery in databases, Electronic discovery (Law), Computer discovery (Law), Ross intelligence, Inc., Workflow automation (Workflow management systems), Law firms -- South Africa -- Rules and practice, UCTD
Citation