=Paper=
{{Paper
|id=Vol-2888/paper9
|storemode=property
|title=Utilizing AI to Improve Efficiency of the Environment and Land Court in the Kenyan Judiciary:
Leveraging AI Capabilities in Land Dispute Cases in the Kenyan Environment and Land Court System
|pdfUrl=https://ceur-ws.org/Vol-2888/paper9.pdf
|volume=Vol-2888
|authors=Florence Ogonjo,Joseph Theuri Gitonga,Angeline Wairegi,Isaac Rutenberg
|dblpUrl=https://dblp.org/rec/conf/icail/OgonjoGWR21
}}
==Utilizing AI to Improve Efficiency of the Environment and Land Court in the Kenyan Judiciary:
Leveraging AI Capabilities in Land Dispute Cases in the Kenyan Environment and Land Court System==
https://ceur-ws.org/Vol-2888/paper9.pdf
Utilizing AI to Improve Efficiency of the Environment and Land
Court in the Kenyan Judiciary
Leveraging AI Capabilities in Land Dispute Cases in the Kenyan Environmental and Land Court System
Florence Ogonjo Joseph Theuri Gitonga Dr. Angeline Wairegi†
CIPIT CIPIT CIPIT
Strathmore University Strathmore University Strathmore University
Nairobi, Kenya Nairobi, Kenya Nairobi, Kenya
fogonjo@strathmore.edu jgitonga@strathmore.edu awairegi@strathmore.edu
Dr. Isaac Rutenberg
CIPIT
Strathmore University
Nairobi, Kenya
irutenberg@strathmore.edu
ABSTRACT and poverty that continues to plague the nation [2, 3]. The transition
from pre-colonial communal land ownership to private land
The number of land disputes in Kenya continues to increase with ownership, which started in the colonial period and has continued
population and economic growth. In 2013, the judiciary established in the post-colonial era, produced a number of contradictions in
the Environment and Land Court (ELC) to hear disputes relating to administering and managing land that are present to this day [4]. A
environment and land. Unfortunately, the ELC is plagued with the large number of land policies enacted in the colonial era persisted
same problems affecting Kenya’s other courts; chief amongst these even after the country attained its independence in 1963. As a
is an extensive backlog of cases. Past attempts by the judiciary to result, despite enacting individual tenure of indigenous land and
eliminate this backlog have met with varying degrees of success. In redistributing the fertile lands in the highlands occupied by
this paper, we argue that augmenting human abilities with AI colonialists to its citizens, Kenya is plagued with land conflicts and
technology is a viable means of tackling this case backlog. This its courts inundated with land dispute cases among individuals and
paper outlines AI tools that may aid legal personnel in the ELC in between communities [5].
performing their duties and, ultimately, reducing the number of Changing cultural practices are increasing pressure on the
pending cases. country’s land tenure system as well. For example, the Pokot tribe
in the highlands of Baringo county traditionally practiced semi‐
KEYWORDS nomadic pastoralism; in recent years, however, the community has
Kenyan Judiciary, Environment and Land Court, Artificial adopted a more sedentary lifestyle and taken up rain‐fed agriculture
Intelligence (AI), Legal Research, Transcription, Online Dispute [6]. The transition from common property to private tenure has led
Resolution to increased land disputes within members of the tribe [6]. In the
past, people accessed land and asserted their land rights in 3 ways:
(i) using clan-based definitions of landholding communities, (ii)
1 INTRODUCTION through family-based inheritance, and (iii) from claims to rights
Kenya’s relationship with land can be viewed in pre and post – based on long-term occupancy and use [1]. Tensions between these
colonial terms: a precolonial context of land abundance and relative traditional land administration methods and current land laws are
labor scarcity, and a late colonial and postcolonial situation of also contributing to land disputes in the nation. The Maasai’s
rising populations and growing pressure on land [1]. Colonial land customary land holding, for example, is based on long occupation,
policy in Kenya resulted in inequality in land ownership and use, continuous use, traditional rights, colonial treaty, and the Group
resentment by Africans, landlessness, squatting, land degradation Representatives Land Act adopted in the early years after
independence [7]. In recent years, the tribe’s people are
†
Corresponding author. experiencing dispossession from people making claims to their land
In: Proceedings of the Second International Workshop on AI and Intelligent based on the more formal land laws currently in place [7].
Assistance for Legal Professionals in the Digital Workplace (LegalAIIA 2021),
held in conjunction with ICAIL 2021, June 21, 2021, Sao Paulo, Brazil Gender disparities in land ownership and access to land are
Copyright © 2021 for this paper by its authors. Use permitted under Creative prevalent in Kenya. Women lag behind in securing land rights.
Commons License Attribution 4.0 International (CC BY 4.0).
Published at http://ceur-ws.org Women, particularly those residing in rural areas, are more likely
to be systematically excluded from family and patriarchal land
LegalAIIA’21, June, 2021, Sao Paolo, Brazil F. Ogonjo et al.
ownership – only having access to land through a male relative – influenced by the backlog of land cases in the High Court. Case
leaving them in precarious financial situations [8]. This can lead to backlog - defined as cases that have been pending for more than
land disputes. A 2005 study found that widows in the country are one year - and delays in delivery of justice have been main
13% more likely to experience land conflicts when their parcels are indictments against the Kenyan judiciary.
registered under the names of their deceased husbands than when Underfunding of the judiciary is one of the main reasons for the
titles are registered under their names [9]. increasing case backlog in courts across the country. The entire
Generally, the source of land conflicts can be grouped into 3 judiciary system is regularly subjected to abrupt budget cuts from
categories: (i) competing land claims from agricultural and the government; in fact, the Judiciary’s funding has been on a
urbanization demands as a result of rural – urban migratory patterns downward trend since the 2012 - 2013 fiscal year [20, 21].
[10], (ii) conflict between the elite and ordinary citizens in terms of Budgetary constraints mean that the judiciary is consistently
land distribution, natural resource extraction and unbalanced rent operating with less than the required workforce (55% of the
sharing [11, 12, 13, 14, 15], and (iii) land grabbing using political required workforce in the 2019 – 2020 fiscal year [21]) which
or civil machinations [14, 16, 17, 18]. The number of disputes over inevitably results in an increase in the number of pending cases. For
land continue to increase with population and economic growth. As example, in the 2016 – 2017 fiscal year there were 499,341 pending
family patriarchs that acquired land in the early Independence era cases, and this number increased to 617,582 by 2019 – 2020 [20,
pass there is an increase in land inheritance disputes which also 21]. Other factors that contribute to the backlog include: poor
contributes to rising land conflicts. physical infrastructure – there has been minimal progress in the
Prior to 2010, Kenya did not have a comprehensive system of completion of court construction across the country; lack of ICT
land laws, particularly those pertaining to women’s land rights. In capacity to assist with core judicial processes; judicial
2010, it adopted a new constitution that allowed for the organizational structure; court rules and procedures; and manual
implementation of the National Land Policy through institutions management of court records [20, 22].
such as the National Land Commission Act (NLC). The It is worth noting that the judiciary is actively working on
formulation of a comprehensive National Land Policy commenced reducing case backlog. In the 2018 – 2019 fiscal year, under Chief
in February 2004 and was completed in 2009. The National Land Justice David Kenani Maraga, the judiciary significantly reduced
Policy was commissioned by the government to tackle issues of the number of cases pending in the court system - bring down cases
squatting, landlessness, disinheritance of some groups and that are five years old from 110,000 to only 15,278 cases [23]. The
individuals, urban squalor, under-utilization and abandonment of issue of case backlog is a perennial headache for the judiciary,
agricultural land, deterioration in land quality, tenure insecurity, though, with Chief Justice Maraga noting that the number of cases
and conflict [8]. The National Land Policy recommended the filed in Kenyan courts every year exceeds the number of cases the
creation of mechanisms to ensure access to timely, efficient and judiciary settles by as much as 100,000, causing an ever-growing
affordable dispute resolution to land conflicts. This led to the backlog [24].
establishment of the Environment and Land Court. The ELC has one of the highest number of pending cases,
Following promulgation of the 2010 constitution, an 13,630 cases for the 2019 – 2020 fiscal year, across all counties
Environment and Land Court Act was approved in 2011 under despite an impressive case clearance rate [21]. Of the 13,630 cases,
which a new Environment and Land Court (ELC) was created as a 21%, 2920 cases, have been in the court system for greater than 5
specialized court. Currently, 29 of the country’s 47 counties have years, 34%, 4628 cases, are aged between 3 – 5 years, and 45%,
an ELC. The Environment and Land Court is a Superior Court with 6082 cases, have been pending for 1 – 3 years [21]. Most of the
the same status as the High Court of Kenya. It has jurisdiction to disputes in the ELC are family disagreements over land and fraud
hear disputes relating to environment and land. Specifically, the related cases, 29%; succession cases account for 20%, boundary
court has the power to: (i) hear disputes relating to land disputes, 15%, and double registration and double allocation
administration and management, (ii) hear cases relating to public, accounted for 10% and 9% of the cases, respectively [2]. The
private and community land and contracts, (iii) hear cases relating impact of these protracted legal proceedings is devastating to the
to environmental planning and protection (iv) exercise appellate parties involved in the disputes.
jurisdiction over the decisions of subordinate courts or local
tribunals, and (v) exercise supervisory jurisdiction over the
subordinate courts, local tribunals, persons or authorities [19]. The
ELC began its operations in 2013. The majority of the cases
handled by ELC relate to land disputes rather than environmental
matters.
2 CURRENT PERFORMANCE OF THE
ENVIRONMENT AND LAND COURT
Unfortunately, the ELC is plagued with many of the same problems
affecting Kenyan courts; chief amongst these is an extensive back Figure 1: The total number of pending cases over a year old
log of cases. Ironically, establishment of the ELC was largely across the Kenyan judiciary system as reported in the State of
Utilizing AI to Improve Efficiency of the Environment and Land
LegalAIIA’21, June, 2021, Sao Paolo, Brazil
Court in the Kenyan Judiciary
the Judiciary and the Administration of Justice Annual Report
2019 – 2020 [21].
In order to accurately assess the current performance of the
ELC this study evaluated the total number of pending cases and
their average age in all 29 ELC county stations. It also examined
the average age of cases in terms of those that were ultimately
dismissed and those allowed to proceed through the court. This data
was obtained by analyzing court fillings in the Environment and
Land Court posted on the Kenya Law online website, the official
account of the Kenyan judiciary. A computational search of the
court case meta-data was performed and the relevant data compiled.
Between 2002 – 2020 the number of land cases filed in
Environment and Land Courts increased significantly. The
distribution of the number of cases filed each year is shown in
Figure. 2. The significant decrease in the number of cases in 2020
was due to a lack of availability in the court’s calendar, i.e., the case
backlog prevented parties from scheduling new hearings in the
ELC. Chief Justice David Maraga announced in January 23, 2020
that the Environment and Land Courts are fully booked until March
2021, and called for urgent measures to fund the Judiciary’s bid to
employ more judges and magistrates to deal with the case backlog
[25].
Figure 3: A mapping of the number of pending land cases filed
in Environment and Land Courts in counties across Kenya.
The highest caseloads are in Nairobi, Nakuru and Meru
counties, with 18%, 7% and 7% of the 14,686 total pending
cases, respectively.
The average age of these cases is 3 years. The highest average
durations from filing to judgement are in Meru county, 4.5 years,
Machakos county, 4.3 years and Bungoma county, 3.8 years.
Figure. 4 outlines the average duration of cases in the ELC system
in counties across the country.
It is clear that the current court system is ill equipped to deal
with the demand of cases. In the following section, we argue that
AI tools could be used to significantly decrease, or eliminate, the
Figure 2: The total number of land cases filed in Environment
backlog of cases. We outline the different AI tools that the Kenyan
and Land Courts in 29 counties for the 2002 -2020 period. The
Judiciary should introduce to the ELC to aid the legal workforce to
cases between 2002 – 2012 are land cases carried over to the
efficiently perform their duties and, ultimately, tackle the large
ELC from the High Court.
number of pending cases.
There are a total of 14,686 pending land cases. The distribution
3 UTILIZING AI IN THE ENVIRONMENT AND
of cases across the country is shown in Figure. 3. A total of 127
LAND COURT
judges are assigned to these cases, equating to an average of 115
The use of AI in legal proceedings is not as prevalent in Africa as
pending cases per judge.
it is in the USA or Europe. A few African firms - Bowman, with
offices in Nairobi, Kenya; Webber–Wetzel, headquartered in
Johannesburg, South Africa, and KTA Advocates (formerly
Karuhanga, Tabaro & Associates) in Uganda, for instance - have
adopted AI to improve their legal services delivery; streamlining
the mundane, time consuming tasks through the use of AI systems
and freeing up their lawyers’ time to focus on high level tasks [26].
LegalAIIA’21, June, 2021, Sao Paolo, Brazil F. Ogonjo et al.
and (iv) lack of funding and labor to augment legal proceedings
with AI technology. This paper argues that AI holds great potential
in increasing the efficiency of the Kenyan courts thereby reducing
the current and future case backlog.
3.1 AI in Legal Research for Land Dispute Cases
The Kenyan legal system, like many globally, is based on
precedent - judges make rulings consistent with prior cases on the
same subject. Judges must therefore identify and retrieve
information from relevant cases to support their decision-making.
The high number, and high complexity, of cases that judges must
sift through makes this aspect of their job highly time consuming
and contributes to the length of a trial. AI tools that aid with legal
research would ease this aspect of judges’ workload.
AI legal research platforms are computer software systems that
not only perform pre – programmed tasks but have the ability to
learn and refine their searches and outputs. Machine learning (ML)
and Natural Language Processing (NLP) may offer affordable ways
to obtain precise and relevant legal research results [34, 35, 36, 37].
Some of the commercially available AI legal research platforms use
natural language processing to search and process data using pre-
defined parameters. NLP uses prior users’ queries and results to
form a predictive model, expanding or narrowing a search to ensure
all relevant cases are identified. The efficacy of these tools is
Figure 4: A mapping of the average age of land cases filed in
documented. A 2018 study, for example, found that attorneys who
ELC in counties across Kenya. The average age for pending
used AI tools to conduct legal research completed projects 24.5%
cases in the ELC system country-wide is 3 years.
faster and the search results were 21% more relevant; the study
concluded that use of AI would save attorneys 132 – 210 hours a
LawPavillion, a Nigerian legal technology company, launched an
year when conducting legal research [38].
AI platform in 2016, LawPavillionPrime, that gives in-depth
The cost reduction potential of these AI legal research
analysis of the strengths and weaknesses of legal positions and
platforms should also motivate the ELC to integrate them to the
authorities by generating statistical analysis, historical data,
current adjudicating process. Understanding the exact fiscal impact
precedential value ratings, conflicting judgments, locus classicus,
of AI solutions in the ELC before implementation, however, is
statutory or literary authorities, and opinions [27]. This was the first
difficult. The cost of software, implementation, training and
such platform launched on the continent. In 2018, it released TIMI,
staffing comparative to current processing and personnel cost may
Nigeria’s first artificial intelligence legal assistant, which assists
not incentivize utilization of these AI systems if it is prohibitively
lawyers with legal research, litigation, opinion drafting, provides
higher. The previous upgrade to provide internet and Wi-Fi access
notes with legal authorities, and gives a step-by-step guide on
in 90% of the courts cost KSH 40 Million (£300,000) and stalled
drafting and filing court processes [28].
shortly after surpassing that sum due to lack of funds [39]. If the
In general, however, law offices and courts on the continent
cost of deploying AI legal research platforms is similar than the
have been slow to embrace technology. In 2018, for example, the
same problem may arise. Fortunately, there are several AI legal
Law Society of Kenya (LSK) went to court to oppose a decision by
research platforms, also known as ‘Due Diligence’ platforms
the Ministry of Lands and Physical Planning to digitize the land
currently on the market: Kira Systems, Leverton, eBrevia, Ross
transactions processes at the land registry through the National
Intelligence, CaseText, WhatSun, TIMI, and many more, at varying
Land Information Management System (NLIMS), arguing that the
price points depending on the functionality and tools available.
ministry had failed to consult the relevant stakeholders as required
Subscriptions can be as low as $59 per month.
[29, 30, 31]. The government argues that digitizing land registration
Effective deployment of these tools will also require extensive
documents will root out corruption in land transactions while the
personnel and algorithm training. The cost of both of these training
LSK argues that done without appropriate legislation, digitization
is likely to vary. However, these initial costs are likely to be offset
is likely to increase corruption in land management [32].
in the long term by a reduction in the personnel required to operate
Furthermore, it is only in recent years that digital signatures and
the ELC efficiently. The hiring practices in the ELC will need to be
service of pleadings via email have taken root in the country [33].
drastically altered if these tools are adopted. There will be no need
Currently, AI is not utilized in the Kenyan judicial system in a
to recruit armies of young lawyers to perform services that are no
substantive manner. There are several reasons for this: (i) poor
longer needed, instead the ELC will need to hire a smaller number
digital infrastructure and data capacity, (ii) under-digitization of
of legal personnel adept at utilizing AI legal research platforms.
records, (iii) tradition-bound court systems and legal professionals,
Utilizing AI to Improve Efficiency of the Environment and Land
LegalAIIA’21, June, 2021, Sao Paolo, Brazil
Court in the Kenyan Judiciary
These platforms are only as strong as the data they have access corporations are hesitant to invest in digital infrastructure in these
to. Access to comprehensive, robust case data increases the rural communities. In order to provide digital infrastructure capable
efficiency and accuracy of AI platform searches. Opportunely, in of supporting all technologies, the Kenyan government and private
2017, the Kenyan judiciary unveiled its digital strategy, enshrined industries may have to work together. The government may
in the 2017-2021 Sustaining the Judiciary Transformation subsidize some of the costs of construction incentivizing private
Blueprint, to re-engineer its processes through information and industries to provide better digital services in rural areas.
communications technology (ICT) [40]. Part of the strategy Alternatively, both parties can opt to share the infrastructure to cut
outlined is the digitization of court records and proceedings, down cost.
retiring archaic filing systems and modernizing document
management [40]. According to the Ministry of ICT, 60 million 3.2 AI for Speech Recognition and Transcription in ELC
records were digitized under the High Court Registry pilot The official records of courtroom proceedings are vital in the
digitization project [41]. There are minimal reports on the progress justice system. Legal transcription is therefore a vital component of
of the digitization project in other courts. Digitization of these the adjudication process. Court transcripts influence, “…the
records will make the use of AI to conduct legal research a viable conduct of the trial, whether by court alone or by court and jury;
strategy. the relationships between the trial judge and participating counsel;
Access to land records is necessary for effective deployment of the procedures for review of the trial by the trial judge; and
these platforms. This means that complete digitization of land appellate review, including the feasibility of seeking such review
records in the country is required. In April 2021, the government and the nature, scope and potential achievements thereof” [46].
launched a new National Land Information Management System Unfortunately, underfunding of the judiciary affects the number of
(NLIMS), a digital land resource management platform named available court transcriptionists. This shortage of transcriptionists
Ardhisasa; another step in the government’s goal to digitize land has left many courts on their own when it comes to obtaining
records and transactions [42]. The phased roll out of the Ardhisasa accurate transcripts of courtroom events. Many court proceedings
platform started in Nairobi (where digitalization of all services is in Kenya exist only as audio recordings. In 2019, the Judiciary and
complete), with another twenty counties to be on-boarded to the the Ministry of Information vowed to digitize all audio court
digital system by the end 2021. The platform is expected to be proceedings using the Ajira Digital Program, while employing
available across the country by the end of 2022 – a goal that falls youth to perform the transcription [47]. This is a worthwhile but
short of the 2021 completion date of digitization of land records set slow endeavor. During the COVID-19 pandemic, many Kenyan
by the government in 2019. A partial digitization of these records courts were forced to adopt real – time transcript devices. Data
would invariably affect the efficacy of the AI legal research tools. regarding how many, if any, Environment and Land Courts adopted
Digitization of land services is likely to be more cost effective these devices could not be found.
as well. In 2009, the average cost of managing the manual land AI can reduce case backlog at the ELC by filling in the gaps
system was KSH 1,770.00 per file documents; it cost KSH caused by the shortage of court transcriptionists. AI coupled with
10,621.00 on average to trace a misfiled or missing documents and automatic speech recognition (ASR) allows for proceedings to be
KSH 19,473.00 to reproduce a lost file or document in the land recorded, processed, and transcribed faster than using traditional
registry [43]. These costs were significantly lower in developing court transcriptionists. Generally, ASR in targeted applications
countries that had fully digitized their operations [43]. (e.g., legal or medical transcriptions) tends to have lower accuracy
It should be noted that the country’s poor digital infrastructure, than in general purpose applications (e.g., regular speech, internet
i.e., lack of internet access, poor internet connectivity, and cost search engines) [48]. However, automated speech recognition
prohibitive internet, may hamper the use of these AI platforms in (ASR) technology combined with AI improves speech-to-text
Environment and Land Courts located in rural counties. There is an engines increasing their ability and allowing them to transcribe
ongoing push by the Ministry of ICT to improve access to high- jargon-heavy legal proceedings highly accurately [49]. In general,
speed internet in rural locations [44]. However, there are number of the most effective application of these AI transcription tools
obstacles hindering this goal. First, rural communities often lack augment the automated process with human oversight; the
reliable electricity which makes it harder for technology companies automatically produced transcripts are reviewed and edited by
to set up internet networks. The quality of available digital professional transcribers to ensure the highest level of accuracy
infrastructure is also cause for concern. For example, only 57% of [49]. This would be especially critical in this context since ASR is
the population receives 4G coverage in Kenya, and the majority of less accurate when dealing with accented speech [48, 50].
places not covered are rural [45]; as a result, even the simplest Corrections or enhancements are fed back to the ASR via adaptive
technologies often don’t work as expected in these areas. Finally, algorithms, allowing the technology to constantly improve [49]. A
the depressed income of many residents in the rural areas mean review of a transcript should take much less time than manually
competing basic needs often impact the ability to access digital transcribing audio recording of court proceedings.
services. Perversely, the cost of offering internet services is often Additionally, AI transcription service systems provide high
higher in rural areas due to greater costs in building, servicing and searchable features, allowing for targeted data to be easily
even fueling those networks [45]. As a result of lower demand, identified using relevant keywords and dispersed files to be
LegalAIIA’21, June, 2021, Sao Paolo, Brazil F. Ogonjo et al.
consolidated in the form of an organized digital database [51]. This dismissed were pending for a longer duration in most of the
would further streamline case management flow in the ELC and counties surveyed.
mitigate case backlog.
Funding is both an obstacle and motivation in deploying AI Predicting judicial matters is an ongoing and longstanding
transcription platforms in the ELC. In the USA, the most commonly preoccupation in legal circles that continues to be an open issue in
recommended AI services cost around 25¢ per minute of audio, and both the theory practice of the law [54, 55, 56, 57, 58]. In recent
services employing human transcriptionists cost up to $2 for a years, AI based approaches have been increasingly utilized for legal
minute of clear audio [52]. One transcription service operating in predictive analysis. AI can be used to identify patterns in a judges’
Kenya offers rates of $1.00 per minute for legal transcription with rulings, allowing lawyers and other legal professionals to predict
5 - day delivery [53]. Therefore, in addition to increasing the speed how the court may rule. Algorithms and machine-learning can
of the transcription process, use of AI transcription platforms would interpret data and predict a logical outcome for a case before filling.
save the perennially underfunded ELC money. It is worth noting Environment and Land Courts publish case details including
that during the 2019 fiscal year, the Directorate of the ICT judgements online making big data analysis possible.
developed specifications for the procurement of a speech to text Researchers in the United States were the first to determine
software system, however, the procurement process was halted due whether machine learning techniques could be used to predict
to lack of funds [21]. The judiciary will have to overcome this short courts’ decisions or the voting behavior of judges [59, 60]. Katz
term funding obstacle to enjoy the long term cost savings from et al. developed a prediction model that aims to predict whether the
utilization of the AI transcription platforms. US Supreme Court as a whole affirms or reverses the status quo
AI transcription service systems also provide high searchable judgement, and whether each individual Justice of the Supreme
features, allowing for targeted data to be easily identified using Court will vote to affirm or reverse the status quo judgement; the
relevant keywords and dispersed files to be consolidated in the form model achieved an accuracy of 70.2% at the case outcome level and
of an organized digital database [51]. This would further streamline 71.9% at the justice vote level [61]. Medvedeva et. al. found that
case management flow in the ELC and mitigate case backlog. Natural Language Processing techniques could predict (future)
judicial decisions in the European Court of Human Rights with an
3.3 Predictive Analysis on Case Duration and Dismissals average accuracy of 75% [62]. The study used a computer to
One of the most frustrating aspects of the prolonged adjudication perform quantitative analysis on words and phrases used in a court
process in the ELC is that it is just as likely to result in a case case and then based on that analysis trained the computer to predict
dismissal as it is to result in a ruling in favor or against the the decision of the Court [62]. It is feasible that similar approaches
aggrieved party. In fact, in the survey of ELC done in this study, may be used to predict whether a case may or may not be dismissed
the cases that were ultimately dismissed were in the courts longer by the ELC. This approach is likely to reduce the number of land
than those that resulted in a judgement for or against one of the dispute cases filed in the ELC – a prediction of dismissal may force
parties. the aggrieved parties to seek alternate dispute resolutions. The
ethical ramifications of this type of predictive analysis would need
to be taken into account, however. There are concerns that the use
of this sophisticated AI prediction models may only be accessible
to wealthy litigants, leaving those that cannot afford them in a less
powerful position of legal armament [63]. Issues of AI bias are well
documented [64]; pro-active measures will need to be implemented
to identify any bias present in the predictive AI platforms.
Predictive analytics may also be used to predict the duration of
a court case [65]. This would allow courts to give priority to cases
that are predicted to consume less processing time in order to
reduce the average total time in adjudicating cases on the docket.
Knowledge on the duration of a case might also quell litigants’
desire to submit cases to the ELC, instead seeking alternate routes
of dispute resolution.
3.4 Online Dispute Resolution
There are 3 reasons that the Kenyan judiciary should embrace
online courts as platforms for providing justice. First, some of the
farthest regions of the country, largely rural areas, still do not have
Figure 5: The average age of cases in ELC in various counties physical court buildings, which means that advocates and witnesses
in 2 categories: cases that are ultimately dismissed and those travel long distances in search of justice [66]. In fact, Environment
that are heard by the court. In general, cases that were and Land Courts are only present in 29 counties in the country.
Second, in instances where legal representation is cost prohibitive,
Utilizing AI to Improve Efficiency of the Environment and Land
LegalAIIA’21, June, 2021, Sao Paolo, Brazil
Court in the Kenyan Judiciary
litigants may use these online courts and represent themselves. new platforms of justice introduced by the judiciary. In the coming
Finally, online courts may expedite adjudication of a case by years, with greater exposure, familiarity and uptake, ODR may
eliminating the need of legal counsel or judges for hearings by fully become the commonly chosen, if not the default option, of
automating the legal process or requiring human input only in the arbitration in the ELC. This is especially likely given the sluggish
‘ruling’ portion of the proceedings. In this case, Online Dispute pace of construction of ELC courts across the country and the
Resolution (ODR) utilizing online courts would provide means of staggering distances that parties in more remote locales must travel
settling land disputes via a hearing using technology but outside of for in – person hearings.
the courtroom. There are several such AI platforms in use. ODR
platforms such as Rechtwijzer, MyLaw BC, and the British 5 CONCLUSION
Columbia Civil Resolution Tribunal, utilize AI to determine which Kenya’s judiciary is stuck in a perennial battle against an ever
cases may be adjudicated using the platform, and to automate increasing case backlog. Despite small successes in recent years in
decision-making and settlement or outcome proposal [67]. Similar reducing the number of cases pending in the court system, it is clear
platforms could be deployed by the Kenyan judiciary system. By that human efforts alone are not sufficient to tackle this problem.
mining data from prior related court cases and decisions these AI offers a great opportunity for the judiciary to achieve its service
platforms could autonomously decide settlement options or fair delivery goals. The problems caused by insufficient funding and
workforce could be mitigated by utilizing AI tools.
adjudication. Judges could review the platform’s decision to ensure
In this paper we introduce 4 ways that AI may be used to ease
it is just. AI could help parties reach an equitable settlement in land the pressure on the Environment and Land Courts; emphasizing
disputes. that augmenting these tools to existing human abilities would be
The issue of digital literacy, especially in rural counties, must the best way of leveraging both AI and human abilities. While the
be considered and addressed for the government to effectively country’s poor digital infrastructure and data capacity does create
utilize ODR platforms across the country. The number of people in obstacles in deploying these AI tools, we believe that these are not
the country who are able to effectively use digital technologies is insurmountable and that the strategies outlined in this paper are the
still low; only 25% of the population are mobile internet users best way forward.
according to a 2019 study compared to 95% of the population in
the USA in the same year [68].The absence of networks in many REFERENCES
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