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Chandra et al., International Journal on Emerging Technologies 11(3): 344-350(2020) 344
International Journal on Emerging Technologies 11(3): 344-350(2020)
ISSN No. (Print): 0975-8364
ISSN No. (Online): 2249-3255
Role of Artificial Intelligence in Transforming the Justice Delivery System
in COVID 19 Pandemic
Geetanjali Chandra1, Ruchika Gupta2 and Nidhi Agarwal3
1Associate Professor, Amity Law School, Amity University Dubai, UAE.
2Professor, Amity Business School, Amity University Greater Noida (Uttar Pradesh), India.
3Principal, Integrated School of Education, INMANTEC, Ghaziabad (Uttar Pradesh), India.
(Corresponding author: Ruchika Gupta)
(Received 22 February 2020, Revised 18 April 2020, Accepted 20 April 2020)
(Published by Research Trend, Website: www.researchtrend.net)
ABSTRACT: Artificial intelligence is programmed on computers to depict human intelligence. It has created
a huge hype and has evolved to revolutionize almost every profession including legal sector. New lawful
simulated AI programming software like Ross intelligence and Catalyst along with Machine Learning and
Natural Language Processing give viable fight goals, better legitimate clearness, and better permission to
justice and new difficulties to ordinary law firms offering legal assistance utilizing leveraged cohort correlate
model. Also, AI enabled lawyer bots are performing tasks that normally requires human intellect and needs
to be performed by lawyers. In such a situation, a question strikes- Will these lawyer bots replace human
lawyers? This question becomes all the more important in the present scenario when the whole globe is
facing challenges imposed by global pandemic “Covid 19”. How is COVID-19 going to change the justice
delivery system, and what does it look like? Therefore, this study is conducted to evaluate the role of
artificial intelligence in transforming the justice delivery system post Covid-19. The study tries to examine
the various areas in which AI is affecting the legal profession, evaluate the extent of its impact on the legal
employment, assess the tasks in legal sector which cannot be undertaken by AI, and discuss the legal issues
in the implementation of AI. The study also suggests the way forward with regards to the future of legal
sector to help practitioners and researchers.
Keywords: Artificial Intelligence, COVID-19, Lawyers, Legal Sector, Machine Learning, Natural language
Processing, Justice system & dispensation.
Abbreviations: AI, artificial intelligence.
I. INTRODUCTION
At whatever point another innovation is acquainted with
the World, each part and industry are offered the
likelihood to receive that to upgrade their tasks. One
model is of PCs and how they immediately developed
being used, taking over a large number of the manual
desk work, and how they have become basic today in
pretty much every office and calling. Law firms are no
exemption to that, where innovation has consistently
been bleeding edge and discovers its way into
supporting the lawyers, paralegals, specialists and
customers the same which are related with the calling
[2-5].
Artificial Intelligence or AI is headed to changing the
legitimate calling in different manners, helping Law firms
deal with their activities just as enlarging and decreasing
a large number of the errands that were recently
depended upon people to do, sparing valuable time and
labor that can be in any case utilized for increasingly
beneficial undertakings [6, 8, 10, 12].
However, many predicted during the industrial revolution
that automation would lead to mass unemployment in
industries dependent on manual labor. Developing more
advanced robots and artificial intelligence leads to a
similar debate and only now are intelligent jobs at risk.
This also includes justice delivery system occupations,
such as lawyers and judges [13, 15].
Furthermore, the current global pandemic COVID-19
has brought transformation in all spheres of life and
have totally reshaped the way we used to work earlier.
Law has tirelessly clung to conventional methods for
getting things done. Significantly after the worldwide
money related emergency, the law firms balanced at the
edges—vacations, diminished rack rates, and interior
cost-cutting measures. This time thing will be unique;
the progressions will be wide, profound, and
persevering. The coronavirus has turbocharged law's
transition to a virtual workforce so as to keep up social
distancing. The all-round strengthened dividers of
opposition have been penetrated with stunning velocity.
Justice delivery system has not, obviously, had the
opportunity to process this, however it has exhibited that
it can, when pushed, adjust dug in strategies for
teaching and conveying administrations [19, 17, 28].
A judicial system powered by artificial intelligence (AI)
will ensure that nothing hangs during the COVID 19
pandemic. That could be a major obstacle in the justice
delivery system for victims' access to justice and in
protecting the interests of the convicted. In light of the
COVID 19 pandemic, the Chief Justices of various legal
systems have provided instructions to the trial courts
requiring immediate orders to modify or cancel court
operations. In addition to these steps, the modern
Artificial Intelligence technology may be beneficial
during these days, and can be used to ensure access to
justice such as social media, where possible.
Telephonic arguments or lawyers may appear remotely
through video [38].
e
t
Chandra et al., International Journal on Emerging Technologies 11(3): 344-350(2020) 345
Basically, law is based on two important aspects:
predictability and precedence. Artificial Intelligence can
greatly help align these processes and provide high
quality analytical data, while also assisting the legal
sector in a number of other areas, particularly in
reducing the amount of time spent over monotonous
process of reviewing and managing legal documents. AI
enables lawyers to invest time in more critical activities
like advising clients, preparing to appear in court and
negotiating deals. The impact of technology on the legal
sector is not new, the evolution of the internet, emails
and legal databases online have been there for quite a
time now [22, 25, 27]. What is interesting is the extent to
which Artificial Intelligence is thought to be a threat to
displacing the lawyers. Therefore, the objectives of this
paper are:
– To examine the various areas in which AI is affecting
the legal profession
– To evaluate the extent of its impact on the legal
employment
– To assess the tasks in legal sector which cannot be
undertaken by AI
– To discuss the legal issues in the implementation of AI
– To suggest the way forward with regards to the future
of legal sector post COVID-19.
II. LITERATURE REVIEW
“The science and engineering of making intelligent
machines, especially intelligent computer programs.”
John McCarthy
Defining AI: The term “Artificial Intelligence”, or AI, has
been coined since 1950s by the father of AI, John
McCarthy. During the era, there was a period of
declining funding and research interest around artificial
intelligence, called the “AI winter” [27]. Ever since then,
AI has created a huge hype and has evolved to
revolutionize almost every aspect of our life. Simply put,
artificial intelligence is programmed on computers to
depict human intelligence. The software is programmed
over mathematical operations using vector graphs.
These algorithms enable computers to learn and train
itself from data and experiences, called Machine
Learning. Through neural networks, AI is able to
produce predictive models used for image and sound
recognition, autonomous cars and virtual agents [21, 29,
30]. AI is widely classified into two: weak and strong.
– Weak & Deep AI: It is also referred to as rules
engines, knowledge graphs, expert
systems, or symbolic AI. This AI was usually referred to
as Weak AI, which was required only to perform a
certain set of tasks.
– Strong AI: It is a self-improving AI which understands
itself well enough. Artificial General Intelligence (AGI),
which has cross-domain capabilities (like humans), can
benefit from a range of (like humans) experiences [7].
“Weak” AI as a rule alludes to that it has no
mindfulness. “Strong” or “Deep” as a rule alludes to
what is commonly called ‘Artificial General Intelligence’
which would imply that the AI made would coordinate or
surpass that human knowledge which incorporates the
aptitudes to join the capacity to reason, plan, learn,
convey and incorporate these towards a shared
objective for the accomplishment of a specific
assignment [31].
AI contains propelled calculations that follow a scientific
capacity, which can deal with higher procedures like
people. Examples include:
– Machine learning, - deep learning, predictive analytics
– NLP – translation, classification, info extraction
– Expert systems, robotics, neural networks, algorithm,
data mining, big data, pattern & image recognition,
automation, problem solving.
Judiciary System: Every single human choice is
vulnerable to partiality and every judicial system
experience the ill effects of oblivious inclination, in spite
of good motives. Algorithms that can disregard factors
that don't legitimately bear on singular cases, for
example, sexual orientation and race, could evacuate a
portion of those failings. One of the most significant
contemplations for judges is whether to give bail and to
what extent jail sentences ought to be. These choices
are generally directed by the probability of reoffending.
Algorithms are currently ready to settle on such choices
by giving a proof based examination of the dangers, as
opposed to depending on the abstract dynamic of
individual appointed authorities. In spite of these
conspicuous points of interest, it is a long way from
clear who might give oversight of the AI and check their
choices are not defective. Also, increasingly wary
eyewitnesses caution that AIs may take in and emulate
inclination from their human creators or the information
they have been trained with [23, 39, 35].
Legal Dimension of COVID: COVID-19 influenced all
three State bodies, the Senate, the Executive and the
Judiciary. It has disrupted supply chains, leading to the
closure of several manufacturing facilities worldwide;
serious disruption of air and sea traffic and the closure
of vital air routes, such as the one between the United
States and Europe. This turn has led to the collapse of
worldwide stock markets leading to the loss of billions of
dollars, which was wiped out in a matter of days. A
convergence of all these causes has led to a fall in the
total level of global economic activity and has pushed
the world economy into a potential recession [36, 39].
Torchbearers of AI in Law: A polymath, distributed
'Dissertatio de arte combinatoria' (On the Combinatorial
Craftsmanship) in 1666 in which he imagined his
trademark universalis, i.e. a universal language that
would be beer to lessen enlargement to computations.
This thought should be the main driver of the
improvement of Artificial Intelligence throughout the
hundreds of years. Leibniz is viewed as one of the
granddads of AI and in his different speculations of
Philosophy of Mind he claimed that delivered the
possibility of AI by method for consolidating science with
thinking. He said, "The best way to address our thinking
is to cause them as unmistakable as the
mathematicians' with the goal that we to can discover
our blunder initially, and when there are differences
between individuals, how about we figure and see who
is correct!"
The application of legal informatics to AI has been the
fundamental reason behind the possibility of using AI in
law. Lee Loevinger, Layman E. Allen, L. Mehl after Bruce
G. Buchanan and Thomas E. Headrick were
torchbearers of various ideas that led to the application
of AI in law [31, 32, 33].
Chandra et al., International Journal on Emerging Technologies 11(3): 344-350(2020) 346
III. HOW AI IS TRANSFORMING LAW FIRMS AND
THE LEGAL SECTOR
As per Meng Jianzhu, former Head of Legal and
Political affairs at the Chinese Communist Party,
Artificial Intelligence have a high capability to improve
accuracy, predictability and efficiency of the legal sector
with precision and speed unmatchable by humans [35].
Law is based on two important aspects: predictability
and precedence. Artificial Intelligence can greatly help
align these processes and provide high quality analytical
data, while also assisting the legal sector in a number of
other areas, particularly in reducing the amount of time
spent over monotonous process of reviewing and
managing legal documents. AI enables lawyers to invest
time in more critical activities like advising clients,
preparing to appear in court and negotiating deals [9].
The effect of technology on the legal sector is not
recent, the advancement of the internet, emails and
electronic legal databases has been around for quite
some time now. What is interesting is the extent to
which Machine learning is thought to be a threat to
displacing the lawyers. In this section, we examine the
various areas in which AI is affecting the legal
profession, and the extent of its impact on the legal
employment [14, 21].
It started out as a way to understand natural intelligence
through the construction of artificial agents and this has
by now generated a wealth of methods and techniques
for adding intelligence to information systems. Some of
these techniques are associated with knowledge-
oriented intelligence: reasoning, knowledge
representation, (precision) language processing,
symbolic machine learning, whereas others are related
to behavior-based or data-oriented processing such as
adaptive control, neural networks, data-oriented
machine learning, statistical NLP. Knowledge-oriented
intelligence is associated with conscious human
intelligence whereas data-oriented intelligence is
associated with subconscious mental activity [35].
– Precedent: Precedent, in law, a judgment or choice of
a court that is referred to in a resulting contest for
instance or relationship to legitimize choosing a
comparable case or purpose of law in the equivalent
manner. A significant hidden incentive in the Dutch
legitimate system is lawful certainty. It holds that the
activities of the government ought to be unsurprising. In
any case, this doesn't imply that judges consistently
need to stick to the specific stated purpose of the law. In
some cases, lawmakers purposefully leave space for
understanding or even permit judges to ignore the
stated aim of the law so as to guarantee a sensible and
fair result [23].
– Prediction: Specialists from the UK have attempted
to foresee choices by the ECHR (European Court of
Human Rights) by utilizing common language handling
and AI. The forecasts accomplished a 79 percent
exactness rate in anticipating whether there would be a
human rights infringement. The technique for examining
content to make expectations appears to be successful,
however the scientists didn't plan to structure a system
that can completely assume control over the appointed
authority's activity [4, 23].
AI used in the justice delivery system is yet considered
to be the “weak” (or “shallow”) (or narrow) AI on grounds
that it has no self-awareness. Several examples of the
application of AI are given:
Table 1: Application and Examples of AI in Legal Sector.
Legal application Description Example
Document Drafting Drafting contracts, form filling using chatbots LegalZoom
LISA
Contract Review &
Management
Identify issues/risks
Provide standard clauses when drafting
COIN
Kira Systems
LawGeeks
Leverton
KM Standards
Document Management Storing & easy retrieval, auto template creation & scanning
docs using OCR Docubot by 1 Law
E-Discovery/ Document
Review
Search for necessary (other) facts from internet for analysis &
decision. Use keywords. Predictive coding EVA
Due Diligence Review background inf ormation and prior cases
Highlight and classify essential clauses
Kira Systems
Legal Research Find arguments and reasoning reported in the past for
assessing similar arguments
Ross Intelligence
FastCase
Thomson Reuters- W estlaw
Smart Contract provides an easy way to reference and trigger an Ethereum-
based smart contract to manage contractual promises. OpenLaw
IV. TASKS IN LEGAL SECTOR WHICH CANNOT BE
UNDERTAKEN BY AI
As indicated by Yuen Thio, AI can't yet recreate support,
exchange, or organizing of complex arrangements. The
New York Times proposed that undertakings like
prompting customers, composing briefs, arranging
arrangements, and showing up in court were past the
scope of computerization, in any event for some time. AI
likewise isn't yet generally excellent at the sort of
experimental writing in an Incomparable Court brief
or then again a film content [11, 13]. Some of the tasks
which cannot be undertaken by AI and needs lawyers
are given:
– In the event that, after some time, the appointed
authority settles on various choices when confronted with
a similar case attributes, the AI model won't fit the
information and it will have constrained prescient force
(as befits an unusual adjudicator). What's more, the
model's prescient capacity is limited to cases that are
Chandra et al., International Journal on Emerging Technologies 11(3): 344-350(2020) 347
commonly like the judges' past cases on which the
model was assessed. On the off chance that the past
cases all included female plaintiffs, the model may not
effectively foresee the appointed authority's choice on
the off chance that with a male plaintiff.
– All the more by and large, AI models—evaluated
factual models—experience issues preparing
possibilities that lie outside the information on which they
were trained.
– There are, at long last, a noteworthy number of lawful
undertakings that are too perplexing to be in any way
demonstrated by any arrangement of directions (at any
rate right now). Unscripted human cooperation falls into
this class since it frequently relies upon planning
reactions to unforeseen inquiries and proclamations.
This requires perceiving the more extensive setting
where words are being utilized—the encompassing
words yet the character and inspiration of the speaker
and the reason for the correspondence.
– Understanding setting as often as possible requires
perceiving the effect of the individual creation the
announcement. Certainly, progress has been made in
the field of "emotional figuring," empowering PCs to
perceive a client's effect by estimating physiological
states and outward appearances. Yet, as a pioneer of
the field explains, it is one thing to separate between
"client is disappointed" and "client isn't baffled," or even
to separate between fundamental passionate states, for
example, outrage, dread, misery, and love. It is very
another, and substantially more troublesome, for a PC to
perceive and mark the unending exhibit of progressively
complex passionate states that we ourselves can once in
a while name, yet that we all things considered explore
utilizing the implicit abilities of enthusiastic knowledge.
Such assignments need adequate structure to be
demonstrated as a lot of deductive or information driven
guidelines and can't be robotized as of now.
V. LEGAL ISSUES IN THE IMPLEMENTATION OF AI
– Pace: Innovation has been creating at the fastest rate
since the Industrial Revolution; snappier than the law
can pace. Along these lines, when legitimate issues
emerge, usually, they are an instance of initial
introduction. Lawyers who have an AI case fall into their
lap will step into a strange area, without a guide, and
attempting cases before judges who may not
understand the innovation.
– Liability: If a mishap includes AI, attempting to locate
the obligated party resembles playing a sci-fi rendition of
Sign. A shrewd vehicle hits a passerby, who is the
blameworthy party? The developer in the workplace with
the source code? The proprietor out and about with the
vehicle? The maker in the lab with the testing
conventions? For instance, the issue of liability hasn't
been settled at this point for Google's driverless
vehicles, however specialists, for example, UCLA
teacher John Villasenor and others contend that item
liability could cover any driverless auto crashes [16, 20].
– Liability (civil): As AI is sorted out to legitimately
influence the world, even truly, liability for hurts brought
about by AI will increment in remarkable quality. The
possibility that AI will carry on in manners fashioners
don't expect difficulties the prevailing supposition inside
tort law that courts just make up for predictable wounds.
Courts may self-assertively appoint liability to a human
on-screen character in any event, when liability is better
found somewhere else for reasons of fairness or
proficiency. On the other hand, courts could decline to
discover liability in light of the fact that the litigant under
the steady gaze of the court didn't, and proved unable,
anticipate the damage that the AI caused. Liability would
then fall as a matter of course on the exemplary
casualty. The job of item liability—and the duty that
tumbles to organizations fabricating these items—will
probably develop when human on-screen characters
become less liable for the activities of a machine.
– Liability (criminal): If tort law anticipates that
damages should be predictable, criminal law goes
further to expect that damages be proposed. US law
specifically appends incredible significance to the idea
of mensrea—the proposing mind. As AI applications
take part in conduct that, were it done by human, would
establish a wrongdoing, courts and other lawful
entertainers should bewilder through whom to consider
responsible and on what hypothesis [1].
Variations/bias: AI frequently needs to distinguish
items, for example, vehicles, or individuals. Be that as it
may, on the grounds that AI depends on cameras and
coding, things like complexity, shading, and picture
thickness influence AI's "thinking" considerably more
significantly than people'. An individual would not
probably miss a white semi-trailer "against a brilliantly lit
sky." A human would not botch an example of spots or
lines for a starfish. AI additionally can reflect inclinations
of the engineer; as observed in numerous product
projects' propensities to create racial predispositions.
Recognizing and moderating predisposition in AI
systems is basic to building trust among people and
machines that learn. As AI systems discover,
comprehend, and call attention to human irregularities in
dynamic, they could likewise uncover manners by which
we are incomplete, parochial, and psychologically one-
sided, driving us to embrace progressively unbiased or
populist sees. During the time spent perceiving our
inclination and showing machines our normal qualities,
we may improve more than AI. We may very well
develop ourselves [19, 23].
(a) Employment Law for AI: The driver behind the
advancement of AI is the interest and requirement for
robotization. With the target of expanding effectiveness,
organizations over the world have endorsed to the act of
using AI as a substitution of the human workforce. This
rush of computerization is making a hole between the
current business laws and the developing utilization of
AI in the work environment.
For example, can an AI claim advantages, for example,
fortunate reserve installments or tip under existing
business enactment or sue an organization for
illegitimate end of work? Such inquiries likewise hold
pertinence for the human workforce, as in many cases,
AI expects people to work and the failure of business
laws to have clearness as to the above may
antagonistically effect such people, too [34].
(b) Contractual relationship/ Smart Contracts:
Another worry is the capacity of an AI to execute and be
limited by contracts. W hile worldwide laws have
perceived self-upholding contracts, there is a
requirement for an extensive enactment regarding the
matter. Under Indian law just a "legitimate individual"
can be skillful to enter a substantial agreement.
Chandra et al., International Journal on Emerging Technologies 11(3): 344-350(2020) 348
The general standard up to this point has been that an
AI may not qualify as a lawful individual. Subsequently,
an agreement went into independently may not be
viewed as a substantial agreement in India. Resultantly,
steps should be taken to guarantee that innovation
norms are created to satisfactorily direct agreements
went into by AI [12, 13].
(c) Privacy: AI as of now tracks and predicts people's
shopping inclinations, political inclinations, and areas.
The information collected and shared between these
innovations has just made numerous discussions inside
the legitimate field. In any case, AI is beginning to
handle progressively disputable subjects, [9] for
example, anticipating sexuality and penchant to carry
out a wrongdoing. W ill these forecasts have the option
to be utilized in preliminary? Or then again will the AI fill
in as specialists, to be interrogated to decide the
legitimacy of their conclusions?
With regards to AI, there are as of now more lawful
inquiries than answers. In any case, don't stress; robots
may have legitimate responses for us soon enough.
When they do, will we be prepared to tune in? Law,
including AI lawyers, is nevertheless one territory to be
disturbed by AI.
VI. INJUSTICE IN COVID PANDEMIC ON LABOUR
MIGRATION & ECONOMIC SLOW DOWN
Covid 19 Pandemic effects all over the world in each
and every sector but the two major categories have
major injustice during pandemic situation."Coronavirus
has taught workers that distance matters, "Professor S
Irudaya Rajan at the Centre for Development Studies,
Thiruvananthapuram. IrudayaRajan, one of India's
leading population studies experts and pioneer of the
annual Kerala Migration Survey, says the lesson
learned from the 2008 global economic crisis was that
"employment matters." The virus has given a new
distance lesson and could lead to a considerable
reduction in long-distance migration, he says.
Lacking jobs and money, and shutting down public
transportation, hundreds of thousands of migrants were
forced to walk hundreds of miles back to their
hometowns – with some dying along the way.
On May 2020, Moody's Investors Service said the steps
announced by the government for financial institutions
as part of the Rs 20 lakh crore-economic package would
help ease their asset risk, but will not entirely account
for the negative effect of the COVID-19 outbreak. The
government declared aRs 3.70 lakh crore funding
package for the micro, small and medium-sized
enterprises (MSME) industry, Rs 75,000 for non-bank
companies. Moreover, the MSME sector was still under
financial pressure before the coronavirus outbreak due
to the steady downturn in India's economic growth over
the past 18 months. As a result, it has limited ability to
survive another economic shock, according to Moody's.
"The deeper and broader economic downturn in India's
economy, the more liquidity stress the MSMEs will face,
leading to asset-quality problems.
VII. DISCUSSION AND CONCLUSION
The J Turner (2018) believes will thrive as what he
terms the “zero-sum” or “distributive” activities. That is,
they not so much create as distribute resources
throughout the economy. Among these, for example,
are lawyers “who protect intellectual property rights”; tax
accountants and lawyers who minimize tax payments;
and “financial regulators and the increasing army of
compliance officers and auditors” [23]. The effects of
relentless automation are growth in personal service
jobs, e.g. nurses, chefs, care aides, some of which
might be able to command higher salaries, others not,
as people leave the jobs which are being automated.
There will also be an increase in returns to monopoly
capital, of all kinds, and rent seeking skills like creative
industries and exploiting intellectual property [23]. These
shifts and outcomes raise the demand for professionals,
the zero-sum specialists, who will be managing the
distribution of rights and property. Lawyers are essential
to these activities and so will not fade away. A key
question will be: what is the optimum number of lawyers
and other professionals in an automating economy?
Turner argued that zero-sum activities will increase, but
over time the tasks being done by such specialists will
themselves become subject to automation through
developments in AI, blockchain and the like. Thus, an
increase in professionals could be followed by an
eventual decrease in numbers [15, 12].
The legal practice requires strong problem-solving skills
and emotional intelligence — skill sets that cannot be
directly replaced by machines. In addition, we are
operating in a complex and ever-evolving global
environment. A single wave of tech solutions is unlikely
to replace the legal landscape. After all, AI tools are
based on human intelligence and are only as smart as
we make them [18].
VIII. WAY FORWARD – FUTURE FOR JUSTICE
DELIVERY SYSTEM POST COVID-19
Eventually, obviously, undue weight ought not be put on
Legitimate AI alone. Lawyers keep on assuming an
imperative job in key lawful work for a long time to
come. Innovation isn't intended to be (nor without a
doubt is it presently fit for being) utilized as an
independent instrument.
The objective is to utilize AI in addition to people (as
airplane pilots use autopilot). Together, they can
guarantee that agreements are inspected significantly
more precisely — and more reliably — than a human
alone. This will keep on bringing more selection of the
bunch lawful innovation arrangements, that empower
lawyers to carry out their responsibilities all the more
successfully.
Justin Earthy colored, Accomplice at Earthy Colored
Siblings Law, another member in the analysis in the
examination, put it along these lines: "As a chess player
and lawyer I will take from Grandmaster VishyAnand
and state the eventual fate of law is 'human and PC'
versus (another) 'human and PC.' Either working alone
is substandard compared to the mix of both. I see AI
and innovation as energizing new devices that would
take into account such day laborer work to be done
quicker and all the more effectively”.
Existing technology already allows us to use ML tools to
predict judicial outcomes based on previous cases. A
“robot clerk” based on these technologies has the
potential for alleviating the overwhelming caseloads of
routine decisions in many jurisdictions. Moreover, by
providing some input and analysis of an individual
Chandra et al., International Journal on Emerging Technologies 11(3): 344-350(2020) 349
judge’s decisions, the robot clerk might help human
decision makers identify their weak spots and learn to
understand and mitigate their prejudices. ~But these
promises do not lead to a robot serving as final legal
decision-taker. The choices of current calculations are a
black box and can't be explained to legitimate members
or general society. There is no guaranteed approach to
cleanse previous inclination from the machine-
anticipated choices. What's more, there are major
mechanical and political difficulties to creating and
actualizing system that would peruse the laws and
attempt to execute socially ideal strategies.
~Nevertheless, the state-of-the-art existence of
legitimate computerization has arrived [24, 26].
It is up 'til now uncertain which of these advances may
get across the board and how various governments and
legal authorities will decide to screen their utilization.
The day when innovation will turn into the appointed
authority of good and awful human conduct and dole out
suitable disciplines despite everything lies some path
later on. Be that as it may, lawful systems frequently
give perfect instances of administrations that could be
improved, while preliminaries are probably going to
profit by better information examination.
The law frequently requires a preliminary to start a trend
– so keep an eye out for the experiment of AI as judge
[37].
IX. FUTURE SCOPE
The next step of this study is to evaluate various
Artificial intelligence tools and techniques to understand
their applicability in the Judicial Delivery System. The
use cases from different countries around the globe also
to be considered.
Conflict of Interest. There is no Conflict of Interest in
this work.
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How to cite this article:
Chandra, G., Gupta, R.
and Agarwal, N.
(2020). Role of Artificial Intelligence in
Transforming the Justice Delivery System in COVID 19 Pandemic. International Journal on Emerging Technologies,
11(3): 344–350.
