Relevance: GS-3: Science and Technology- developments and their applications and effects in everyday life.

Key Phrases: AI, Machine learning, Natural language processing, Data and Privacy, Ethical governance, SUPACE, SUVAS, human rights, AI portal, RAISE 2020.

Why in News?

• Can artificial intelligence (AI) be used in judicial processes to reduce the pendency of cases? In response to this unstarred question in the Lok Sabha during the first part of the Budget session of Parliament, Law Minister Kiren Rijiju said that while implementing phase two of the eCourts projects, under operation since 2015, a need was felt to adopt new, cutting edge technologies of Machine Learning (ML) and Artificial Intelligence (AI) to increase the efficiency of the justice delivery system.

Context:

• AI and Machine Learning (ML) have a multiplier effect on increasing the efficiency of any system or industry. If used effectively, it can bring about incremental changes and transform the ecosystem of several sectors.
• In the justice delivery system, there are multiple spaces where the AI application can have a deep impact. It has the capacity to reduce the pendency and incrementally increase the processes. The recent National Judicial Data Grid (NJDG) shows that 3,89,41,148 cases are pending at the District and Taluka levels and 58,43,113 are still unresolved at the high courts. Such pendency has a spin-off effect that takes a toll on the efficiency of the judiciary, and ultimately reduces peoples’ access to justice.
• Over the course of the COVID-19 pandemic, the use of technology for e-filing, and virtual hearings has seen a dramatic rise. From the beginning of the lockdown in 2020 until January 8 this year, the Supreme Court of India emerged as a global leader by conducting 1,81,909 virtual hearings.

How can AI uses in the justice system?

• The use of AI in the justice system depends on first identifying various legal processes where the application of this technology can reduce pendency and increase efficiency. The machine first needs to perceive a particular process and get information about the process under examination. For example, to extract facts from a legal document, the programme should be able to understand the document and what it entails.
• Over time, the machine can learn from experience, and as we provide more data, the programme learns and makes predictions about the document, thereby making the underlying system more intelligent every time. This requires the development of computer programmes and software which are highly-complex requiring advanced technologies. Additionally, there is a need of constantly nurturing to reduce any bias, and increase learning.
• One such complex tool named SUPACE (Supreme Court Portal for Assistance in Court Efficiency) was recently launched by the Supreme Court of India. Designed to first understand judicial processes that require automation, it then assists the Court in improving efficiency and reducing pendency by encapsulating judicial processes that have the capability of being automated through AI.
• Similarly, SUVAS is an AI system that can assist in the translation of judgments into regional languages. This is another landmark effort to increase access to justice. The technology, when applied in the long run to solve other challenges of translation in filing of cases, will reduce the time taken to file a case and assist the court in becoming an independent, quick, and efficient system.

Application of AI in Judiciary:

AI to improve administrative efficiency

• Besides doing their judicial tasks, judges in all courts, including the Supreme Court, are required to undertake administrative work as well.
• In this context, the paper talks about developing “task-specific narrow AI tools”, which can help judges in spending less time on administrative responsibilities.
• Such tools would also ease the “general rigour of the registry”, from scheduling a hearing and creating cause-lists to more complex tasks like discovery and review of evidentiary documents.
• The pandemic has led to a surge in discussion around increasing digitisation through the e-Courts Project, creation of virtual courts, and the potential of online dispute resolution. Within this conversation, AI has also become an increasing talking point.
• Other small tasks like smart e-filing, intelligent filtering or prioritisation of cases and notifications or tracking of cases can also benefit from this integration.

Justice can be expedited through AI tools

• Artificial intelligence tools can also aid lawyers and judges with “legal research, analysis of factual proposition, determination of appropriate legal provisions and other similar mechanical skills”, which in turn can expedite justice delivery.
• The research paper noted that algorithms can be conceptualised, designed and deployed for “intelligence analytics and research work”.
• These tools can also provide comprehensive legal briefs on cases, encapsulate pertinent legal research and identify crucial points of law and facts.
• This can effectively supplement human judgment in adjudication. Furthermore, intelligent tools, like legal bots, can be designed to help potential litigants with better informed decision making concerning their legal rights, and easily and cost-effectively access basic legal services.
• It also suggested developing tools that can help judges arrive at decisions in cases such as the motor vehicle compensation claims, where the tribunal’s role is limited and rarely involves legal interpretation.
• A possible tool could aid the judge in cataloguing the requisite documents for such a claim, and glean the relevant information that will allow the judge to determine if compensation is due, the party that is liable to pay, and the value of compensation.
• However, to harness the “transformative potential of emerging technologies like AI”, it stressed on the need to have open access to machine-readable, non-sensitive data.
• The judiciary, it added, should lay out some broad rules to govern data sharing.

Challenges to AI

There are various challenges and potential dangers of using AI technology:

• AI can perpetuate biases either unintentionally or intentionally and can be vulnerable to attack or hacking.
• Since these systems are often trained on large datasets, they tend to replicate the same biases that were present in the original datasets. Similarly, personal biases of developers of algorithms may further add to this problem.
• It also noted that according to research, people tend to use computer systems to reduce the effort of the decision-making process rather than to increase the quality of their own decisions.
• Therefore, given the high pressure of caseloads and insufficient resources, there is a danger that supporting systems based on AI can be used by judges without applying their own minds.
• It is therefore possible that the use of decision support systems in the judiciary might not improve adjudication, but rather make it worse.
• Data and Privacy: The protection of personal data in the AI environment may be a serious challenge wherein there may be trade-off between privacy and prosperity. The General Data Protection Regulation in European Union, the sectoral and state laws in US and cybersecurity law in China may be taken as the basis for policy formulation.
• Ethical governance: The ethical considerations and governance issues of AI may be redefining regulations and governance with focus on fairness, safety, reliability, privacy, inclusiveness, transparency, and accountability.
• Consumer courts are an area where AI can be helpful. But in criminal cases where oral evidence and cross examination are key processes, we have to rely on regular human intervention.

Way forward:

• The Supreme Court has become the global frontrunner in application of AI and Machine Learning into processes of the justice system. But we must remember that despite the great advances made by the apex court, the current development in the realm of AI is only scratching the surface.
• Over time, as one understands and evaluates various legal processes, AI and related technologies will be able to automate and complement several tasks performed by legal professionals.
• It will allow them to invest more energy in creatively solving legal issues. It has the possibility of helping judges conduct trials faster and more effectively thereby reducing the pendency of cases.
• However, the integration of these technologies will be a challenging task as the legal architecture is highly complex and technologies can only be auxiliary means to achieve legal justice.
• There is also no doubt that as AI technology grows, concerns about data protection, privacy, human rights and ethics will pose fresh challenges and will require great self-regulation by developers of these technologies.
• It will also require external regulation by the legislature through statute, rules, regulation and by judiciary through judicial review qua constitutional standards. But with increasing adoption of the technology, there will be more debates and conversations on these problems as well as their potential solutions. In the long-run all this would help in reducing the pendency of cases and improving overall efficiency of justice system.

Source: The Hindu

Mains Question:

Q. Discuss the role of cutting edge technologies of Machine Learning (ML) and Artificial Intelligence (AI) to increase the efficiency of the justice delivery system. Critically Analyse.