The pandemic has led to re-imagination of several key processes. Given the impact Covid-19 has had on justice delivery, it is encouraging to note how the judiciary has explored and supported innovations through technology. While the eCommittee’s Vision for Phase 3 is transformational, equally progressive is the approach of the judiciary to non-intrusive inclusions relying on artificial intelligence (AI) and machine learning (ML). Building upon accomplishments of courts in facilitating virtual hearings, and the introduction of e-filing during the pandemic, exploring how AI can help courts is visionary.
Tools derived from AI could help expedite the case-flow management, unclog processes that slow justice down, and in many cases ease administrative aspects. Importantly, the use of AI in courts does not envision replacing the wisdom, experience and objectivity of judges in determining verdicts. In the conceivable future, there is no question of replacing human reasoning, logic and intelligence of the judiciary, with automation. But there are many aspects of technology that can be integrated with immediate effect.
AI and ML for justice delivery will need to be adapted with several precautions in mind. The Supreme Court Portal for Assistance in Court’s Efficiency (SUPACE), inaugurated recently by former CJI SA Bobde, is said to be the first of its kind globally. Building upon the requirement that AI should assist the judiciary, it will help aid access to material, but would remain non-intrusive when it comes to decision making. This is the correct approach, where AI and ML assist but do not replace human decision making.
It also will not lead to increased unemployment; as Bobde earlier said, “there is no question of creating redundancy of any post in the judiciary.” The SUPACE follows the launch of the Supreme Court Vidhik Anuvaad Software (SUVAS), an ML tool for translating Supreme Court judgments into vernacular languages. Together, these are important forays into bringing AI for efficiency to the judiciary.
The relevance of AI in justice delivery will be predicated on the availability of clear and well-labelled data sets. A report by the Aapti Institute titled ‘Just and Equitable AI Data Labelling: Towards a Responsible Supply Chain’ notes the “surge in automation and the necessity for a ‘human-in-the-loop’ for creating robust, training data sets is indicative of the fact that data labelling is likely to be a viable employment opportunity in India, particularly given that it can be carried out remotely. Its potential was also recognized by India’s first-ever National Strategy for AI, by NITI Aayog (2018).”
Justice L Nageswara Rao, the chairman of the Supreme Court’s AI Committee, has said that it is “implausible that the AI system will make human lawyers or judges redundant.” He added the system should help the judiciary and courts in lowering delays and pendency in courts. Justice BN Srikrishna in his chapter in the book ‘India 2030: Rise of a Rajasic Nation’ said that “AI will not only help organise cases, it will also bring references into the judgment at a speed not seen so far. Technology will ensure that those who do not have access to justice due to distance will not be excluded anymore.”
The responsible use of AI has been explored extensively, including both by NITI Aayog, and recently by the Vidhi Centre for Legal Policy in its paper titled ‘Responsible AI for the Justice System.’ In the paper, Vidhi stressed upon increased administrative efficiency whereby “task-specific, narrowly tailored algorithms, trained through machine learning, can be deployed to automate run of the mill administrative functions, from something as routine as scheduling hearings and creating causelists, to more complex tasks like discovery and review of evidentiary documents. Similarly, other procedural tasks which can benefit from the use of AI include interventions at the level of smart e-filing, intelligent filtering/prioritisation of cases or notifications and tracking of cases.” Also to be considered is the augmenting of decision-making processes where “computational tools can be used to expedite justice delivery such as those for traffic challans and motor vehicle compensation claims. Assimilated learning from such first generational tools that increase administrative efficiency will be necessary before potentially creating more complex algorithmic decision-making tools.”
The ethical and responsible use of AI and ML for the advancement of efficiency enhancing can be increasingly embedded in legal and judicial processes. The Supreme Court has laid a strong foundation basis which efficiency enhancement can be accelerated across functional processes. This is one of the key reasons why justice delivery in India is poised for transformative change.
Source: financialexpress.com
