Featured ~ Society for Excellence in Arbitration Law

By: Chitrangda Saini and Kanishtha Daswani.

Introduction

Alternative Dispute Resolution (ADR), which mainly involves negotiation, mediation, or arbitration, or a combination of all three, gained popularity due to the expensive costs and time-consuming process associated with litigation. With technological advancement on the rise, ODR gained prominence as a preferred medium of dispute resolution, particularly for disputes arising out of electronic contracting, which are often delayed and inadequately addressed owing to inefficient and outdated court practices. Furthermore, the pandemic also necessitated the adoption of ODR and drove the need for a robust online mechanism for dispute resolution. The International ODR forum has greatly influence regulatory bodies in the field of ODR and have suggested measures to encompass ODR’s social ramifications, such as its applicability to sports, accessibility for people with disabilities and  social intuition in virtual processes, while also exploring the untapped potential of ODR in high-stakes cases. 

As we inch towards creating a favourable environment for ODR, it is pertinent to realize and appreciate the extent of potential AI holds in shaping the landscape of ODR in India. There is a higher incentive to leverage AI for efficient facilitation of ODR system since the regulatory bodies like Securities and Exchange Board of India (SEBI) are now proceeding towards establishing a common ODR portal for enhanced efficiency.

The judiciary has also recognised AI’s potential in reducing the burden on courts. Moreover, it has acknowledged that the developments in the legal framework must attune to such developing trends in technology while being conscious of their implications for the future. 

AI As A “Fourth Party”

AI can be tailored to serve different purpose for different aspects of ODR. A well build mechanism can direct the clients to the appropriate dispute settlement forum after a thorough analysis of the dispute. The predictive analytics prowess of AI proves particularly advantageous in gauging potential case outcomes. Countries like UK, Canada, France, Netherlands, Qatar and many others have been increasingly integrating AI into dispute resolution mechanisms for the purposes such as – scrutinising historical case data and considering diverse factors. These countries have developed tools where AI systems can forecast the likelihood of success associated with different legal strategies. This aids parties in making educated decisions regarding settlement offers, negotiation strategies, or the pursuit of legal action. Predictive analytics also fosters transparency in the dispute resolution process, enabling parties to comprehend better the potential risks and advantages inherent in their chosen course of action. Moreover, these tools are noticed to be used to automate repetitive and predictable tasks, freeing up human resources to focus on more complex and nuanced issues.

AI as the “fourth party” can be employed as a virtual mediator to assist the mediation process. China, the trailblazer in this arena, has already established “smart courts” or “internet courts” in place. Noteworthy examples include China’s Self-contained ODR forum TABAO and the private ODR forum ICANN, which have successfully managed 1,20,000 disputes since their inception. The EBay Resolution Centre is another example which has further underlined the efficacy of AI in resolving disputes. 

Taking a cue from the existing mechanisms in place, India can work towards adopting a framework premised on directing the AI in decision making by employing a meticulously curated set of rules and regulations. An alternative approach could be to set up a mechanism which would rely on existing data pertaining various and use pattern recognition to evaluate the strengths and weakness of a case, scrutinize crucial issue, draw comparisons and could suggest a possible course of action along with a probable rational solution to the problem. 

Similarly, AI has revolutionized translation in an era marked by intricate trade relationships and cross border disputes. It natural language processing (NLP), neutral networks and machine learning algorithms which can access and process data on a greater scale and produce results with more efficacy and precision. DeepL, Lengoo, Google are few examples of AI powered translating systems. Another remarkable mention is Supreme Court’s Vidhik Anuvaad Software (SUVAS) which facilitates translation of English into vernacular languages to help bridge the language barrier.

Moreover, Chatbots are being used in ODR to help users navigate complex systems and classify claims by using multiple-choice questionnaires or advance NLP for more complex tasks. The efficacy of these tools hinges on technological resources, system complexity and user volume. Advanced chatbots, such as those using ChatGPT’s API, offer enhanced user experiences but require careful management to ensure they provide accurate, region-specific legal information.

Legal, Ethical and Technical Considerations 

Notwithstanding the efficacy AI possess, there is always a lurking possibility of erroneous solutions. As promising as integration of AI with ODR seems, it is not devoid of its limitations. 

Though AI opens several avenues for the future of ODR, there have been serious privacy and data protection concerns raised parallel to the advancement of such technologies. There are several questions that are yet to be answered regarding the measures in place which would protect confidential information collected by AI based tools and who can have access to that information. Though India has enacted the Digital Personal Data Protection Act 2023 (DPDP), it fails to address several concerns with regards to AI systems. Clause 3(c) (ii) of the Bill excludes publicly available data from its ambit, thereby allowing AI companies to access and process it without consent. 

Further, there is ambiguity regarding the admissibility of any document generated by such tools in courts and asserting liability in case of fault in the AI system. This indicates the unpreparedness of the legal framework to deal with legal and ethical implications of AI especially in countries like India.

Another impediment in the quest to operationalize AI within the realm of ODR is the paucity of industry specific data, absence of robust research mechanism and difficulty in accessing and annotating fragmented data, translation tools being one of these examples. The efficacious implementation of NLP and similar translating mechanism could be hurdle for a country like India due to scarcity of data and research conducted on Indian languages, especially different regional languages, not to mention different nuanced accents across the country which could hamper the efficiency of speech recognition software. 

Further, lack of technical know-how among the general public raise doubts regarding the effectiveness of AI and creates trust deficit. It is imperative that there is a revolutionary shift from “one-size fits all” approach and efforts are made to develop AI peculiar to the issues in India. 

Global Perspective

Nations across the world have made laudable efforts to integrate AI supported platforms with ODR processes. These platforms are a diverse mix of government-run platforms, platforms affiliated with the courts and privately owned platforms, fashioned to cater to specific needs of different countries. One such initiative is the ODR platform by the European Commission which facilitates direct communication between the trader and the consumer and alternatively provides a provision for resorting to an ODR service provider, accredited by sector-specific regulators to resolve their dispute. 

Canada has been at the forefront with its CRT, a government run platform, which offers various options to the parties to negotiate, opt for a mediator or take the route of arbitration to resolve their disputes.

A similar initiative is US’ New Mexico Courts ODR Centre for resolution of debt and money claims. It provides a platform to the parties to negotiate and reach a settlement. Upon reaching a settlement, the platform prepares an agreement for the parties to sign, ensuring legally binding resolution. Simultaneously, it also prepares a stipulation of dismal to withdraw the case and submits it in the court.

Other prominent examples are Europe’s YOUSTICE, Canada’s PARLe, US’ smart settle offering ODR services for different categories of disputes.

The legal industry in India is gradually embracing online infrastructure in its functioning, with initiatives like Peacegate by Indian Institute of Arbitration, SEHMATI, a remarkable initiative by Delhi dispute resolution society which is solely dedicated to ODR. However, there still exists a pressing need for broader acceptance and proactive measures to expedite the transition. India still has a long path to tread and in its attempt to actively incorporate AI in ODR, it can mirror initiatives taken by countries around the world. 

Taking a cue from Brazil’s Consumidor, there can be a dedicated platform for ODR, integrated with state or district consumer rights protection bodies. Alternatively, such platform can have private-owned ODR service providers accredited by a regulatory body which can keep checks on all the ODR service providers and can manage their incorporation, accreditation, audits and other related compliances. 

However, any initiative in this regard would only be possible if the government in particular assumes a leadership role and spearheads the mainstream adoption of ODR mechanisms meanwhile fostering effective collaboration with private players to execute the vision.

Way Forward

In the contemporary landscape, the predominant focus has been on transitioning traditional ADR to ODR. However, this evolution should extend beyond mere electronic ADR (e-ADR). This entails the formulation of targeted policies, the initiation of remote learning programs to educate professionals, meeting the escalating demands for neutrals, and the establishment of a robust legal framework which addresses concerns surrounding privacy and data management and also streamlines legal processes nationwide. An impactful starting point could involve the government adopting ODR for the resolution of its disputes, thereby fostering trust in the process and encouraging broader public acceptance of ODR as a viable means of dispute resolution.

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Author’s Bio

The blog is co-authored by Chitrangda Saini (Final Year Law student at National Law University Odisha) and Kanishtha Daswani (A Final Year Law student at National Law University Odisha).

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