Artificial Intelligence (AI) is a field of computer science focused on developing systems that can perform tasks typically requiring human intelligence. It has revolutionized industries such as healthcare, finance, and manufacturing, with applications like disease diagnosis, fraud detection, autonomous robots in factories, etc.

Various industries seem to have accepted and inculcated AI into their day to day lives and the legal industry seems to be moving towards the same direction. AI Platforms like Chat GPT, Perplexity, Do Not Pay are chat boxes, where users can interact with AI to seek information, have been used by people for drafting of legal documents and seeking legal advice. However, there have been various instances where the users have not been able to find what they were looking for or have received incorrect information based on which they have moved forward and have not gotten the desired result, which raises some critical unanswered questions related to administration, regulation and accountability that need to be addressed before a full-fledged implementation takes place.

Arbitration is a voluntary dispute resolution process where impartial arbitrators chosen by the parties or arbitration institutions assess evidence, hear arguments, and issue binding decisions in a less formal and often confidential setting. It is commonly employed in various contexts, including commercial disputes, labour matters and international trade, offering a more efficient and specialized alternative to litigation with enforceable outcomes, often stemming from contractual agreements between the disputing parties.

This article aims to discuss two upcoming fields and their interplay that would help revolutionize the field of law.

Artificial Intelligence (AI) in arbitration refers to the integration of advanced technologies such as machine learning, natural language processing, and data analytics into the arbitration process. It involves the use of AI-powered tools to streamline and enhance various aspects of dispute resolution. The significance of AI in arbitration lies in its ability to expedite proceedings, reduce costs, and improve the overall efficiency and fairness of the arbitration process. By leveraging AI, arbitration can keep pace with the demands of the modern world.

The potential for AI applications in arbitration is vast and continues to expand, transforming the way disputes are resolved. Here's an exploration of how AI, including predictive analytics, smart contracts, and online dispute resolution (ODR) platforms, can shape the future of arbitration:

1. Predictive Analytics -

• Case Outcome Prediction: AI can analyse vast amounts of historical arbitration data, including case details, arbitrator decisions, and jurisdiction-specific factors, to predict potential case outcomes. This can help parties assess the risks and benefits of pursuing arbitration, leading to more informed decisions.

• Optimizing Arbitrator Selection: AI-driven algorithms can suggest suitable arbitrators based on their past decisions, expertise, and biases. Parties can use this information to select arbitrators who are more likely to render favourable decisions.

• Time and Cost Estimations: AI can provide estimates for the time and cost involved in an arbitration case based on historical data. This information allows parties to plan more effectively and budget accordingly.

• Data-Driven Negotiations: AI can assist in negotiation strategies by analysing past settlement outcomes in similar cases, helping parties identify optimal settlement terms.

2. Smart Contracts -

• Automated Dispute Resolution: Smart contracts can include predefined dispute resolution clauses, allowing parties to specify arbitration as the default mechanism in case of disputes. When a dispute arises, the smart contract can trigger the arbitration process automatically.

• Real-Time Monitoring: Smart contracts can be programmed to monitor a contractual performance. If certain conditions are not met, they can automatically initiate arbitration proceedings without the need for manual intervention.

• Transparency and Trust: Smart contracts operate on block-chain technology, providing a transparent and immutable record of contract terms and dispute resolutions, which can enhance trust between parties.

3. Online Dispute Resolution (ODR) Platforms -

• Efficient Case Management: AI-powered ODR platforms streamline case management by automating administrative tasks, scheduling, and document management, reducing the burden on arbitrators and parties.

• Virtual Hearings: ODR platforms enable virtual arbitration hearings, allowing parties and arbitrators to participate from different locations, which can significantly reduce costs and increase accessibility.

• Data Analytics: ODR platforms can leverage AI to analyse data from past cases, helping arbitrators and parties make informed decisions during ongoing arbitrations.

• Scalability: ODR platforms make it possible to handle a large volume of disputes simultaneously, making arbitration a more scalable and accessible option.

4. Technology-Assisted Review (TAR) -

• TAR is a process that utilizes AI and machine learning algorithms to assist in the review and analysis of large volumes of documents and data during legal proceedings.

• In the context of arbitration, TAR can significantly streamline the discovery process and enhance the efficiency of document review.

While the Indian Arbitration System is yet to implement and inculcate the use of AI, the Indian legal system, has started to meet the global standards that are being set for the implementation of AI.

Judiciary

Since 2021, the Hon'ble Supreme Court has stated to use the Supreme Court Vidhik Anuvaada Software (SUVAS) which uses AI to translate legal papers from English into vernacular languages and vice versa. The Artificial Intelligence Committee was created by the Hon'ble Supreme Court to examine how AI is used in the legal system. It introduced the Supreme Court Portal for Assistance in Courts Efficiency (SUPACE) that aims to provide digital infrastructure to help digitization of the court process.

Lawyers

Even the lawyers have had a taste of the benefits of AI as they have also stated to use AI chatboxes like ChatGPT and Perplexity to seek basic legal knowledge and draft some legal documents with ease. However, due to lack of any regulations and institutionalized mechanisms, the information and documents that are provided by these AI based systems cannot be relied on completely.

The successful integration of AI in the arbitration process presents several obstacles and hurdles that must be overcome. These challenges encompass regulatory compliance, technological limitations, ethical concerns, and practical considerations. Here's an overview of the key obstacles:

1. Data Privacy and Security

   Arbitration disputes often involves sensitive and confidential information. AI systems must ensure the protection of data throughout the arbitration process as it is crucial for the proper disposal of cases. Further, compliance with respect to data privacy regulations such as the Personal Data Protection Act, 2023 in India is critical.

2. Bias and Fairness

   AI algorithms can inherit biases present in training data, leading to unfair outcomes. Ensuring fairness in AI arbitration requires constant monitoring and mitigation of bias. Further, it should be ensured that the people inserting the data are not biased.

3. Regulatory Frameworks

   The existing legal framework, that is, the Arbitration and Conciliation Act, 1996 does not provide clear guidance on the use of AI in arbitration. Developing comprehensive regulations and standards is essential to ensure accountability and consistency.

4. Technological Limitations

   In a country like India, it is highly probable that not all parties or jurisdictions may have access to the necessary technological infrastructure for AI-based arbitration, potentially creating disparities in access to justice.

5. Ethical Considerations

   AI algorithms are difficult to explain and understand so would be the reasoning behind arbitration decisions that are based on AI, thus raising transparency concerns. So there is a need to strike a balance between the automation of arbitration processes and maintaining human oversight to ensure ethical and just outcomes.

6. User Acceptance and Trust

   The parties involved in arbitration must trust AI systems to make impartial and fair decisions. Building trust in AI's capabilities and neutrality is a significant challenge as many people are not technology friendly.

7. Education and Training

   Arbitrators, legal professionals, and parties involved in arbitration may require training and education on AI technologies and their integration into the arbitration process.

NITI Aayog released a report titled 'Designing the Future of Dispute Resolution (the ODR Policy Plan for India), 2021.' The committee recognized the benefits of Online Dispute Resolution and the role of Al towards achieving the same. The report recognized the importance of AI in developing an Online Dispute Resolution system in India. The benefits of AI in the development of such a system can be manifold, including the elimination of human bias in the process of dispute resolution, etc. The goal of ODR as noted in the report is to supplant and not eliminate the existing model of dispute resolution. The report shows that India is considering the implementation of Al in arbitration. However, it would have to go through a lot of hurdles and challenges as discussed in the article before it is successfully implemented. With the world steadily moving towards implementation of AI in various fields, India has also taken a step towards where the world is heading. Countries over the world have expressed the need to implement an AI Act in their respective legislations to be able to control the misuse of the new technology, and hence India should consider the same.

About the authors: Vikrant Rana is the Managing Partner of SS Rana & Co. Nihit Nagpal is an Associate Partner and Avik Gopal is an Associate at the firm.