Role of Artificial Intelligence and Machine Learning in Arbitration

Arbitration is based on three pillars: (i) quick, inexpensive, and equitable trials before an impartial tribunal; (ii) the parties’ autonomy; and (iii) judges’ minimal involvement. Keeping these ideas front and centre, research into generative AI models for judicial and arbitral applications is a fascinating development that may lead to extraordinarily positive but unthinkable results. There are a lot of options because the law is flexible and intended to cover a wide range of situations. Technologies and the law seem to be collaborating and could do so in the future. Concerns about their creation and scope, however, still exist. Interestingly, the origins of one such widely held belief, online dispute resolution, can be traced back to 2001, when professors Ethan Katsh and Janet Rifkin publicly published “Law in a Digital World.”

Machine Learning and Artificial Intelligence

Alan Turing is considered the father of machine learning, or “ML,” which started in the 1950s. The independent ability for thinking and logic is the main difference between machine learning (ML) and artificial intelligence (AI). The reliance on human guidance, teaching, and feedback is one of machine learning’s disadvantages. Time saved is the main benefit attained. Essentially, machine learning occurs on blockchains, in which algorithms and data are employed to program the computer or program to perform specific activities. The process, outcome, and code are then preserved within a huge network of databases that are easy for the machines and human players to retrieve. Players within that specific blockchain, which is a cloud, get access to the preserved data. But they cannot change the way things work.

With arbitration, ML has brought in supervised learning, where input data is properly matched with output data in order to recognise patterns and process the relevant data concerning the task, i.e., the legal case under consideration. This has primarily resulted in those developments which can be designated as secure case management systems, quicker research and its compilation, summarization and problem identification, strategy formulation and outcome predictions. Singapore and China have made significant progress with the Singapore International Arbitration Centre (“SIAC”) having issued a draft of its seventh edition of the SIAC Rules, including in its provision for the SIAC Gateway, an online case management system.[1] Inspired in 2022, the ICC launched “Case Connect,” which is a secure online case management platform that facilitates communication and file sharing between arbitrators, parties, and the Secretariat. This significantly accelerates and simplifies the arbitration process by relying only on technology.

In addition, China is testing AI in the legal area through trials of programmed AI secretaries to draft decisions. Institutions like the Shenzhen Court of International Arbitration are probing how AI can support arbitrators in examining documents and analyzing cases. Software like Thomson Reuters’ Co Counsel, Jus Mundi’s AI research assistant, and ChatGPT are already assisting lawyers and arbitrators with anything from summarizing documents to researching the law. Rather than merely executing code, companies are automating the comparatively more mundane tasks that need neither creativity nor code writing, such as retrieving data and carrying out research, along with determining the possible vulnerabilities and corresponding countermeasures. Due to this, parties are investing in democratization, levelization, and market stabilization, making small businesses more competitive since they are focusing on vital matters. This aligns with the accelerated resolution concept of arbitration; due to its virtually instant and online/automated process, parties are gravitating toward this collaborative system of ML/AI in their arbitration disputes. India’s Ministry of Law and Justice has also pledged to carry out preliminary studies on the implementation of AI and machine learning within the legal and arbitration frameworks. Considering the humongous number of pending cases in the country, this is a tremendous amount of hope. Except for a few, Online Dispute Resolution (ODR) started from the completion of all proceedings online, but now it has grown in terms of scope.

The conduction mode of choice used to be a specific online forum. Work was not mechanised, though; the procedures/process remained the same, but differed in the simple sense of filing mode of documents and hearings conducted online. With the arbitration panels acknowledging it, e-evidence has also been given top importance. Arbitration courts, organizations, and businesses have started extending their search radius. Regarding ML’s inclusion into e-commerce arbitration and online consumer mediation, WIPO, SIAC, UNICTRAL, etc., have all reassured development. Currently, improvements in artificial intelligence are being used in court and arbitration processes, which could be cause for concern; the legally open-ended character of arbitration and its optimistic goal and approach could cause problems.

Pertaining Issues

1. Minimum court intervention

As such, it is possible that with the judicial aid generative artificial intelligence has to offer, one may not necessarily need to be trained in law if the technology is widely used. Small Claim Tribunals in Singapore have started testing AI-driven justice, where the bot assesses the facts, finds relevant precedents, and gives a decision in line. However, the parties are requested to report on their satisfaction; in case of party grievances, the case is referred to a human judge overseeing the AI bot court. Though there remains a shortage of reliability and transparency that creeps in, this may impact the processes of arbitration with high cost-effectiveness and expedited hearings; this would pose problems, particularly if extended to Arbitral Awards.

2. General issues with AI

The advent of AI has created issues concerning reliability, responsibility, privacy, and transparency for the industry. The same problems would arise for Arbitration and other areas of technology law if they were to be applied. Answers and solutions provided by GPT are still unverifiable, posing a greater question of trust, with increased chances of error pertaining to errors being made during arbitration and time-constrained, decisive judgment calls. Due to the lack of access to the system’s code other than its builders or the system’s creators, the operators and users do not understand the step-by-step processes of the inner workings of the system, which leads to a total opacity of the procedures exploited within the system. Arbitration proceedings are often preferred due to the transparency they offer. However, parties may not opt for ODR due to hesitancy and ambiguity on how the arbitral award is reached, formulated and passed. Accountability and confidentiality of the systems will naturally fall upon the operators, i.e., the arbitration firms or the international/national arbitration bodies.

3. E-evidence

For online arbitral proceedings, the evidence submitted would naturally devolve into electronic means. Parties will have a lack of confidence in the same, with human arbitrators facing difficulties in verifying of evidence submitted. New and uniform guidelines will have to be issued. The development of faith in the procedure requires a passage of time, with natural errors along the way. Additionally, a rising issue is that of deep-fake testimonies[2], with people creating electronic evidence on their devices and pre-recorded testimonies with the help of generative AI and technology, verification of which is extremely difficult, if not impossible. The ease of manipulating court proceedings and evidence will heighten with AI’s advent and incorporation into the arbitration system. The fundamentals of the process will be put at risk.[3] Relevant guidelines and rules can be put in place to tackle the same.

Way Forward

Contrary to rising fears, the possibility of a complete takeover of AI in the judicial system seems highly improbable, owing to the slow development of ML and AI, while also having severe limitations on scope. The ability of AI to develop rationality and independent thought is a far-off and long-drawn idea, if possible, at all, and would, therefore, be unlikely to be entrusted with the task of passing an arbitral award that has real consequences.

 While the responsibilities could extend to an assistor’s capacity with AI revolutionizing cost effectiveness and expedited arbitral proceedings along with heightening case management and strategy development for arbitration firms; human beings would still be needed to supervise, and, more importantly, to make creative decisions, come up with new landmark judgements and lines of thinking, as well as building human trust and interpersonal relations with clients and parties. Essentially, generative AI will not develop soon, if at all, to have a mind of its own. However, the incorporation of ML in arbitration will shortly lead to positive outcomes. The playing field for arbitration firms will be levelled with smaller firms competing with the bigger firms due to stabilising and equalising tools, i.e., analytic ML and AI. Arbitral proceedings would be expedited and delivered to the parties’ satisfaction, with frivolous claims cleared up on the basis of prediction by the arbitration-counsel firm. The tedious and bothersome paperwork and research will be taken off the hands of young interns and paralegals and instead be merely inputted into the ML program, subject to verification.

Blockchain-based proceedings will be efficient, expedited and cost-effective if explored and consequently implemented. The future of arbitration with respect to revolutionised online dispute resolution and ML’s assistance seems assured and positive, onto a new era.

Author: Apnatva, in case of any queries please contact/write back to us via email to [email protected] or at IIPRD. 

[1] (2024, August 27). SIAC launches online case management platform, powered by Opus 2. OPUS 2. Retrieved May 18, 2025, from https://www.opus2.com/en-us/news/siac-gateway-launch/

[2] Haridi, S. (2024, September 12). Innovation in arbitration: The technological revolution in dispute resolution. International Bar Association. Retrieved May 19, 2025, from https://www.ibanet.org/innovation-in-arbitration-the-technological-revolution

[3] Stanley, C. (2019, April 2). Fundamentals of Risk in Decisions – Part 3. VMware Cloud Blog. Retrieved May 19, 2025, from https://blogs.vmware.com/cloud/2019/04/02/fundamentals-risk-decisions-part-3/