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The transformative potential of Artificial Intelligence in ADR

The transformative potential of Artificial Intelligence in ADR

Alternative Dispute Resolution (ADR) methods, such as mediation and arbitration, have gained significant traction as efficient and cost-effective alternatives to traditional litigation. Of course, this is not without its pitfalls, some of which include cost and time. Nevertheless, with the rapid advancements in technology, particularly in the field of Artificial Intelligence (AI), it has become important to interrogate the cause and effect of AI in shaping and engaging the ADR framework for effective resolution of disputes.

AI refers to the development of computer systems that can perform tasks that would typically require human intelligence. These systems simulate human cognitive processes, such as learning, reasoning, problem-solving, perception, and language understanding. AI can be applied to various fields, including machine learning, natural language processing, computer vision, robotics, and expert systems. AI aims to create intelligent machines that can analyze data, make decisions, and solve complex problems, ultimately enhancing human capabilities and improving efficiency in various disciplines.

AI is not a substitute for human judgment and expertise, but rather a tool that can support and augment the decision-making process

In the context of ADR, AI refers to the application of technologies to assist in the resolution of disputes outside of the traditional court framework. It can be used to automate certain aspects of the ADR process, such as case management, document analysis, and decision-making; being key elements that attract parties to use the ADR framework as a mechanism for resolving disputes. For example, AI-powered chatbots can be used to provide initial information and guidance to parties involved in a dispute, helping them understand their rights and options. AI algorithms can also analyze large volumes of legal documents and precedents to provide insights and recommendations to ADR practitioners. Additionally, AI can be utilized to facilitate Online Dispute Resolution (ODR) platforms, as well as assist with mediation or arbitration of disputes between parties in a virtual environment.

By leveraging AI in ADR, the aim is to improve efficiency, reduce costs, and enhance access to justice. However, it is important to note that AI is not a substitute for human judgment and expertise, but rather a tool that can support and augment the decision-making process in ADR. Legal practitioners should therefore not worry about legal service extinction but rather, equip themselves to be relevant in today’s changing world of AI technology.

Read also: Chief Judge advises lawyers to embrace Alternative Dispute Resolution (ADR)

The author’s focus is therefore to interrogate the transformative potential of AI in the field of ADR, highlighting its benefits, challenges, and future prospects, which are as follows:

a. Predictive analytics: This is a branch of AI that employs algorithms and machine learning to analyze data and make predictions about future outcomes. Predictive analytics can be utilized to scrutinize data about past disputes, how they were adjudged, and a prediction of the outcome (judgment/Award) of cases with similar facts. This assists parties in deciding whether or not to pursue ADR, as well as the type of ADR mechanism to employ in resolving their dispute. In a 2017 study, a machine-learning statistical model correctly predicted the outcome of 70% (seventy percent) of 28,000 (twenty-eight thousand) United States Supreme Court decisions and 72% (seventy-two percent) of individual Justices’ votes from 1816 to 2015.

b. Assistive technologies: These technologies, as exemplified by platforms like Harvey, have been shown to significantly benefit ADR 3rd party Neutrals by simplifying processes, furnishing them with crucial informational resources, and expediting decision-making. Harvey, a large language model-based platform, has been instrumental in assisting Attorneys in various legal tasks, including contract analysis, due diligence, litigation, and regulatory compliance. These applications have resulted in faster, improved, and cost-effective recommendations and predictions, which attorneys can review and verify (Allen & Overy; 2023). This aligns with the core objective of ADR to offer a fair, efficient, and economical resolution process, as emphasized in the United Nations Commission on International Trade Law (UNCITRAL) Model Law 2006.

c. Automotive technologies: Situated at the other end of the spectrum from assistive technologies, is Automotive technologies. This has the capacity to partially or even fully automate discrete tasks, potentially replacing human neutrals in some specific instances. These tasks encompass automated negotiation, settlement, award, resolution plan drafting, and decision-making. Automotive systems can enhance access to justice for self-represented litigants by offering real-time and affordable legal advice and explanations (de la Rosa & Zeleznikow 2021). Furthermore, some studies suggest that individuals may find it easier to confide in an AI-based ADR system than a human neutral, often due to the anonymity and perceived absence of judgment or bias (Orr & Rule;2019). ADR participants frequently express concerns about neutral bias and may seek neutrals with differing nationalities to ensure impartiality (UNCITRAL Mediation Rules 2021). Automotive ADR systems may be perceived as less likely to exhibit partiality, even if this perception is not entirely accurate.

d. Online Dispute Resolution: More recently, digital technology has reshaped ADR into ODR. This is a form of dispute resolution that uses technology to facilitate the resolution of disputes between parties. In informal ODR, algorithms are used mainly in supporting parties’ own decision-making either in the initial diagnosis phase at the outset of the process, or later on in considering common outcomes in similar cases and circumstances on such matters as child support. Also, algorithms are sometimes used in a negotiation or mediation to assist parties in drafting court documents and in devising joint agreements based on their input in online exchanges. Notably, eBay and PayPal have developed ODR systems to handle the disputes that regularly arise on their platforms from and among Users. Realizing that they could not afford to hire enough human mediators to resolve all of these disputes or arrange for parties to video-conference with each other, these companies leveraged the extensive amounts of data they had collected on consumer behaviour and usage. Their ODR systems aim to prevent as many disputes as possible and to resolve the remainder quickly and amicably.

e. Efficient case management: AI-powered algorithms can streamline the case management process by automating administrative tasks, such as document review, case scheduling, and data analysis. This allows ADR practitioners to focus more on substantive issues and provide better assistance to the parties.

f. Enhanced decision-making: AI can assist in decision-making by analyzing vast amounts of data and identifying patterns, precedents, and legal principles. This may help Tribunals to make informed decisions and ensure fairness, consistency, and predictability in the resolution of disputes.

g. Improved Access to Justice: AI can bridge the access to justice gap by providing affordable and accessible ADR solutions. Virtual mediation platforms, powered by AI, can connect parties from different geographical locations, reducing the need for physical presence and associated costs. This promotes inclusivity and enables individuals and businesses to resolve disputes without significant financial burdens. Regrettably, some of the senior legal practitioners still insist on a physical trial, ostensibly to ‘study the demeanour of the witness’. This has often proved a denial of justice as critical witnesses to an arbitration may be far away in another jurisdiction but given the access, would have given useful evidence.

h. Neutral and impartial assistance: AI can provide neutral and impartial assistance to parties involved in the ADR process. By eliminating human biases, AI algorithms can provide objective guidance, helping parties understand their legal rights, obligations, and potential outcomes. This promotes a fair and balanced resolution of disputes. This is extremely useful to decision-makers in dispute resolution.

Read also: Kogi trains law officers on alternative dispute resolution

Whereas the above are the merits of AI technology in dispute resolution, there are some obvious demerits, some of which include:

a. Ethical considerations: The use of AI in ADR raises ethical concerns regarding privacy, data protection, and the potential for algorithmic biases. It is crucial to ensure that AI systems are designed and implemented with appropriate safeguards to protect the confidentiality of information and avoid discriminatory outcomes.

b. Human element: ADR processes often rely on the human element of empathy, emotional intelligence, and interpersonal skills. While AI can assist in various aspects, it cannot entirely replace the human touch required for effective mediation and negotiation. Striking a balance between AI assistance and human involvement is crucial to ensure successful outcomes.

c. Technological limitations: AI technologies are continually evolving, and their effectiveness in complex legal disputes is yet to be fully explored. The accuracy and reliability of AI algorithms in interpreting nuanced legal concepts and understanding human emotions remain areas of ongoing research and development.

Quite apart from resolving conventional disputes, AI technology has proven a useful and efficient tool in resolving trade disputes. For instance, the International Chamber of Commerce (ICC) used the 2018 World Trade Organization (WTO) Public Forum as the launch pad for an innovative technological tool- the Cognitive Trade Advisor (CTA), which is a pioneering AI-powered application designed to enhance trade negotiations. The CTA uses the understanding of natural language in order to provide cognitive solutions that can largely improve the way delegates prepare for trade talks and carry out their negotiations.

The new tool results from the work of the Intelligent Tech & Trade Initiative (ITTI), a project led by the ICC. According to Daniel Feffer, Chairman of ICC Brasil and founder of ITTI, “The use of AI will optimize and improve cooperation in trade negotiations. The work we carry out in bringing AI technology and trade closer together will have its outreach expanded with the development of tools such as the CTA. Not only are we focusing on interactions and discussions involving tech and trade, but we present pilot projects that can become the starting point for the constitution of an AI-intensive trade ecosystem”.

Artificial Intelligence holds immense potential to shape and enhance Alternative Dispute Resolution processes. By automating administrative tasks, providing objective guidance, and improving access to justice, AI can transform the way disputes are resolved. However, it is crucial to address ethical concerns, preserve the human element, and continue refining AI technologies to ensure their effectiveness and fairness. As AI continues to evolve, it is essential for ADR practitioners in Nigeria and Sub-Saharan Africa to embrace this technology and deepen their capacity for its use. This will create a more efficient, accessible, and just dispute resolution system; particularly as Nigeria has just revised its arbitration laws (the Arbitration and Mediation Act, 2022) with far-reaching innovative provisions contained therein.

To fully harness the transformative potential of AI in ADR, the collaboration between legal professionals, technologists, and Nigeria’s National Assembly members is essential. This collaboration will help address the challenges and ethical concerns associated with AI implementation in ADR, while also ensuring that the human element is preserved.

Tolu Aderemi is a Partner and Co-heads the Arbitration & ADR Practice of Perchstone & Graeys, LP.