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Mediation and AI: Balancing Benefits and Confidentiality

Mediation and AI: Balancing Benefits and Confidentiality

AI is rapidly changing how disputes are settled, making things faster and more data-driven. But there are big questions around privacy, especially in mediation. Philip Corsano’s article looks at both the positives and negatives of AI in dispute resolution, focusing on how it predicts risk and how to can keep things confidential.

Artificial Intelligence (AI) is transforming dispute resolution in the United Kingdom through the use of predictive models and machine learning algorithms. These technologies have the potential to improve the efficiency, cost-effectiveness, and data-driven nature of dispute resolution processes. However, the use of AI in dispute resolution also raises important ethical questions, particularly concerning the issue of confidentiality in mediation. This document explores the benefits and challenges of using AI in dispute resolution and proposes potential solutions to address ethical concerns.

Predictive Models of Human Risk Tolerances

Researchers at the University of Cambridge, in collaboration with the University of Zurich and the London School of Economics, have conducted a study on the use of machine learning to predict risk preferences (Kutbay, Sgroi, & Starkey, 2022). The study found that machine learning models could predict risk attitudes with an accuracy of up to 72% based on factors such as personality traits, time preferences, and financial literacy.

This type of predictive modelling has significant implications for dispute resolution in the UK, particularly in cases where parties have different risk tolerances. By using AI-powered predictive models, mediators can gain a deeper understanding of each party’s risk tolerances and tailor their approach accordingly. For example, mediators may adopt a more gradual approach for risk-averse parties and a more assertive approach for risk-tolerant parties.

Predictive Analytics and Machine Learning

In addition to predictive models of human risk tolerances, AI is also being used in predictive analytics to analyse historical data and inform decision-making in disputes. For example, researchers at UCL London and other universities have developed AI-powered tools that can analyse court decisions and identify key factors likely to influence case outcomes (Aletras et al., 2016; Medvedeva et al., 2020; Jur-E Project, 2021). These tools can provide parties and their legal representatives with a more data-driven approach to decision-making, complementing intuition and experience.

Ethical Concerns and Confidentiality

The use of AI in dispute resolution raises important ethical questions, particularly around the issue of confidentiality in mediation. Mediation relies on parties’ willingness to share sensitive information and explore creative solutions without fear of that information being used against them in future legal proceedings. The use of AI-powered tools in mediation may challenge this principle of confidentiality.

However, it is important to note that current AI analysis in dispute resolution primarily relies on publicly available court decisions, which does not pose a confidentiality issue. The relevance of AI-generated insights based on public data to specific mediation cases will depend on the distinctive facts of each case.

Addressing Ethical Concerns

To address ethical concerns surrounding the use of AI in dispute resolution, two main approaches have been proposed:

1. “Confidentiality by design”: This involves building privacy and security safeguards into the design of AI-powered tools from the outset. For example, predictive models could be trained using anonymized data, and the models could provide only aggregate insights rather than revealing information about individual cases or parties.

2. Informed consent: Parties in mediation should be fully informed about the use of AI-powered tools and given the opportunity to opt out if they have concerns about the privacy or security of their information. This could involve providing clear explanations of how the tools work, what data is being collected and analysed, and how that data will be used and protected.


The use of AI in dispute resolution in the UK has the potential to bring significant benefits in terms of efficiency, cost-effectiveness, and data-driven decision-making. However, it is crucial for the legal and dispute resolution community to carefully consider the ethical implications of these technologies, particularly concerning confidentiality in mediation.

By developing clear guidelines and protocols for the use of AI in dispute resolution and building privacy and security safeguards into the design of these tools, we can help ensure that the benefits of AI are realized while also protecting the fundamental principles of trust, confidence, and confidentiality essential for successful dispute resolution. As the use of AI in dispute resolution continues to evolve, it will be important for all stakeholders to work together to find a balance between the potential benefits of these technologies and the need to uphold confidentiality and the highest ethical standards in the delivery of legal and dispute resolution services.

An MBA graduate from London Business School, and the Stanford Decision Science Programme. Philip graduated from the  University of London Law LLB, with Maritime & Banking LLM’s. He was an executive director in a premier Merchant Bank and a director at IBM for Eastern Europe & Asia. He was called to the Bar in 2024 he is a resident expert in business mediation. In 1996-2000 he was a diplomat in Moscow dealing with direct investments. He is highly motivated to find creative solutions for many conflictual situations.

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