Artificial Intelligence In Alternative Dispute Resolution - A Comparative Study

Author: LawSphereX

Category: Arbitration & ADR

Published: 2026-08-23T18:17:50.06763+00:00

Updated: 2026-08-26T17:12:02.012+00:00

ARTIFICIAL INTELLIGENCE IN ALTERNATIVE DISPUTE

RESOLUTION: A COMPARATIVE STUDY

Ms. Shivangi Sharma, Gautam Buddha University Mr. Pawan Yadav, Gautam Buddha University

ABSTRACT

The emergent growth of Artificial Intelligence (AI) is in process of reshaping how Alternative Dispute Resolution (ADR) works, especially in terms of mediation and conciliation. This paper provides focus at two emerging new approaches. The first being the AI assisted mediation, where the tools of AI are used to emphasise the work of mediators. And the second being the AI led mediation, meaning where the AI will act like a mediator where the algorithms are written in such a way that the AI take the role of a facilitator who can even help in resolving disputes. By using a perspective which is legal as well as comparative, the paper examines as to how these models are addressed across India, the United States of America, Singapore as well as Europe.

Exploring the benefits of AI in Alternative Dispute Resolution, as improved efficiency and better access to justice simultaneously highlighting the concerns it raises. It also includes questions in terms of neutrality, due process, transparency and accountability. The main emphasis is given to India's Mediation Act, 2023 as to how well it assesses and handles the incorporation of AI into Dispute Resolution processes. The major argument is that even though the AI has the potential to transform ADR, its usage needs to be regulated by a strong framework, and by stating clear ethical standard and design approach which keeps human values as the focal point. Keywords: Artificial Intelligence, Alternative Dispute Resolution, Mediation Act 2023, Online Dispute Resolution, Algorithmic Neutrality, Comparative Law, Access to Justice, Algorithmic Accountability.

INTRODUCTION

The global system in the entire world is facing an intense and growing crisis of the caseload. The courts around the globe, starting from Indian courts which are heavily burdened to Europe and their Arbitral Tribunals are all struggling from increasing backlogs, exponentially rising costs and the continued inaccessibility of justice for many more. The mechanisms of Alternative Dispute Resolution especially Mediation and conciliation have been developed as a response to these challenges. Their aim is mainly to provide a consensual, cost effective and a path which is timely when we talk about resolving disputes outside the court system. In terms of all these issues AI has begun to play a crucial role.

Tools which are well known at this point such as Predictive analytics platforms such as Lex Machina and Westlaw Edge, and for automated contract review systems and Online Dispute Resolution (ODR) platforms for example, Modria and Smartsettle are increasingly becoming a part of how legal processes are carried out. 1 This rapidly increasing intersection of AI along with ADR raises questions such as can AI truly remain neutral? Is AI truly capable of managing human interactions involved in mediation? When the disputes are influenced what are its implications for the due process which are decided by algorithms? How exactly are the legal systems of different places responding to these developments? This paper seeks to explore these major issues.

Structure of this paper would entail: Part II provides a conceptual overview of mediation and AI; Part III examines AI-assisted mediation tools; Part IV analyses AI-led or autonomous mediation models; Part V conducts a comparative analysation of the legal frameworks in India, the EU, the US, and Singapore; Part VI identifies key challenges and ethical concerns; and Part VII offers conclusions and

recommendations.

II. CONCEPTUAL FRAMEWORK: MEDIATION, ADR, AND ARTIFICIAL

INTELLIGENCE

2.1 Overview of Mediation and Conciliation

1Ethan Katsh & Orna Rabinovich-Einy, Digital Justice: Technology and the Internet of Disputes 45 (Oxford University Press 2017).

Mediation is a voluntary, confidential and non-adjudicatory process which has a neutral party, known as the mediator, facilitates dialogue between disputing parties to help them reach a mutually acceptable settlement. 2 It is a process which is different from arbitration and litigation as it places emphasis on Party Autonomy and its non-binding nature of mediator's role. The mediator simply cannot impose their decision but can only assist the parties in reaching to a resolution. Then comes Conciliation which is a similar process and can be used interchangeably with the process of mediation in a lot of jurisdictions. 3 Although, it involves an active role for the conciliator,4 that includes their ability in suggesting the terms of settlement.

In India, conciliation comes under Part III of the Arbitration and Conciliation Act, 1996, and on the other hand Mediation Act, 2023 establishes a separate statutory framework specifically for mediation. 5

2.2 Definition of AI Technology

Artificial Intelligence refers to computational systems that can perform tasks which would typically require human intelligence. 6 So in legal terms, essential capabilities such as Natural Language Processing that enables a machine in understanding and generating the human language. Then comes Machine Learning which lets the systems learn and improve automatically from its experience and uses older data in figuring out outcomes. Considering the purpose of this paper, the use of AI in ADR can be understood through two models. The first model is the AI assisted mediation, where the roles of the human mediators are not replaced and the mediators use technological tools for the process of mediation. And the second model is an AI led mediation, where the systems operate with a high level of autonomy in facilitating and even resolving disputes with no involvement from a human mediator.

2Laurence Boulle, Mediation: Principles, Process, Practice 3 (3d ed. 2011). 3Nadja Alexander, International and Comparative Mediation: Legal Perspectives 78 (Kluwer Law International 2009). 4UNCITRAL Conciliation Rules, art. 7 (1980). 5The Mediation Act, No. 32 of 2023 (India). 6Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach 1 (4th ed. 2020).

III. AI ASSISTED MEDIATION AND THE HUMAN MEDIATOR

3.1 Tools and Their Platforms

Mediation that is assisted by AI includes a wide range of technologies designed to improve the efficiency of the mediator while at the same time preserving the judgement by a human. These tools can be grouped in the form of document analysis and preparation tools, sentiment and communication analysis tools, negotiation support systems and Online Dispute Resolution Platforms. Document analysis tool uses the natural language processing for reviewing and summarising large volumes of case data that allows the mediator in identifying key facts, points on which the dispute took place and the areas of agreement. Platforms such as Kira Systems majorly rely on Machine Learning models that are trained at extracting data and organising obligations and clauses that are contested.

7 Sentiment Analysis Tools, these are also based on Natural Language Processing, they help in tracking the emotional tone of communication at the time of mediation. There are systems that can detect patterns those suggest frustration, mistrust or openness such as Cogito and IBM Watson Tone Analyzer,8 they help mediators identify moments of tensions or any progress by detecting the patterns. There are systems which can even support Negotiation, such as Smartsettle ONE, it applies algorithms to figure out certain zones for agreement by merely analysing the preferences and priorities which have been shared by the parties earlier. 9 Analysis of this form can clearly give a picture of practical solutions which can emerge through negotiations of the traditional form.

3.2 Online Dispute Resolution Platforms

Online Dispute Resolution Platforms are the most developed and widely implemented form of AI assisted Alternative Dispute Resolution.10 These platforms integrate two communication tools known as synchronous and asynchronous which are AI driven for management of cases, document generation and in few cases, algorithmic negotiation support. Modria which is now 7Kira Systems, How AI Is Transforming Contract Review (2023), https://www.kirasystems.com (last visited Apr. 15, 2026). 8IBM Watson, Tone Analyzer Documentation (IBM Cloud 2023), https://cloud.ibm.com (last visited Apr. 15, 2026). 9Ernest Thiessen & Joseph McMahon, Beyond Win-Win in Cyberspace, 15 Ohio St. J. on Disp. Resol. 643, 647 (2000). 10Colin Rule, Online Dispute Resolution and the Future of Justice, 1 World Arb. & Mediation Rev. 1, 4 (2020).

part of Tyler Technologies, handles a huge sum of disputes each year for companies such as eBay, PayPal and a few other government agencies. In India platforms such as SAMA and the Ombudsman Scheme of the Reserve Bank of India makes use of the Online Dispute Resolution mechanisms for handling financial disputes.11 The e-filing system of the Supreme Court and initiatives by the National Internet Exchange of India also reflects a broader institutional shift towards the use of technology in dispute resolution. Online Dispute Resolution which is assisted by AI helps in reducing transactional cost, removes barriers related to geography and speeds up the timeline of the resolution. The benefits shared earlier are of much importance in the Indian context, where access to justice can be limited in rural areas and where cross border commercial disputes are beginning to get common.

IV. AI LED MEDIATION AND AUTONOMOUS DISPUTE RESOLUTION

4.1 The Autonomous Mediator in Concept and Practice

The idea of an AI system that acts as an autonomous mediator, and is capable of independently handling the process of mediation, assessing the positions of the parties as well as suggesting or deciding outcomes, marks an advanced and often used stage in the use of AI in Alternative Dispute Resolution.12 Unlike other models, these systems not merely support human mediators but begin to take on functions that have depended on human judgement and interaction earlier.13 A practical example of this can be seen in blind bidding algorithms used by platforms such as

Cybersettle and ClaimsPilot. Here, parties submit their settlement figures confidentially, and the system determines whether there is a possible overlap or midpoint that can resolve the dispute. While these mechanisms are relatively simple, they offer an early glimpse into how AI can independently facilitate resolution. Meanwhile, more complex methods are starting to come to the fore. For example, the small Claims online dispute resolution platform of the European Union guides disputes to appropriate resolution paths with the help of AI-based decision trees. But academic research has advanced 11SAMA, Online Dispute Resolution Platform (2023), https://www. sama. live (last visited Apr. 15, 2026). 12Ethan Katsh & Colin Rule, What We Know and Need to Know About Online Dispute Resolution, 67 S. C. L. Rev. 329, 341 (2016).

13David Allen Larson, Technology Mediated Dispute Resolution (TMDR): A New Paradigm for ADR, 21 Ohio St. J. on Disp. Resol. 629, 640 (2006).

these limits as well. Researchers at the University of British Columbia's Centre for Digital Media have found that AI systems can manage negotiations involving multiple issues and balance conflicting priorities with a style that starts to look more like complex human decision making.

4.2 Critical Assessment of Whether AI Can Replace the Human Mediator

AI cannot replace the human mediator at least not yet. With the quick growth of AI, however, it is significant to explore this question in detail from a long-term point of view. Mediation, as a human process, relies a lot on qualities such as empathy, intuition, cultural awareness, and the ability to navigate the emotional and relational aspects of conflict. No matter what cutting edge algorithm we are discussing, it just has not had the ability to truly mimic these attributes. Additionally, mediation is only legitimate based on not only the result but also the process by which that result is achieved. Compliance to outcomes, as Tyler's research demonstrates, more closely reflects an experience of procedural fairness than the quality of the outcome.

14 When the decision-making process is affected by systems that are not easy to understand, this sense of fairness can be diminished even though the outcome may feel justifiable. AI led resolution has potential for use in certain kinds of disputes that are both feasible and beneficial. For tasks that are routine, repetitive, and standardized, like processing claims for routine car repairs, routine ticketing, or mundane complaints, AI systems can be more efficient and time-saving than human agents. The concept of better framing is not replacement but can be termed as functional substitution within a carefully bounded dispute category.

V. COMPARATIVE LEGAL ANALYSIS

5.1 India and the Mediation Act 2023 in the Evolving ODR Landscape

The Mediation Act, 2023 is a step towards the positive recognition of mediation in the Indian legal framework. Now, pre-litigation mediation is compulsory, the Mediation Council of India is in place as a regulatory body and section 35 provides for online mediation for the first time in a formal manner.15 All of these are a clear step towards modernisation of dispute resolution making it even more accessible. Meanwhile, the Act fails to answer an important question it 14Tom R. Tyler, Why People Obey the Law 94 (Princeton University Press 2006). 15The Mediation Act, No. 32 of 2023, § 35 (India).

does not address Artificial Intelligence at all. The guidance does not specify whether mediators may use AI tools, how settlement suggestions using algorithms should be handled, or who would be liable in case of any mistake made by the AI driven platform. That silence is not a drafting error; it is a real gap in the regulations. Some progress on the policy front. In 2020, NITI Aayog and the ODR Committee constituted under the Ministry of Law and Justice had identified AI's role in dispute resolution and called for its utilization. 16 They did not go so far as to establish specific legislation or protection, however. It is because of that that India has been born into the lap of a technology which will yet learn to govern. The Supreme Court's SUPACE platform is an example of the judiciary's current efforts to use AI. 17 SUPACE does not decide outcomes it provides information to judges.

It is a balanced and cautious approach that sees technology used as a tool in the legal process, but with human judgment at the heart of it all.

5.2 European Union and the AI Act in the Context of ODR Regulation

The European Union has adopted a fairly structured and future-oriented approach to regulating Artificial Intelligence with the AI Act, which entered into force on 1 August 2024. 18 Rather than applying the same standards to all AI systems, it categorises them according to the amount of risk that they pose, from "minimal risk" to "unacceptable risk. " The aspect relevant here is that AI in the administration of justice and dispute resolution is categorised into the high risk category. 19 The reasoning here is straightforward systems capable of moulding legal outcomes should carry the regulatory burden. Consequently, they must be more rigorously protected, such as in their design, testing, data reliability and validity, transparency in decision making and human oversight.

In parallel, the ODR Regulation was in place in the European Union, establishing an online platform for consumers' disputes. 20 This system implements algorithm-driven tools to enhance 16Ministry of Law and Justice, Report of the Committee on ODR 22 (Gov't of India 2021). 17Supreme Court of India, SUPACE: Artificial Intelligence Research Portal (2021), https://sci. gov. in (last visited Apr. 15, 2026). 18Commission Regulation (EU) 2024/1689, Artificial Intelligence Act, 2024 O. J. (L 1689) 1. 19Id. , Annex III, para. 8. 20Commission Regulation (EU) No 524/2013, Online Dispute Resolution for Consumer Disputes, 2013 O. J. (L

165) 1.

the organisation and management of cases. The combination of the ODR Regulation and the AI Act reveals a balanced approach: the EU is not seeking to prohibit or unconditionally permit AI in ADR, but rather to balance innovation with accountability and fairness.

5.3 United States and Its Sectoral and Decentralised Approach

The approach taken by the United States in the field of AI regulation has been more flexible and less centralised, particularly in comparison with the European Union. The regulation is not one single, unified law, but is instead a product of several sector-specific regulations, statelevel initiatives, and policy guidance like the NIST AI Risk Management Framework released in 2023. 21 Current laws, such as the Federal Arbitration Act and the Uniform Mediation Act, address the broad topics of arbitration and mediation respectively, but do not explicitly reference AI. Despite this, its use is a topic that is gaining traction. The American Bar Association has made some moves in its task force on law and artificial intelligence, providing guidance on responsible use of AI in the practice of law.

22 Meanwhile, states like California and Illinois have enacted legislation that mandates increased transparency in automated decision making procedures. In practice, the United States has become a major centre for AI driven dispute resolution. There are platforms available such as Modria, Resolver, and Cybersettle, which deal with a vast number of disputes on a yearly basis. The market has moved faster than the law and gaps of accountability are not hypothetical, particularly in situations where clear and consistent legal safeguards are still evolving.

5.4 Singapore and Its Role as a Global ADR Hub with SMC's Technology Initiatives

Singapore has emerged as the premier hotspots in the Asia Pacific region for Alternative Dispute Resolution. The Singapore International Arbitration Centre and Singapore International Mediation Centre are well known for their handling of high value cross-border disputes. The Convention on International Settlement Agreements Resulting from Mediation (Singapore Convention on Mediation, 2019)23 is yet another testament to Singapore's robust 21Nat'l Inst. of Standards & Tech. , Artificial Intelligence Risk Management Framework (AI RMF 1. 0) (U. S. Dep't of Commerce 2023). 22Am. Bar Ass'n, ABA Task Force on Law and Artificial Intelligence: Guidance Notes (2023), https://www. americanbar. org (last visited Apr. 15, 2026). 23United Nations Convention on International Settlement Agreements Resulting from Mediation (Singapore Convention on Mediation), opened for signature Aug. 7, 2019, U. N. T.

S. 3 (entered into force Sept. 12, 2020).

support for mediation as a crucial tool in international commercial dispute resolution. Singapore has also been actively pursuing the technological incorporation of its ADR system in recent years. The Singapore International Mediation Centre has introduced an online mediation protocol, and the Singapore Court has undertaken an eLitigation system, both of which indicate a move towards digital-first dispute resolution processes. Singapore has a Model AI Governance Framework, published by the Info-comm Media Development Authority in its second edition in 2020,24 which offers clear, voluntary guidance on responsibly using AI. It is not legally binding, but provides guidance with regard to key principles which could be used when dealing with Online Dispute Resolution Platforms, particularly transparency, fairness and accountability.

Singapore's model is all about making a strategic choice for agility instead of rigidity in its institutions. Instead of relying on strict and prescriptive legislation, it favours soft law instruments, institutional guidelines, and industry standards to govern the use of AI.

5.5 Comparative Summary

India can be seen as progressive because of the Mediation Act 2023 which has bolstered the mediation framework and acknowledged online mediation processes. However, there is no specific governance for Artificial Intelligence, leaving a regulatory void especially in light of the growing role of AI in dispute resolution. The European Union, on the other hand, has the most detailed and organised framework in the shape of the AI Act. The categorisation system of risk levels assigns high-risk status to AI systems for dispute resolution, meaning there are strong requirements for transparency, accountability and human oversight. The United States has a more sector based approach, decentralised and market-oriented approach. There are State, Federal, and professional guidelines, with innovation growing rapidly, albeit not necessarily with consistent safety frameworks.

Singapore follows a soft and flexible approach with standards being set voluntarily and institutional guidance. This strategy allows innovation to flourish while ensuring responsible use of AI, and relies primarily on compliance without legal obligations. 24Infocomm Media Dev. Auth. (IMDA), Model AI Governance Framework (2d ed. 2020) (Gov't of Singapore).

All the models have their own contradictions. The European Union provides robust protection, but can stifle innovation. The United States promotes the rapid development of technology but has concerns about consistency and protection. While Singapore is flexible, it may have weak enforcement mechanisms. Although India has been progressive in promoting mediation, it does not currently have any answers to important questions regarding AI, potentially leaving parties vulnerable to uncertainty. India does not need to transplant any given model, but rather a careful mixing and matching which is done with a clear purpose and with cognizance of its own social and institutional realities, informed by the EU's structured risk-based regulation model, Singapore's institutional flexibility and India's focus on party autonomy and readily available dispute resolution.

VI. CHALLENGES AND ETHICAL CONCERNS

6.1 Algorithmic Bias and Neutrality

Neutrality is not simply a professional expectation in mediation, it is a condition upon which the entire process derives its legitimacy. An AI system trained on pre-existing dispute data may sustain and amplify existing biases embedded in that data. Certain studies have documented racial and gender bias in algorithmic decision making systems across multiple domains, from criminal sentencing to insurance pricing.25 A system cannot neutralise existing inequalities it can industrialise them. For India specifically, given profound socioeconomic and gender asymmetries among disputants, the risk of AI bias is acute. A system which is optimised on commercial litigation data will mostly perform poorly when confronted with the family, land or community disputes which dominate India's mediation docket.

6.2 Transparency, Explainability, and Due Process

Amongst all the challenges AI poses to dispute resolution, the problem of opacity commonly known as the "black box" might be the most difficult to engineer away.26 In many AI systems, especially those based on complex machine learning models, it can be difficult to understand 25Julia Angwin et al., Machine Bias, ProPublica (May 23, 2016), https://www.propublica.org (last visited Apr. 15, 2026). 26Frank Pasquale, The Black Box Society: The Secret Algorithms that Control Money and Information 8 (Harvard University Press 2015).

how a particular outcome or recommendation has been reached. Due process at its base requires that the parties understand why an outcome has been reached, a requirement which opaque algorithmic systems are unable to satisfy. When the reasoning behind an outcome cannot be clearly explained, this expectation is weakened in practice. The European Union AI Act attempts to respond to this concern through requirements related to explainability and meaningful human oversight. These provisions aim to ensure that AI systems used in sensitive areas, including dispute resolution, remain transparent and subject to human review. However, even with such safeguards, technical tools designed to explain AI decisions, such as LIME and SHAP, have their limitations.

In reality, what these tools produce are estimations that satisfy technical auditors but mean very little to a disputant sitting across a screen trying to figure out why the system ruled against them.

6.3 Confidentiality and Data Security

For the parties to speak candidly there is a need of confidentiality, and without candour, mediation loses its advantage over litigation. The Mediation Act, 2023 enshrines this in section 22, prohibiting disclosure of mediation communications.27 AI-driven ODR platforms, however, aggregate and process sensitive personal and commercial data. The risk that sensitive mediation data could be extracted and recycled without any party's knowledge is neither remote nor theoretical. India's Digital Personal Data Protection Act, 2023 provides a baseline data protection framework, but does not address the specific confidentiality norms applicable to ADR data. A sector-specific data governance standard for ADR platforms is way overdue.

6.4 Access to Justice and the Digital Divide

The access to justice promise of AI-powered ADR is genuinely strong on paper lower in cost, no geographical requirement, no fixed hours. In principle, it can make the system faster, more efficient and more widely accessible. However, this promise depends heavily on meaningful digital access. In India, while internet penetration has increased considerably in recent years, access remains uneven.28 There are still clear disparities between rural and urban regions, as 27The Mediation Act, No. 32 of 2023, § 22 (India); see also The Digital Personal Data Protection Act, No. 22 of

2023 (India).

28Telecom Regulatory Auth. of India, Telecom Subscription Data (Mar. 2026), https://www.trai.gov.in (last

well as gaps linked to gender and socioeconomic status. This means that AI-powered ADR systems can be out of reach for those who are not digitally connected and literate. In this way, the "justice gap" that AI is supposed to fill could expand even more. Without access to technology, people may be further disadvantaged by their inability to access efficient mechanisms for settling disputes, thus adding to the disadvantages they already experience.

6.5 Accountability and Legal Liability

In the case of a wrong that occurs in a complex AI system, the person who is responsible for it is not clearly stipulated in India under the current legislation and even in many other jurisdictions the question is not yet settled. This leads to a basic question of accountability for the use of AI to resolve disputes. The European Union AI Act seeks to solve this by sharing responsibilities among various players in the life cycle of AI. It imposes obligations on both the provider and the deployer of AI systems and establishes a chain of accountability. This makes it clearer who may be held responsible depending on how and where the failure occurs. In contrast, India's current legal framework does not provide a comparable system for allocating liability in cases involving AIdriven ADR.

As a result, if harm arises from an AI system used in dispute resolution, affected parties may face uncertainty in identifying who is legally responsible and how redress can be obtained.

VII. RECOMMENDATIONS AND CONCLUSIONS

7.1 Recommendations

The first is the need for a framework that is purpose-built for AI in ADR not aspirational policy language but a framework that has teeth in order to govern the use of AI in ADR. This can be introduced either in the form of subordinate legislation under the Mediation Act, 2023 or in the form of formal guidelines by the Mediation Council of India. A system for the classification of AI-based ADR tools by risk level could be adopted from the European Union model. It should also specify the transparency and explainability requirements for any AI implemented in mediation and provide safeguards ensuring AI is used in a supportive, not supplementary visited Apr. 15, 2026).

manner, particularly in complex cases, requiring human oversight. Moreover, it should define how to distribute responsibility if errors are made in the use of AI. Second, access to dataset diversity must not be left to the discretion of platform developers but must be a pre-condition for regulatory certification, which must be in keeping with India's social and cultural diversity. Independent audits of these systems should be required and conducted by a regulatory agency or independent third party firms, especially with regards to online dispute resolution platforms in the country, to mitigate potential bias issues. Third, the inclusivity target falls if the people who need these systems the most are unable to access the infrastructure needed for AI-powered ADR.

Investment in public digital infrastructure and making platforms accessible and easy to use is therefore an important complement to legal reform. Fourth, India needs to be actively involved in the creation of international standards relating to AI in dispute resolution. Forums like the UNCITRAL Working Group III on Online Dispute Resolution29 and mechanisms related to the Singapore Convention would facilitate greater convergence with international practices. The more that AI-driven resolution moves to operate across jurisdictions, the less affordable it becomes to be outside norm-setting discussions.

7.2 Conclusions

AI in mediation and ADR is neither a dystopian threat to justice nor a utopian solution to the caseload crisis. The regulatory decisions made surrounding these developments and their impacts are the ones that define these outcomes. The model that is most immediately viable and legally defensible is AI-assisted mediation, which helps human mediators but does not replace them. While AI-led mediation could be suitable for specific types of low complexity cases, it demands strong precautions against bias, lack of transparency, and accountability before it can be broadly adopted. India is at a critical juncture. Building upon such a sound institutional base, the Mediation Act, 2023's challenge is to create an AI governance architecture that is forward looking, rights protecting and contextually appropriate.

The lessons to be learnt from the experiences of the 29UNCITRAL Working Group III (Online Dispute Resolution), https://uncitral. un. org (last visited Apr. 15, 2026).

EU, the US and Singapore are relevant, but none of them can be blindly emulated in India's legal, social and technological context. Ultimately, the value of AI in ADR lies less in efficiencies and more in its role in achieving justice. A disputant is not a data point to be optimised around, and a framework that is not aware of that has not yet passed its most basic test.

BIBLIOGRAPHY

Primary Sources Legislation The Mediation Act, No. 32 of 2023 (India). The Arbitration and Conciliation Act, No. 26 of 1996 (India). The Digital Personal Data Protection Act, No. 22 of 2023 (India). Commission Regulation (EU) 2024/1689, Artificial Intelligence Act, 2024 O. J. (L 1689) 1. Commission Regulation (EU) No 524/2013, Online Dispute Resolution for Consumer Disputes, 2013 O. J. (L 165) 1. International Instruments United Nations Convention on International Settlement Agreements Resulting from Mediation (Singapore Convention on Mediation), opened for signature Aug. 7, 2019, U. N. T. S. 3 (entered into force Sept. 12, 2020). UNCITRAL Conciliation Rules (1980). Secondary Sources Books Alexander, Nadja. International and Comparative Mediation: Legal Perspectives. Kluwer Law International, 2009. Boulle, Laurence. Mediation: Principles, Process, Practice. 3d ed.

LexisNexis Butterworths, 2011. Katsh, Ethan & Orna Rabinovich-Einy. Digital Justice: Technology and the Internet of Disputes. Oxford University Press, 2017. Pasquale, Frank. The Black Box Society: The Secret Algorithms that Control Money and Information. Harvard University Press, 2015. Russell, Stuart & Peter Norvig. Artificial Intelligence: A Modern Approach. 4th ed. Pearson, 2020. Tyler, Tom R. Why People Obey the Law. Princeton University Press, 2006.

Journal Articles Katsh, Ethan & Colin Rule. What We Know and Need to Know About Online Dispute Resolution, 67 S. C. L. Rev. 329 (2016). Larson, David Allen. Technology Mediated Dispute Resolution (TMDR): A New Paradigm for ADR, 21 Ohio St. J. on Disp. Resol. 629 (2006). Rule, Colin. Online Dispute Resolution and the Future of Justice, 1 World Arb. & Mediation Rev. 1 (2020). Thiessen, Ernest & Joseph McMahon. Beyond Win-Win in Cyberspace, 15 Ohio St. J. on Disp. Resol. 643 (2000). Reports and Other Sources Angwin, Julia et al. Machine Bias. ProPublica, May 23, 2016. https://www. propublica. org. Infocomm Media Development Authority (IMDA). Model AI Governance Framework. 2d ed. Government of Singapore, 2020. Ministry of Law and Justice. Report of the Committee on ODR. Government of India, 2021. National Institute of Standards and Technology.

Artificial Intelligence Risk Management Framework (AI RMF 1. 0). U. S. Department of Commerce, 2023. Supreme Court of India. SUPACE: Artificial Intelligence Research Portal. 2021. https://sci. gov. in. Telecom Regulatory Authority of India. Telecom Subscription Data. March 2026. https://www. trai. gov. in.