Role Of Artificial Intelligence In Reaching Mediation Settlements - Challenges And Opportunities
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ROLE OF ARTIFICIAL INTELLIGENCE IN REACHING
MEDIATION SETTLEMENTS:
CHALLENGES
AND OPPORTUNITIES Sagar, Research Scholar, Amity Law School, Amity University Noida Introduction Where there is society, there will be disputes1This is a well-established fact that, no matter the causes, society eventually calls for some conflict between individuals. The conflicts can arise out of personal, professional, social, moral or purely commercial reasons, but their existence cannot be avoided. In a situation where dispute is the only constant, to preserve societal integrity, it is important to establish an efficient and conclusive justice delivery system. 2 Catering to this requirement, India has established a robust judicial system that finds its roots in the Constitution of India. But the robust judicial structure eventually faced severe problems due to its rigid nature.
While the Indian judiciary garnered a lot of public trust through its years of existence and justice delivery, such trust eventually led to people becoming more aware of their rights and trusting the judiciary in preserving and protecting their rights. While this was a welcome development but with the public becoming increasingly litigious, the judiciary as an institution had to double its efforts. The trend continued till the point where the judiciary started feeling overburdened by the litigants, and a backlog of cases started piling up that the judiciary, with its ever-expanding infrastructure and workforce, was not able to handle. This resulted in public trust transforming into public dissatisfaction. 3.
To cope with this situation, Alternative Dispute Resolution (Hereinafter “ADR”) Mechanisms were introduced to reduce the burden on the judiciary and to better preserve the societal structure. Even among the multiple ADR mechanisms that were introduced, Arbitration was best received by the public and was not widely adopted. Recently, with the enactment of The Mediation Act, 2023, there is hope for Mediation to pick up pace with the adversarial system and arbitration mechanisms 1 Williams, R. M. , Social Order and Social Conflict, 114(3) Proceedings of the American Philosophical Society (1970), 217–225. 2 Nur Khalidah Dahlan, Mohammad Al-Saifee Aziz Azman, et. Al. , Online Mediation: Issues, Applications and Challenges, 5 Asian Journal of Research in Education and Social Sciences 81 (2023).
3 Report On Strategic Plan For Implementation Of Ict In Indian Judiciary 1 (2005), available at
http://indianjudiciary. nic. in/images/main. pdf. to integrate itself with the justice delivery system. With mediation having a root in our cultural ethos4 It is believed to deliver socially adhesive decisions. However, giving due respect to the efforts put in by Judges and staff across the judicial system in India, we have 4. 48 Crore cases. 5 (Source: National Judicial Data Grid) pending before the judicial system. We need to accept the inherent limitations that individuals acting as judges are subject to; such individuals cannot be expected to work beyond their natural limits at the cost of their health and life.
On the other hand, as the famous quote provides, “Justice delayed is Justice Denied”6While it is not possible to dramatically expand the judicial infrastructure, nor is it possible to demand more from the individuals already working in the system, the best course of action would be to supplement the efforts of the system through the use of technology. 7 Integration of Information and Communication Technologies (Hereinafter “ICT”) has been an ongoing process for the Indian judiciary, with E-stamp paper, e-filing systems, ecourts and Video conference hearings. ICT has become part and parcel of the Indian judiciary. This has allowed the judiciary to significantly reduce its workload, especially in procedural and administrative matters.
With an intent to utilise the latest technology for the benefit of judicial systems, we can explore the utility of Artificial Intelligence (Hereinafter “AI”) in helping the judicial system, specifically in the mediation process, as it lacks the rigid procedure and formalities of the adversarial system. A Brief History of the Development of Mediation in India In ancient times, India had its system of dispute resolution in the form of panchayats. The chief idea was to resolve any disputes in the presence of respectable members of the society. The decisions of panchayats were not based on pre-written rules and regulations; rather, they were governed by the prevalent norms of expected behaviour. In such a practice, the end goal of justice was to reach a compromise, and punishment was the exception.
Even after the incorporation of a formal Court system by the Britishers, panchayats continued to operate as the recognised institutes of administration of justice. However, these institutions had their
4 Mahabharata an early attempt at mediation, mediation embedded in Indian ethos
CJI NV Ramana, BARANDBENCH (28th August 2024) https://www.barandbench.com/news/litigation/mahabharata-mediationindian-ethos-cji-nv-ramana-india-singapore-mediation-summit. 5 National Judicial Data Grid (Sept. 5, 2024 10:35 AM) https://njdg.ecourts.gov.in/njdgnew/index.php.
6 Library Of Cong., A Dictionary Of Quotations 183 (2010).
7 Anjanette H. Raymond & Scott J. Shackelford, Technology, Ethics, and Access to Justice: Should an Alogrithm be Deciding Your Case? , 35 Mich. J. Int'l L. 485 (2014). limitations as they were restricted by the territory in which the disputants resided and could no longer deal with the complex claims of trade and property matters. As such, over time, the institutions got relegated to just dealing with small civil disputes and the rest of the matters were handled by the formal Courts. CJI NV Ramana correctly noticed, “Mahabharata is an early attempt at mediation, mediation embedded in Indian ethos. "8 It's not that ADR has been removed from the Indian legal system; it just took a more formal shape through the Arbitration and Conciliation Act, 1996.
Coupled with the enabling provisions of CPC, the Arbitration and Conciliation Act has been the parent legislation of ADR activities in India, but its shortcomings soon came to light as arbitration proceedings became more complex and closely resembled the adversarial system, which it was supposed to supplement with an informal procedure. To further reduce the burden on Courts and now on arbitral tribunals, Lok Adalats were introduced, but they are only effective in small suits. A feasible alternative to the Court system and the encumbered arbitration tribunals is the mediation mechanism. Mediation is an informal method of dispute resolution that allows for a neutral third party to facilitate dialogue between disputants, and the compromise thereof is reduced into writing to give it legal sanctity.
Mediation is completely informal, and the parties define the parameters within which the mediation process will operate. In India, mediation as an alternative to litigation is still unexplored in most cases because of the strong trust the Indian Judicial System has developed over the years. Arbitration was able to garner support from the public due to its close resemblance to the adversarial system. 9But mediation does not offer the same trust. The main feature of mediation lies not in its informal nature but rather in its confidentiality. Because no umbrella legislation can deal with mediation in India, Courts have invoked Section
89 of the Code of Civil Procedure (1908) to implement mediation as a practical ADR
mechanism. In 200510The Supreme Court of India constituted a committee that brought forward suggestions to better implement Section 89 to provide justice that is accessible to all.
8 Mahabharata an early attempt at mediation, mediation embedded in Indian ethos
CJI NV Ramana, BARANDBENCH (28th August 2024) https://www.barandbench.com/news/litigation/mahabharata-mediationindian-ethos-cji-nv-ramana-india-singapore-mediation-summit. VIRENDRA AHUJA, The Singapore Convention on Mediation and India, https://www.researchgate.net/publication/372419398.
10 Salem Advocate Bar Association v. Union of India, AIR 2005 SC 3353.
The Model Rules brought forward by the committee allowed various High Courts to draft their own rules about the implementation of mediation under their domains. Again in 201011, the Supreme Court reviewed the application of Section 89 and concluded that, wherever possible, Courts shall refer the cases to ADR and gave guidelines for the same. To further expand the scope of mediation, the Supreme Court12 also provided that a few criminal cases can also be referred to mediation if the conditions are appropriate according to the Court13. All this eventually culminated in the enactment of The Mediation Act, 2023, with provisions that allowed for formalising Mediation in India along with introducing provisions for the efficient use of ICT.
Online Dispute Resolution Systems in India Online Dispute Resolution (Hereinafter “ODR”) refers to the active use of technology to facilitate dispute resolution. Ergo, ODR was limited to facilitating ADR mechanisms over cyberspace, and they primarily played the role of enabler through the use of video conferences, document exchange and verification through online modes, signing agreements online and other such activities. However, to limit the benefits of ODR to a mere electronic form of ADR will be mis-categorising the benefits that ODR processes provide over ADR. ODR not only resolves the procedural difficulties but also decreases such difficulties before a case reaches the resolution stage. 14 ODR helps the parties involved understand the risks involved in the process.
Further, ODR allows for the digital filing of documents that not only helps manage documents easily but also streamlines the submission process for the parties involved. 15 The process to which parties are subjected results in a form of mental harassment by itself, and ODR helps in avoiding the majority of such hassles, thereby establishing stronger trust with the participants of the process. ODR, similar to ADR, finds its legislative backing in statutes such as Indian Evidence Act, 1972; Code of Civil Procedure, 1908; Information and Technology Act, 2000; Arbitration and Conciliation Act, 1996; The Bharatiya Sakshya Adhiniyam, 2023; The Mediation Act, 2023 along with other rules and regulations as and when they are brough into picture. These laws
11 Afcons Infrastructure Ltd. and Ors. v. Cherian Varkey Construction Co. (P) Ltd. and Ors.,
MANU/SC/0525/2010.
12 K. Srinivas Rao v. D.A. Deepa, 2013 5 SCC 226.
13 129th Report, Law Commission of India.
14 Joel B. Eisen, Are We Ready for Mediation in Cyberspace?, BYU L. REV. 1305 (1998).
15 Asha A Hemrajani & Eunice Chua, Effectively Leveraging Technology in Mediation-Suggestions for a
Effectively Leveraging Technology in Mediation-Suggestions for a Way Forward in Asia Way Forward in Asia Eunice, 36 Sing. L Rev 208 (2018-19). not only enable ODR but also supplement ODR by covering grey areas such as electronic submission of documentary evidence, thereby providing an encouraging environment to further develop ODR. As a result of these efforts, initiatives such as NIXI, INGRAM and SAMADHAAN came into being and are functioning with great efficiency. 16 ODR has also received judicial recognition from the Supreme Court17. This has allowed nongovernment initiatives such as PeaceGate App and SEHMATI to gain a foothold as dispute resolution platforms that exclusively utilise ODR. Role of AI in dispute resolution: With the advancements in technology, ODR is further enhancing its capabilities and is now able to utilise the benefits given by AI to supplement its processes.
ODR has always benefited from automatic rule-based response mechanisms, but integrating AI will allow for the computer program to derive information through the use of Natural Language Processing (“NLP”), thereby making the process less cumbersome for individuals and building a sense of comfort for the participants. 18 This creates a new set of dispute resolvers that are not human but can emulate human responses. While there was a preliminary aversion to utilising such AI-based solutions on a national scale, China has taken the lead and has already utilised AI systems along with robots such as Xiao Fa, Xiao Zhi, 206 System, Faxin and many more to help both litigants and the judges to reach speedy conclusions. 19 Such AI-based solutions have helped the judicial system not only save costs but also reduce workload, be it administrative or otherwise.
Furthermore, companies such as Thomson Reuters and NextLevel have inaugurated their dispute resolution AIS, such as NextLevel Mediation, CoCouncil (by Thomson Reuters). With such examples in place, we need to understand the application of AI-based ODR mechanisms in India. AI-based mediators are the ones that utilise advanced algorithms to achieve the desired results. They are not essentially mediators by themselves; rather, they play a complementary role alongside human mediators to provide an objective review of the situation and to provide recommendations for solutions.
16 NITI Aayog, Designing The Future of Dispute Resolution (2021).
17 Shakti Bhog v Kola Shipping (2009) 2 SCC 134; Trimex International v Vedanta Aluminum Ltd 2010(1)
SCALE574; Grid Corporation of Orissa Ltd. v AES Corporation (2002) 7 SCC 736. 18 Sarita, Harsh Kumar, Mediation and Artificial Intelligence: Future of Dispute Resolution, 4 International Journal of Law, Management & Humanities 1472 (2021). 19 Benjamin Minhao Chen, Zhiyu Li, How Will Technology Change The Face Of Chinese Justice?, 34 Columbia Journal of Asian Law 1 (2020).
These types of AI mediators can be rule-based or machine learning based. In rule-based AI models, there exists a pre-determined set of rules and criteria that govern the decision-making process of the computer code, whereas in machine learning based systems, the AI will go through a multitude of data to identify an optimal decision-making process. Due to the fundamental difference between the nature of AI and that of the human mind, it is not possible to arrive at a solution purely based on AI recommendations, but it is a powerful tool in setting benchmarks, starting points and identifying risks, taking into account the overall circumstances. 20 AI models work based on data; to train an AI model for mediation, it will require data from past mediations.
It will go through such data to prepare a primary set of rules, which will then be supplemented with new data on a case-by-case basis, and the AI will work on the new data to provide its recommendations. Meanwhile, the AI will add this data to its existing database to perfect itself. This repeating loop helps us develop an AI that can effectively help a human mediator in discharging their duties. The process of utilising AI in mediation involves providing the AI with all the requisite information. It involves providing the AI with facts, evidence, applicable laws, arguments/ demands from both sides, any initial offers, and so on. This data is thereafter processed by the AI, and recommendations are made by the AI based on the strengths and weaknesses of the arguments presented.
Most AIS give sound reasoning for their recommendations, and they are also able to cater to any condition that both parties have agreed upon while preparing their recommendations. The result is presented before the parties and the human mediator, who can now utilise the result to further establish a dialogue between parties and use the findings as an anchor to help parties settle. Such utility of AIS is, however, plagued by several limitations, all of which, though curable, still plague the ODR framework in India. Challenges in the Adoption of AI-Assisted Mediation The challenges faced by AI-assisted Mediation in India can be categorised as follows:
1 Lack of infrastructure
Any mechanism that will be utilising AI for any type of role, be it dominant or supportive, will only work on the precondition that there is sufficient 20 Miles Mediation and Arbitration, Artificial Intelligence (AI) and Mediation: Technology-Based Versus Human- Facilitated Dispute Resolution, JDSUPRA (Aug. 8, 2024, 01:48 PM), https://www. jdsupra. com/legalnews/artificial-intelligence-ai-and-1573917/. digital infrastructure in place and accessible to both the mediator and the participants21. The Indian population has limited access to the internet, with the number of internet users in India having reached just 821 million, which is only a portion of the overall population. 22 Another facet of this problem is the lack of mediators or “Human” neutrals who have access to and knowledge of AI, who can actively use the provided infrastructure to its optimal utility.
Such individuals need to be well-versed in the mechanisms and help the parties navigate the new technologies comfortably. 23
2 Lack of literacy
Just providing access to infrastructure does not satisfy the requirements of justice; the participants need to be made aware of the possibilities and opportunities that it brings. The participants must also be trained on a basic level to utilise their learnings as well. While it is not difficult to converse with AI-based computer code, a certain level of literacy regarding its workings is necessary to properly respond to the queries presented to the participants.
3 Lack of awareness
Another aspect of the problem is that the population is not aware of the existence of AI mediators. For the majority of the population, courts are believed to be the start and end of any dispute resolution process, and they lack any awareness about the existence of ODRS. Therefore, platforms that do provide dispute resolution mechanisms and such resources are encouraged by the court itself.
4 Lack of trust
Any form of mediation process is successful because the parties trust the neutral in both capacity and in principle to look after their interests. When it comes to AI, such trust is not usually present there. Because AI is just a computer code that can operate via information inputs, untrusting participants withhold information or halfheartedly input information that results in AI giving out unsuitable recommendations that further solidify their distrust.24 This results in a negative feedback loop that challenges the credibility of AI integration across the entire judicial system.
5 Need for supervision
While a lack of trust is a major challenge for the implementation of AI mediators, another major challenge is that AI cannot be trusted completely. It must be recognised that AI is just a part of computer code that has been created to work
21 Roger Smith, Rechtwijzer
why online supported dispute resolution is hard to implement, LAW, TECHNOLOGY AND ACCESS TO JUSTICE (Aug. 20, 2024 11:58 AM) https://law-techa2j.org/odr/rechtwijzerwhy-online-supported-dispute-resolution-is-hard-to-implement/. KANTAR, IAMAL, Internet in India (Aug. 22, 02:25 PM) https://uat.indiadigitalsummit.in/sites/default/files/thoughtleadership/pdf/Kantar_iamai_Report_20_Page_V3_FINAL_web_0.pdf. 23 Graham Ross, Challenges and Opportunities in Implementing ODR’ in Proceedings of the UNECE Forum on ODR, MEDIATE (Aug. 14, 2024 08:03 PM) https://www.mediate.com/Integrating/docs/ross.pdf.
24 Dr. Riikka Koulu, Law, Technology and Dispute Resolution, 77 (Routledge 2019).
according to a set of rules. In situations where it is unable to find a solution from its database but a solution is demanded of it, AIS are known to provide made-up answers.25
6 Lack of integration with traditional court system
Even with the advancements of technology, the creation of wide-ranging ODR mechanisms and digitisation of multiple procedures, the courts are not able to integrate technology at an optimal level. The most common example of it is the need to attach a copy of e-stamp certificates as proof of payment of stamp duty, even after e-stamps were introduced to reduce the number of paperwork.26 Although courts are aware of the system in place and the intent behind it, they still rule such actions as irregularities and pass adverse orders.27 The problem revolves around the lack of training of traditional courts so that they can be in line with the innovations and initiatives.
7 Lack of Legislative backing
When it comes to AIS, the lack of legislation is the foremost reason why participants opt against the use of AI-integrated solutions. Legislation brings with it certainty, and the absence of such certainty encourages advocates to steer clients away from the ODR process to the adversarial process.28 AIbased mediation raises a lot of privacy issues, and the applicability of settlements drafted by AI is still a grey area. While the Mediation Act, 2023 does provide some validity to mediation settlements reached by parties but if the courts deny the admissibility of settlements made by AI, it will result in an unwelcome situation for AIintegrated solutions.
8 Lack of Data Protection framework and infrastructure
AI is a completely data centric and to prepare an AI model capable of identifying key components from the data presented and formulate relevant recommendations there is a need to train the AI over a large database of data that includes case files, data submitted by parties and process followed by mediator. The confidentiality of such data and future use of such data is a grey area and a barrier to creating and utilising AI models.
9 Inherent Bias
AI, while being a computer code, is not free from bias. By feeding a particular set of data in a particular manner, it is possible to get biased responses from 25 Christopher K. Poole, The Use of AI in ADR: Balancing Potential and Pitfalls, JAMSADR (Aug. 11, 2024 11:45 AM) https://www. jamsadr. com/blog/2024/the-use-of-ai-in-adr-balancing-potential-and-pitfalls. Shoaib Zaman, Duly Stamped, MONEY TODAY (Aug. 25, 02:15 PM) https://www. businesstoday. in/moneytoday/financial-planning/electronic-stamping-is-a-convenientway-to-pay-stamp-duty/story/201780. html. 27 Garware Walls Ropes Ltd. v Coastal Marine Constructions & Engineering Ltd. 2019 SCC Online SC 515. 28 Amy J. Schmitz & John Zeleznikow, Intelligent Legal Tech To Empower Self represented Litigants, 23 COLUM. SCI. & TECH. L. REV. 142 (2021). the AI.
This AI can be inherently biased, or such bias can be developed later after the mediator repeatedly feeds a certain type of data and suggestions to the software, which can lead to a post-creation bias within the AI model. After discussing the limitations, it is pertinent to note that all these limitations are curable and active efforts are being made by stakeholders to remedy the situation and help expand the application of AI-based solutions. Initiatives such as PMGDISHA ensure access to digital infrastructure as well as ODR in remote regions. 29 Implications for Mediators Mediation is different from arbitration or any other judicial process, not just through the procedure, but rather through the intent behind the process.
30 Mediation is not a process where one of the parties leaves as the victor; rather, it’s the process of helping both parties achieve their respective victories by balancing the interests of the parties with their obligations. The core tenet of mediation is not to provide a logical solution; rather, it is a process of identifying the optimal solution for both parties. This includes understanding, empathising and compromising with each other. 31 Mediation is one of the few situations where the emotional aspect of the circumstances has a significant weight in the decision-making process. The need for a human mediator who can visualise the tapestry of social and moral obligations of the parties, along with their rights, cannot be replaced by an Artificial intelligence, no matter how advanced, because of the “Human factor” involved in such decisions.
An example of the same can be the case of Sullenberger. 32 Emergency landing, which was later portrayed in a movie. In that case, the computer simulation of the flight path during the accident was challenged because it did not replicate the conditions of a human mind. Whereas the adjusted parameters after such a protest resulted in the computer system denying any possibility of the aircraft surviving. But the reality was that the against all expectations, the emergency landing succeeded. This allows us to shed light on the fact that no matter how advanced a computer 29 Ministry of Electronics and Information Technology, Government of India, Objective, PMGDISHA (Aug. 30,
2024 04:15 PM) https://www.pmgdisha.in/about-pmgdisha/.
30 Dr Ranjith Krishnan, Anju Panicker, and Syam Kumar R, AI and Mediation
The limitations in convergence, FINANCIAL EXPRESS (Aug. 24, 2024 04:22 PM) https://www.financialexpress.com/opinion/ai-and-mediationthe-limitations-in-convergence/3493288/. 31 Dafna Lavi, Three Is Not A Crowd: Online Mediation-Arbitration In Business To Consumer Internet Disputes,
37 (3) U. Pa. J. Int’l L. 871 (2016).
32 Sully, WIKIPEDIA (Aug. 28, 2024 02:08 PM) https://en.wikipedia.org/wiki/Sully_(film).
simulation becomes, there remains a “Human factor” that is necessary to supplement and complement those calculations to give them a practical applicability. As far as mediators are concerned, they need to be careful while utilising AI so as not to lose the essence of Mediation. AI can be used to assist the mediator in summarising the data available to them, identifying key facts and highlighting potential obstacles during the process. 33 It can help the mediator draft personalised questions for specific disputes so that no key information is overlooked. 34 AI can also assist with real-time drafting of the settlement agreement and making immediate changes to the terms depending on any new information provided by the parties. By delegating the task of compiling and analysing data provided by parties to the AI, the human mediator can derive two-fold benefits35.
Firstly, he can get the task done quickly and efficiently; Secondly, he can utilise the time saved from this in establishing trust regarding the neutrality of the process between parties. It helps the parties move beyond the language barrier and is not influenced by any bias. AI can also take the form of chatbots to further help the parties provide data or inputs that they would have missed at a prior opportunity, and to include the same in its computations. However, AIS are not equipped to handle emotional outbursts from parties, and such inputs can easily give erroneous results. 36 The AI can not only receive data but can also act as a storage and management for the said data, thereby discharging threefold duties. It can be utilised to manage the procedure as well; it can keep a record of the meetings held, the agendas and key points discussed and help in scheduling further meetings.
However, this is where the limitations of AI surface. It is limited to the data that it works with; often, the solutions offered by AI are unable to be applied directly as they lack the context of society and an “earthly” connection. Furthermore, the nature of mediation proceedings is such that one of the major roles a mediator discharges is to get parties to share data and their concerns, as often parties avoid sharing any information altogether. AI mediators are not equipped to deal with non-verbal cues and concerns, and hence, there is a risk of parties losing
33 Bruce Edwards, Artificial Intelligence in Mediation
What the Future Holds for Mediators, EDWARDSMEDIATIONACADEMY (Sept 2, 2024 03:45 PM) https://edwardsmediationacademy. com/artificialintelligence-in-mediation-what-the-future-holds-for-mediators/. 34 Alyson Carrel & Noam Ebner, Mind the Gap: Bringing Technology to the Mediation Table, 2 Journal of Dispute Resolution 1 (2019). 35 Uchenna Jerome Orji, Technology Mediated Dispute Resolution: Challenges and Opportunities for Dispute Resolution, 5 C. T. L. R. 124 (2012). 36 Katie Shonk, AI Mediation: Using AI to Help Mediate Disputes, HAVARD BLOG (Aug. 22, 2024 05:37 PM) https://www. pon. harvard. edu/daily/mediation/ai-mediation-using-ai-to-help-mediate-disputes/. trust in them if left to their own devices. Further, the lack of empathy in the recommendations given by AI and the way it demands information skips out on empathy and may result in parties becoming more rigid in their approach.
Concerns regarding data privacy and protection have already been discussed earlier. The use of such data to train AI models is barred by a plethora of legal barriers, along with moral obligations on the mediator. Another legal issue is concerning the admissibility of documents created by AI in the court of law. It calls into question the responsibility of professionals such as lawyers who are tasked with the duty to ensure proper documentation. Further, if the recommendation given by AI turns out to be harmful to the parties, then who is liable for such a recommendation? Such questions raise doubts with regards to the application of AI models in mediation and require the mediator to ensure that the AI plays a subservient role through recommendations and support only.
The recommendations and key findings provided by the AI are still subject to scrutiny and should not be taken at face value. As noted by Christopher K. Poole37 AI often includes madeup citations or illegal recommendations within its responses that need to be vetted by professionals. Countries such as the US and Europe have already started developing policy frameworks regarding the disclosure of the use of AI by professionals to ensure accountability. Conclusion Based on the data collected and analysed, it must be noted that despite all its limitations, AI is a lucrative option in the eyes of stakeholders. However, the attraction of AI aside, there exists a certain level of scepticism about its application in the legal domain, especially in mediation, where the “Human factor” plays a critical role in helping the parties reach settlements.
The lack of data protection laws is the biggest hurdle that AI-based mediators face as of now, and without receiving a concrete framework regarding the same, public trust in the use of AI will eventually falter. To summarise the situation regarding the use of AI in achieving mediation settlements, the best description would be “Optimistic with great future potential”. However, considering the current state of events, it is for the best that AI takes a subordinate and supporting role in helping mediators and parties in achieving settlements. The actions, decisions and recommendations by AI cannot be left unchecked, for it is still in a nascent stage. However, it should not be disregarded that AI is a technology of such a nature that the more time passes 37 Christopher K. Poole, The Use of AI in ADR: Balancing Potential and Pitfalls, JAMSADR (Aug. 11, 2024 11:45 AM) https://www. jamsadr.
com/blog/2024/the-use-of-ai-in-adr-balancing-potential-and-pitfalls. and the more data it processes, the better and more reliable it becomes. Although it will never be able to replace human mediators in the mediation process, it will be able to achieve a similar outcome by giving completely neutral and calculated recommendations for the benefit of both parties.