Whenever we hear the words “dispute” or “argument”, we immediately think of conventional litigation and heated courtrooms discussions. Arguments and disagreements are a frequent and natural part of our lives; the answers, conclusions, and intricacies of such things are what keep us going. However, we all are aware that the Indian courts are packed with cases that have been pending for a long time. To deal with such circumstances, Alternative Dispute Resolution (ADR) can be a useful technique since it settles dispute in a peaceful way with a result that is acceptable by both parties.
Alternative Dispute Resolution (ADR) is a concept that may be used to resolve conflicts instead of using traditional techniques. Alternative Dispute Resolution (ADR) is a concept that may be used to resolve conflicts instead of using traditional techniques.
ADR is a process generally known as the “out-of-court settlement,” and individuals who didn’t want to engage in the complexities of a judicial battle are increasingly selecting it as a feasible alternative. However, with advancements in the area and the law adapting to it more than ever, it has spread its wings to the technological era. Artificial Intelligence (“AI”) is one such futuristic technology that is aiding the legal field like a pro.
Artificial Intelligence is the idea that computers can replace humans in various fields of life. Like : Smart Contracts are contractual agreements that are created using computer code instead of traditional written clauses. They are usually linked to an automated trigger.
Over the past couple of years, the number of transactions that take place online has increased significantly. This has led to the emergence of various online dispute resolution processes.
This essay aims to introduce the various aspects of how AI could be used in the dispute resolution process. There was little systematic development of such systems in the early years. A variety of improvised systems was created. Our essay discusses its integration with ADR, as well as its benefits and drawbacks.
A package of ADR with AI:
ADR, which includes disciplines such as Mediation, Arbitration, and Negotiation, literally means “an alternative to conventional conflicts.” These areas entail professional complexities, making this procedure dependable for the public. The core of this system is the lack of judicial procedures and the use of professional legal representation. The ADR procedure is similar to a family conversation, but there are “no links” in this case, which makes it more credible because it is handled objectively. Its benefit is that it brings customers and professionals together in a close-knit discussion/argument, where the function of the mediator is critical because it entails analysing the situation.
The law is not lagging behind in terms of technological developments. Artificial Intelligence (AI), the idea that computerised systems may replace human cognitive processes and interactions, is gaining popularity in all walks of life, including the legal profession, and particularly in the field of conflict resolution.
In layman’s language Artificial Intelligence shows “human-like” skills which runs on well-tuned algorithms .
Artificial intelligence (AI) is a technology that can imitate and replace human behaviour. Online dispute resolution provides for the settlement of disputes through internet-based procedures. It allows for virtual conversation between persons that are separated via distance. These interactions take place between businesses and customers. Due to social distancing conventions and distant work rules, online dispute resolution has gained popularity in the wake of the recent COVID-19 epidemic. The Supreme Court of India recently issued a suo moto ruling outlining principles for how courts should operate online.
How AI work?
By classifying and analysing the existing information, Artificial Intelligence enhances the human’s efforts. It enables the combination of human and computer-based knowledge, management skills. Decision-making tools increase the performance of individuals, whereas decision-making tools automate the process and need little to no intervention. The system may be taught to make judgments based on rules, situations, and previous experience. Machine learning is what drives experience-based learning, and it happens automatically based on data mined by the software.
The following are some of the tools that have been utilised to build intelligent negotiating support systems:
- Rule-based reasoning – It is a type of reasoning in which knowledge of a given legal subject is represented as a set of rules.
- Case-based reasoning – Case-based reasoning is using prior experience to analyse or solve a new problem, explaining why earlier experiences are or are not comparable to the current situation, and adapting past methods to suit the criteria.
- Machine Learning – Machine Learning (ML) is the science of teaching computers to learn on their own. It’s a set of techniques that allow machines to learn from data on their own. Machines can also make predictions without being explicitly told to do so by improvising on previous experiences.
- Neural network – A neural network is a set of algorithms that attempts to detect underlying relationships in a piece of data using a technique similar to how the human brain works. In this context, neural networks are systems of neurons that might be biological or artificial in origin.
The Lodder-Zeleznikow explains Online Dispute Resolution Model in Three Steps:
The suggested three-step approach is based on a predetermined order.
- Firstly, if the negotiations fail – that is, “the best alternative to a negotiated deal”, BATNA – the instrument for negotiations assistance should give retroactions on the anticipated outcomes of the conflict.
- Second, the tool should use reasoning or discussion approaches to try to settle any pre-existing disagreements.
- Third, for concerns that were not resolved in step two, the tool should use decision analysis approaches and compensation/trade-off tactics to help settle the conflict.
Finally, if the outcome of step three is unacceptable to the parties, the tool should allow them to return to step two and repeat the process recursively until the disagreement is resolved or a stalemate is reached. A stalemate happens when there is no progress from step two to step three or vice versa. Even if there is a deadlock, appropriate types of Alternative Dispute Resolution (such as blind bidding or arbitration) can be utilised on a smaller group of concerns.
Will claimant want to work according to computer’s advice?
Could artificial intelligence help process claims more quickly and even make decisions on cases? Would claimants be willing to have their claims decided by computers?
There is an abundance of raw data available on the planet. For example, we could train an AI to read a large number of court decisions. Many companies are also attempting to use AI to make sense of court proceedings. Finding ways for AI to process this data is the issue. It is now quite tough to accomplish. The law has a lot of structure, but it’s not the type of organisation that makes it easy for an algorithm to learn and recognise patterns and rules. Giving an AI Lexis-Nexis access and then expecting it to serve on the Supreme Court is still a fair distance
AI using software algorithms (i.e., us, the humans) now tackles complex activities that were previously done by non-artificial intelligences. Humans have their own methods for analysing problems and coming up with solutions. AI must also be able to comprehend issues and design solutions in order to produce results that are comparable to or better than those produced by humans. However, algorithmic intelligence does not approach these goals in the same way that human intelligence does.
The opposing idea is that, as AI gets more integrated into our daily lives – to the point where we allow it to drive us and our families about in self-driving cars – we will feel perfectly comfortable in having the algorithm decide our cases for us.
We need to develop data sets if we want to train AIs to make better decisions. Because so many cases are now determined on ODR systems, one duty AIs could take on in the near future is to assist in the classification of these data sets. New cases would be negotiated, mediated, and arbitrated by humans, with AIs reviewing and structuring the evidence generated in real time. This would give us a leg up on the competition in terms of assembling a huge corpus to train future AI systems.
An AI must concentrate on examples that are similar in nature. It’s quite tough for an algorithm to gather a database of a variety of cases (such as, workplace, traffic, divorce) and then deduce rules that could make sense of any new scenario. Specialization in specific case types (for instance –, traffic) is critical for rule correctness. General decision-making systems (people) must still be able to classify each new situation and then apply the rules that relate to that particular case type.
Technology has established itself in the lives of people in today’s society. Artificial Intelligence (AI) is one such technology that has aided humanity in growing in different sectors, making a variety of activities simple. Life has become both simpler and more complicated because of such technologies.
Excellences of AI:
AI is transforming the world for the better, from our smartphones’ voice-based personal assistants to drones that are assisting Indian farmers in reaping a better harvest. AI can be advantageous to the legal field as it will reduce the load off the people working to resolve the case.
- Time Effective – Artificial intelligence is primarily used in arbitration today to assess increasingly large volumes of digital arbitral data held by parties and their counsel in order to decide what is important to the specific case, then to analyse and present that material in a more effective manner. The use of artificial intelligence (AI) to handle arbitral data has helped, and will continue to help, to solve the cost and time problems caused by the digital data at issue in today’s complicated conflicts. Artificial intelligence (AI) may eliminate the need for court reporters, as the AI platform would be able to record the hearing via microphones and deliver a real-time transcript with speaker identification for all parties involved.
- No unconscious control cognitive biases – humans are affected by cognitive biases. When deciding a case in the evening, the arbitrator may be influenced by cases he handled earlier in the day or the external environment. Its decision-making process may be influenced. The anchor effect, which is a common human tendency to rely on the first piece of knowledge, is an example of cognitive biases. gained in order to make future judgments When it comes to making decisions, humans have a proclivity towards cognitive biases. Robotic appointments would be less likely to be challenged on the basis of a conflict of interest or bias. Their decision-making process, presumably, would be less polluted by the very human flaws of bias, illogicity, or simply having a terrible day.
- Elimination of Errors – Human arbitrators are prone to making errors in interpretation, translation, documentation, authority selection, and decision-making, among other things. The use of artificial intelligence (AI) at various stages or for different jobs can aid in the elimination of inefficiencies in the arbitration process. It can detect blind spots and give recommendations for smoothing them out to make the process more efficient.
- Immediate enforcement of awards – There is a lag between the decision and the enforcement of an appeal, or an application for setting aside the award or a stay on enforcement is not filed. In the current situation, the parties must wait for the award to be enforced after it has been passed.
- Time Effective – Arbitrators devote a significant amount of effort to crafting common portions of arbitration decisions, such as the parties, procedural history, arbitration clause, governing legislation, parties’ views, and arbitration fees. By delegating the drafting of such “boilerplate” parts to AI computers, arbitrators can save time and money.
Imperfections of AI:
Every good technology can also be used to accomplish evil purposes. In this regard AI is no exception. AI has the potential to negatively affect the purpose of the Arbitration.
- Data Privacy – Confidentiality is one of the most important aspects of the Arbitration Process. AI is entirely based on the intellectual algorithms and software programming created by a programmer, and only a select few have total access to the algorithms that could deliver the ultimate conclusion in a given instance. Hacking is a common occurrence in software development. There is a risk that the parties’ confidential information will be compromised as a result of hacking. Any system update comes with the risk of a virus and other complicated technical concerns.
- Lack of Flexibility – Every case in arbitration is unique, and if conclusions are made based on a normal operating procedure and a standardized approach for judging the case is the same, inconsistency is evident. Each award is presented with an explanation of the factors that contributed to the decision. If there are only a few fixed algorithms, there will only be a few combinations of judgments, resulting in a rigid structure.
- Huge Investment – For adopting to such a dynamic technology necessitates training, the initial implementation of AI in arbitration will involves a significant expenditure of both money and time. The development of AI systems is done to lower the cost of proceedings, but it takes a lot of money to produce such AI programmers and clever algorithms, which immediately raises the price of such a system. If adopted, it will show to be cost-effective for those interested in arbitration in the near future.
- Non-Acceptance of such system – In the United States, there was a case known as the ‘Loomis case,’ in which Eric Loomis was convicted based on the results of closed-source risk assessment software known as COMPAS (Correctional Offender Management Profiling of Alternative Sanctions). Equivalent, a private company, created proprietary algorithms using 137-item Questionnaires. A challenge to the conviction was filed, claiming that it was based on confidential algorithms that could not be scrutinized. This demonstrates the legal profession’s rejection of AI.
- Unemployment – The goal of AI development and application is to lessen human strain. However, this has a direct influence on employment rates because only a few people will be required to make the AI system work. Furthermore, AI will be capable of performing tasks previously performed by people, resulting in a reduction in the workforce.
Indian legal scenario for AI in Alternate Dispute Solutions:
Online Dispute Resolution is becoming more popular in India. The Information Technology Act, 2000 was passed in order to officially recognise e-commerce and e-governance systems. Alternative Dispute Resolution Processes are legally recognised in India under Section 891 of the Code of Civil Procedure, 1908.
The CJI stated during an International Conference on ‘Arbitration in the Era of Globalisation,’2 hosted by the Indian Council of Arbitration and FICCI, that “As we conceptualize international arbitration in a globalized era, we must also be cognizant of the synergistic opportunities available for international arbitration through the utilization of disruptive technologies.”
This demonstrates that India is searching for ways to incorporate artificial intelligence into its arbitration legislation. In this line, some regulatory adjustments have been recommended in India to accommodate artificial intelligence in its early phases. As a consequence of India’s commitment on establishing institutional arbitration, the proposed modification to the Arbitration and Conciliation Act now allows the Supreme Court and the High Courts to designate AI (for domestic arbitration). In the absence of an agreed-upon arbitration procedure, the AI shall designate arbitrator/s, according to the bill.
However before the implementation of Artificial Intelligence, there will be many amendments required in Information Technology Act, 20003 as despite the fact that authorising the use of Artificial Intelligence is permissible, there are no laws governing its usage. There will be major influence in Intellectual Property Rights as well. Algorithms are currently not patentable under India’s Patent Act, section 3 (k)4. Copyright for such algorithms must be handled in accordance with current legislation.
The Supreme Court of India affirmed a decision that barred an individual or entity with a vested interest in the arbitration from serving as the sole arbitrator. Under Indian law, the lone arbitrator’s independence is a legal necessity for every arbitration. India also lacks the necessary technology and infrastructure for all Indians to have access to online dispute resolution. Only 36% of Indians have internet and associated services.
Indian Platforms of ODR(Online Dispute Resolution):
Due to the COVID-19 issue, the existing pattern of dispute resolution has altered, and the internet platform has become the only option for individuals to address their problems. Because there are no judicial processes, all issues are addressed online through multiple platforms using video conferencing.
- A website-based platform for conflict settlement is the Centre for Alternate Dispute Resolution Excellence (CADRE). The parties will not be able to reach them by e-mail or video chat. It operates with skilled arbitrators who are well reversed by the regulations of CADRE. One of their major obligations is that customers do not walk empty-handed without money and remedies during the entire procedure.
- SAMA is another online dispute settlement platform that offers ease of access to high quality ADR service providers as well. It helps ICICI Bank resolve ten thousand disputes of Rs.20 lakh worth.
- AGAMI is a non-profit organisation that promotes ODR but is not a service provider platform, and it was founded in 2018. Its goal is to use ODR to resolve one million conflicts by the year 2022.
- The CODR (Centre for Online Dispute Resolution) is an organisation that handles disputes entirely online. It’s a private organisation that specialises in online cases from start to finish. By allowing the client and their advocate to manage the whole process, it attempts to reduce the complexity of the procedure while also ensuring the goals of justice.
Alternative dispute resolution techniques are considered versatile, economical, quick, and less formalistic than court-based adjudication, making them a potential alternative. Aside from the court system, the parties can choose from a variety of alternate conflict resolution solutions for uncomplicated disagreements. India is making progress in the area of judicial equality. The ADR structure acts as a stepping-stone for both parties as they work their way up the court system. The ADR movement has to move forward more quickly. This would considerably lessen the pressure on the courts, in addition to providing rapid justice at no cost. They will achieve the goal of giving social justice to the conflicting parties if they are adequately executed.
While the idea of computers answering questions does not sound unusual, the thought of them doing so while building a relationship with us does.
Artificial intelligence will play a major part in international arbitration in the near future, whether we like it or not. The stakes are immense, and the benefits of artificial intelligence are far too great to ignore. AI has many potential benefits for international arbitration, but as members of the arbitration community, we also need to grasp the risks of AI, what they are, and how they might affect international arbitration in non-obvious ways.
The growing tendency of people seeking out-of-court settlements for their disputes stimulates the incorporation of AI in arbitration. The basic goal of arbitration is to reach a resolution in a shorter amount of time while avoiding the complexities of the courtroom. Arbitration is poised to lead the way in terms of technological and procedural advancements. It is the role of arbitral institutions, tribunals, and practitioners to do so, particularly if such innovations can lower costs and improve efficiency.
There is yet no legislation that addresses the use of an AI-enabled system at various levels of arbitration. If AI-enabled technologies are used in arbitration procedures, some laws will be required to ensure that the parties are not endangered. This is a difficult area where AI’s strengths must be exploited without endangering arbitration’s essential values.