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ODR AND AI – AN INTERLINKED PROSPECTIVE

Updated: Apr 15, 2021

At the outset of the complete shutdown and overpowering barriers that exist, the need for the urgent online dispute mechanism has paved its way. There do prevail the already established out-of-the court alternative dispute resolution (ADR) framework in the form of arbitration, mediation, conciliation, etc. But even these have proved futile when such a pandemic struck and the dispute remained unsolved. That is the reason to mitigate the delay and long-distance, and the methods that will work with the help of technology are introduced. It cannot be doubted that technology and, artificial intelligence is the future. With evolvement and advancement in these, it is also required that law doesn’t lag behind all of it.

Traditionally, in the alternative dispute mechanism, there is the involvement of the parties of the dispute and a neutral negotiator that listens to the problem and suggests the solution and it is generally (except arbitration) up to the party to accept or refuse those terms. But in ODR, it can be said that there is the involvement of the fourth party which is technology-intermediary. This is the differentiating factor between conventional ADR and ODR. While AI involves the study of automated human intelligence, it is not wrong to say that both ODR and AI are connected, helping each other along the way.

With the aid of AI, it can perform tasks quickly and thus, resolving the matter in faster steps. The AI acts as an expert panel with giving out the appropriate logical solutions and outcomes possible in the dispute at hand with the help of calculated mechanisms. Though AI can assist in easier steps as well relating to compiling of the data, filing, etc. but with added advancement, it can lead the way towards less burden in litigation and even lesser burden of the lawyers or counsels.

An important thing under AI is the decision support systems (DSS). These are those that help in supplementing the human knowledge and management skills with the computer-based means for it. The software and programs established to act as a neutral party in resolving the dispute. The example can be seen in the form of the AI software ‘Bravia which can analyze a particular contract within minutes and can even extract the relevant portions of the data. This shows the capability and prospect that AI offers. With the help of such distinguished features, it would lead to efficiency in legal matters.

There can be no doubt that it can help in the resolution of family matters. When a family dispute arises, parties tend to go or the court, which more often suggests mediation or negotiation between the parties. This is because the nature of the dispute is of such a personal nature. That is the reason that family matters can be more adequately handled and resolved by the use of AI. For example, AI software called ‘SmartSettle’ can process the information and preferences provided by the parties and then, come up (by using different algorithms), the possible outcomes and solutions. It analyses by looking at different cases as well in the database.

More than now when the issues related to the different spheres are rising and the courts are becoming congested with the overload. It is necessary to understand and adopt different mechanisms by the advocates, courts, and parties themselves that will provide an effective and efficient way of coming to a conclusion or negotiation in a case. The algorithm building and the accuracy level of almost around 90 percent provide for sufficient outcomes by providing such services.

Yet, the limitation does exist in the classification of the matter and different interlinked disputes through algorithms in artificial intelligence, having its limits and lacunas. And, one cannot deny the need for human assistance in resolving the dispute even with the continued support from artificial intelligence. But, to completely ignore any kind of interlink between AI and ODR is ignorance as it is the future of legal disputes.

- LEGAL HUMMING

(CO-AUTHOR ARUSHI ANAND)

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