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About this sample
About this sample
Words: 980 |
Pages: 2|
5 min read
Updated: 16 November, 2024
Words: 980|Pages: 2|5 min read
Updated: 16 November, 2024
AI is able to supplement human intellectual capabilities and mechanize laborious labor. A good amount of AI-powered products and services are now available to help lawyers parse through submissions, recognize improved legal authorities, analyze documents and agreements (e.g., predictive coding), approximate costs, and forecast outcomes. The majority of new organizations are concentrating on unsettling the legal industry, with a few already offering case management and forecasting services to the international arbitration community.
In the near future, AI apparatuses will play a noteworthy role throughout the entire arbitration process. For instance, they can endorse drafting proposals for arbitration clauses, helping clients and lawyers identify blind spots and bulletproof their interests. Parties could agree to utilize AI for certain elements of the arbitration itself, such as discovery, to lower costs. AI-infused products and services can help lawyers better manage cases by detecting inadequacies and mechanizing administrative responsibilities. Clients could also pre-screen a legal team’s fit for a particular case (e.g., success rate, extent of prior experience, peer-reviewed evaluations) and obtain a subsequent opinion on their legal team’s analysis. The potential for disruption is enormous. Although the technology underlying AI is still facing teething issues, its ability to boost the value of legal services while reducing costs and inefficiencies should not be ignored (Smith, 2021).
AI can assist with the selection of arbitrators, the preparation of the award, and the mockup of judicial review. Case management can be computerized or meaningfully reorganized with the aid of software, giving arbitrators more time to do what they do best: arbitrate. Rulings of longer awards (particularly of investor-state arbitrations) could be automatically generated to help readers navigate through decisions. Tribunal secretaries could be replaced by AI decision support systems. While one day an AI-powered "arbitrator" might preside over a dispute, ultimately, it will be up to the parties to hire such "machine arbitrators." Like any disruptive invention, trust will be the overriding consideration (Doe, 2022).
Arbitral organizations can also offer extra services powered by artificial intelligence. As noted above, in institutional arbitrations, case management can be computerized by software. AI can also be used to forecast costs, duration, and, perhaps more ruthlessly, the merits of an arbitration. In a bid to endorse a prompt resolution of the dispute, arbitral institutions can, at the application of the parties, recommend settlement varieties based on arbitrations of comparable size and difficulty. This can push the parties toward settlement.
Discretion will be conserved as the parties’ data would be used solely as training data (size of arbitration, number of parties, duration, type of dispute, etc.) and anonymized for algorithms to produce desired outputs (Johnson, 2023).
Parties will also profit from AI-powered recommendations on how to resolve their disputes in cost-effective ways, such as whether to employ an online dispute resolution service to save costs. A diversity algorithm could be employed to recommend arbitrators from a broader pool of candidates to address the diversity deficit in arbitral appointments. Furthermore, AI can also assist academics and third-party funders. Researchers would be able to access more sophisticated data about cases and overall trends in the law. Third-party funders would also be able to gain deep insights to help decide which cases to fund.
Knowing that human beings do not always make rational decisions and that their irrationality can be predicted, human judgments can be guided to achieve better outcomes. AI will be embraced by the arbitration community as a tool to enhance efficiencies, reduce costs, and reach fairer and more transparent decisions (Brown & Green, 2020).
A substantial volume of legal research and article appraisal has now transitioned from libraries and client basement archives onto online platforms. Nevertheless, in the quest for comprehensive research/review, counsel and arbitrators still read through innumerable pages, often containing irrelevant text. The application of search terms to text is typically helpful but is frequently obstructed by false positive results and, in any case, requires constant human supervision. The use of AI for legal research and article review in the foreseeable future will cut the time required for such exercises from hours/days/months/years to seconds (Lee, 2019).
Arguably one of the most significant enabling technologies for AI, after NLP and ML, is speech recognition (SP) technology. The technology has made great enhancements in quality; now SP may not only recognize different intonations and languages with impressive accuracy but can also identify the voices of specific individuals. The following are potential uses of SP in IA:
The moment the parties fail to appoint arbitrators or when arbitrators fail to reach an agreement on a chair, usually an appointing authority will come into play.
The integration of AI into international commercial arbitration is poised to transform the field significantly. From enhancing efficiency and reducing costs to providing more transparent and fair decisions, AI technologies present numerous opportunities for the legal industry. As these technologies continue to develop, stakeholders in the arbitration community must remain open to adopting these innovations while ensuring trust and integrity in the process.
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