The use of sports arbitration, a type of alternative dispute resolution (ADR), to settle disputes arising from sporting events has grown significantly in recent years. It involves resolving disputes related to contracts, disciplinary matters, anti-doping, and other sports-related issues through arbitration rather than traditional dispute resolution methods.
One of the most recent advancements that has impacted sports arbitration is artificial intelligence (AI). AI has brought about significant advances in sports arbitration, revolutionizing the way disputes are resolved and changing the landscape of sports law.
Sports Dispute Resolution: The Growing Preference for Arbitration
The Court of Arbitration for Sport (CAS) is an international arbitral tribunal based in Lausanne, Switzerland.  It was established in 1984 to resolve sports related disputes such as doping, match-fixing, and athlete eligibility. According to the yearly statistics of the Court of Arbitration for Sports (CAS) , the number of cases brought before the CAS in 2021 reached a record high of 996. 
The CAS operates independently of any sports organization and its decisions are final and binding. It has jurisdiction over all Olympic sports and a number of non-Olympic sports. Its decisions also have a significant impact on the sports industry. The CAS has become the go-to institution for resolving sports disputes due to its expertise, neutrality, and efficiency in handling cases.
The Evolving World of AI: Breakthroughs and Trends
Artificial Intelligence (AI) has made significant advances in various areas, especially in data analysis and predictive modeling. In data analysis, AI algorithms analyze vast amounts of data in order to make predictions about future events, carry out real-time analytics, and gain insights into trends and patterns. These advances have transformed many industries, including finance, sports, healthcare, and marketing, allowing organizations to make better-informed decisions and improving operational efficiency. 
One application of AI in data analysis is predictive modeling, which involves using machine learning algorithms to analyze historical data and identify patterns that can be used to make accurate predictions about future events.  The World Anti-Doping Agency (WADA) uses predictive modeling to identify athletes who may be using performance-enhancing substances.  The system, called the Athlete Biological Passport (ABP), analyzes an athlete’s biological data over time and generates a baseline profile. Any significant changes from the athlete’s baseline profile may suggest the effects of doping on the athlete’s body and warrant further investigation, even if the specific substance is not identified.
Predictive modeling has also been adopted in sports arbitration; for example, AI-powered predictive modeling can be used to predict the outcome of sports disputes. By training algorithms on a range of data including previous decisions, player and team statistics, and even weather conditions, predictions can be made about the outcome of a particular case.
Another application of AI in sports arbitration is Natural Language Processing (NLP) algorithms. These algorithms enable the analysis of unstructured data such as player interviews, social media posts, and news articles, to gain insights into the views and opinions of players and the public. This information can be used to inform arbitration decisions and to provide insight into the wider impact of decisions.
AI algorithms can offer real-time insights into the performance of players, teams, and officials by processing data as it is generated. AI algorithms can also identify areas of concern such as overtraining and fatigue by analyzing a player’s performance data, thereby allowing for proactive measures to be taken and assisting in identifying and preventing potential injury risks.  These may serve as data with persuasive effect on an arbitral tribunal as they can improve decision-making during a match or competition and inform future arbitration decisions. Generally, AI is used in sports; the VAR in football for instance is used for real-time analytics. The difference between various AI application being that some are proactive and others retroactive.
Overall, AI has opened up exciting possibilities in sports arbitration, enabling more informed and accurate decision-making based on vast amounts of data. As AI continues to evolve, we can expect to see even more innovative applications of AI in sports arbitration.
Convergence of Sports Arbitration and Artificial Intelligence:
The field of sports arbitration has been transformed by rapid advancements in AI technology. With the ability to analyze vast amounts of data and automate tasks, AI has greatly improved the efficiency and accuracy of the arbitration process. From case management to evidence analysis, AI-powered systems have significantly reduced the time and costs in sports dispute resolution.
The convergence of sports arbitration and AI has not only made the process more efficient but has also increased the transparency and fairness of the arbitration process. With AI-powered tools providing insights and predictions on the likely outcome of disputes, arbitrators can make more informed decisions. Some of these convergent points include:
1. Case-Management Systems
AI-powered case management systems can automate tasks such as scheduling, document management, and evidence analysis, making the arbitration process more efficient and cost-effective. 
2. Data Analytics
AI algorithms can analyze vast amounts of data, including legal precedents, statutes, regulations, and case law, to provide insights and predictions on the likely outcome of a dispute. AI can also assist in predicting case outcomes based on available data,  which can aid parties in evaluating the risks and the potential outcome of a dispute which could facilitate settlement discussions. AI gives the dispute resolution process some predictability which sports arbitration can benefit from.
An example of such AI technology is ROSS; an AI legal research platform that employs natural language processing to evaluate enormous volumes of legal material and offer insights into possible legal outcomes. In sports arbitration, ROSS may be used to analyze legal precedents and provide insights into the possible outcomes of disputes such as doping allegations, contract disputes, or disciplinary actions. AI such as this can aid sports arbitrators in making more informed decisions and ensuring consistency in their rulings. However, it is important to note that while AI can provide valuable assistance, the ultimate decision-making authority still rests with the human arbitrator.
3. Video Assistant Referee (VAR) Technology
VAR technology is primarily used in sports arbitration, particularly in association football.  It is a support tool for sport officials, aimed at improving decision-making by reducing the number of incorrect decisions made by referees. The implementation of VAR in football was included in the 2018/2019 edition of the Laws of the Game, allowing video match officials (VMOs) to assist on-field referees in making decisions related to goals, penalties, red cards, and cases of mistaken identity.
VAR technology works by having the VMOs review controversial or potentially game-changing incidents using video replays and multiple camera angles. The VMOs then communicate their findings to the on-field referee, who makes the final decision. This technology aims to reduce the number of incorrect referee decisions, leading to fairer match outcomes. The use of VAR technology in sports arbitration is an example of how technology can assist decision-making, particularly in cases where human error can significantly impact the outcome of a game.
In sports arbitration, the decision-making process often involves reviewing video footage of the incident in question. VAR can aid in this process by providing high-quality footage from multiple angles, giving arbitrators a clear and comprehensive view of the situation. VAR can significantly enhance the accuracy and efficiency of the arbitration process, as arbitrators can make more informed decisions based on the available evidence.
However, the impact of VAR technology on decision-making in sports arbitration has been the subject of research and debate. While VAR technology improves the accuracy of decisions made by referees, it has also been criticized for slowing down the pace of the game and leading to confusion among players and fans.  There have also been concerns about the consistency of its application across different leagues and competitions. To ensure the effectiveness of VAR technology in sports arbitration and prevent controversy, researchers suggest that there is a need to standardize its use across different leagues and competitions.
4. Online Filings
International Court of Arbitration for Sport (CAS) has developed a new online platform that allows parties to file documents and participate in hearings remotely. This has made it easier for parties to participate in CAS proceedings, even if they are located in different countries.
The evolution of sports arbitration has been characterized by a constant search for more accurate and efficient ways of resolving disputes in the complex and rapidly changing world of sports. Recent advances in artificial intelligence (AI) have significantly impacted sports arbitration, providing new tools and technologies that have revolutionized the field. From video assistant referee systems to AI-powered contract analysis tools, these innovations have helped to streamline processes, reduce costs, and improve the accuracy and efficiency of decision-making in sports arbitration.
The use of AI in sports arbitration has also brought about significant benefits for athletes, sport teams, and other stakeholders in the sports industry. With the ability to analyze vast amounts of data and provide recommendations based on past cases and legal precedents, AI-powered tools have made it possible for sports arbitrators to make more informed and fair decisions. Moreover, the use of AI in sports arbitration has helped to promote transparency and accountability, ensuring that disputes are resolved in a timely and efficient manner.
While the impact of AI on sports arbitration has been largely positive, there are also some potential drawbacks that need to be addressed. For example, the use of AI may result in a reduction in the role of human decision-makers, which could have implications for the fairness and impartiality of the arbitration process. Additionally, there are concerns about data privacy and security, particularly in cases where sensitive personal information is being analyzed by AI-powered tools.
Overall, the recent advances in AI have had a profound impact on sports arbitration. While there are challenges that need to be addressed, the potential benefits of AI are clear. As sports continue to evolve and become more complex, it is likely that AI will play an increasingly important role in sports arbitration, helping to ensure that disputes are resolved fairly, efficiently, and in the best interests of all stakeholders involved.
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Diane Okoko is the Principal Partner of Marcus-Okoko & Co., and she specializes in International Arbitration, Corporate Law and Regulatory Compliance.