Algorithmic Justice or Automated Injustice? A Critical Examination of the Disadvantages of Artificial Intelligence in Arbitration

Abstract

Artificial Intelligence (AI) is often regarded for its ability to increase accessibility, lower costs, and improve efficiency in arbitral procedures. Beneath these potentials, are a number of significant issues that raise doubts about whether AI promotes algorithmic justice or results in automated injustice. This study employed a doctrinal research design, which is largely qualitative, meaning it is non-numerical. A doctrinal research design is a theoretical approach rooted in libraries that is mostly employed in legal research. It entails identifying, organizing, and interpreting legal norms and principles through the critical analysis and synthesis of existing legal resources, including statutes, case laws, and regulations. Without gathering personal evidence, this research approach concentrates on "the letter of the law," looking at legal theory separately to address particular legal issues, formulate legal theories, and spot contradictions, ambiguities, or places in need of reform. The study revealed that the drawbacks of AI in arbitration are critical, and particular attention is required to resolve the challenges of algorithmic bias, decision-making opacity, data scarcity, hallucinated results, and the loss of party autonomy. In addition, the study discovered that, even while AI can be a useful tool to help arbitration, relying too much on opaque algorithms runs the risk of compromising due process, transparency, and the validity of arbitral decisions. The study concludes that whereas the merits of the use of AI in arbitration cannot be overestimated, care must be exercised to consider the shortcomings of AI. The study recommends the need for AI specific enactment in Nigeria.