Crossing the Rubicon: Evaluating the use of artificial intelligence in the law and Singapore Courts

• Main Author: TOR, Ming En
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: law; artificial intelligence; AI; technology; Singapore courts; Science and Technology Law
• Online Access: https://ink.library.smu.edu.sg/sol_research/3917; https://ink.library.smu.edu.sg/context/sol_research/article/5875/viewcontent/CTR_Article.pdf
• Institution: Singapore Management University

In recent years, Artificial Intelligence (“AI”) has challenged many fundamental assumptions of how organisations and industries should operate. The Courts, traditionally seen as a hallowed ground graced by the best of lawyers, still remains as unchartered territory for AI’s infiltration. Yet, there is growing evidence which suggest AI may soon cross this frontier to replace important court functions. This paper critically assesses the use of AI in law and the courts. Part II will first examine the arguments for and against the adoption of AI in the legal profession. Thereafter, Part III will critically examine whether AI should replace judges in the courts. Based on the analysis, the paper provides some detailed recommendations on how AI integration with the courts should be conducted in Singapore. In view of the possible threats against AI applications, Part IV provides a security and safety framework which guides Singapore courts in the adoption of AI. Against the backdrop of this paper’s recommendations, Part V will then discuss how automated AI judging may be done in the context of property disputes. Finally, Part VI concludes that AI integration should be readily welcome amongst legal practitioners, while AI should support instead of replacing current human judges. The implementation of AI should also be done in a calibrated, gradualist fashion. Unless AI judges can overcome their technical limitations in replicating judgecraft, AI should not be thrust into high responsibility judging roles on their own.