2020/08/18 by Lance B. Eliot, Eliot, Lance
Computer Science · Economics, Econometrics and Finance · Social Sciences · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Law #Computers and Society (cs.CY) #FOS: Computer and information sciences #I.2.0 #J.7.0 #K.5.9 #Law, AI, and Intellectual Property #Law, Economics, and Judicial Systems
paper · pdf · doi:10.48550/arxiv.2008.07743
openalex publication_date 2020/08/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Artificial Intelligence (AI) is increasingly being applied to law and a myriad of legal tasks amid attempts to bolster AI Legal Reasoning (AILR) autonomous capabilities. A major question that has generally been unaddressed involves how we will know when AILR has achieved autonomous capacities. The field of AI has grappled with similar quandaries over how to assess the attainment of Artificial General Intelligence (AGI), a persistently discussed issue among scholars since the inception of AI, with the Turing Test communally being considered as the bellwether for ascertaining such matters. This paper proposes a variant of the Turing Test that is customized for specific use in the AILR realm, including depicting how this famous gold standard of AI fulfillment can be robustly applied across the autonomous levels of AI Legal Reasoning.