Turing Test and the Practice of Law: The Role of Autonomous Levels of AI Legal Reasoning
This addresses the need for evaluation standards in AI applied to law, but it is incremental as it adapts an existing test to a specific domain.
The paper tackles the problem of assessing when AI Legal Reasoning (AILR) achieves autonomous capabilities by proposing a variant of the Turing Test customized for the AILR domain, aiming to provide a robust method for evaluating autonomous levels in legal reasoning.
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.