Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics
The idea of artificial legal intelligence stems from a previous wave of artificial intelligence, then called jurimetrics. It was based on an algorithmic understanding of law, celebrating logic as the sole ingredient for proper legal argumentation. However, as Oliver Wendell Holmes has noted, the life of the law is experience rather than merely logic. Machine learning, which determines the current wave of artificial intelligence, is built on data-driven machine experience. The resulting artificial legal intelligence may be far more successful in terms of predicting the content of positive law. In this article, I discuss the assumptions of law and the Rule of Law and confront them with those of computational systems. As a twin article to my Chorley lecture on law as information, this should inform the extent to which artificial legal intelligence provides for responsible innovation in legal decision making.
The idea of artificial legal intelligence stems from a previous wave of artificial intelligence, then called jurimetrics. It was based on an algorithmic understanding of law, celebrating logic as the sole ingredient for proper legal argumentation. However, as Oliver Wendell Holmes has noted, the life of the law is experience rather than merely logic. Machine learning, which determines the current wave of artificial intelligence, is built on data-driven machine experience. The resulting artificial legal intelligence may be far more successful in terms of predicting the content of positive law. In this article, I discuss the assumptions of law and the Rule of Law and confront them with those of computational systems. As a twin article to my Chorley lecture on law as information, this should inform the extent to which artificial legal intelligence provides for responsible innovation in legal decision making.
Executive Summary
The article 'Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics' explores the evolution of artificial legal intelligence from the earlier field of jurimetrics to the current machine learning-driven approach. The author examines the assumptions underlying law and the Rule of Law, contrasting them with the principles of computational systems. The article argues that machine learning, by leveraging data-driven experiences, may better predict legal outcomes compared to traditional logic-based methods. This discussion is positioned as a complement to the author's previous work on law as information, aiming to guide responsible innovation in legal decision-making.
Key Points
- ▸ Evolution from jurimetrics to machine learning in artificial legal intelligence
- ▸ Contrast between logic-based and data-driven legal argumentation
- ▸ Assumptions of law and the Rule of Law versus computational systems
- ▸ Potential for machine learning to predict legal outcomes more accurately
- ▸ Role of artificial legal intelligence in responsible legal innovation
Merits
Comprehensive Historical Context
The article provides a thorough historical context, tracing the development of artificial legal intelligence from jurimetrics to contemporary machine learning, which enhances the understanding of current advancements.
Balanced Perspective
The author presents a balanced view by contrasting traditional legal logic with modern computational methods, offering a nuanced discussion on the potential and limitations of artificial legal intelligence.
Relevance to Legal Practice
The article's focus on practical implications for legal decision-making makes it highly relevant to both legal practitioners and academics.
Demerits
Lack of Empirical Evidence
While the article discusses theoretical frameworks and historical context, it lacks empirical evidence or case studies to support the claims about the effectiveness of machine learning in legal prediction.
Broad Generalizations
The article makes broad generalizations about the capabilities of machine learning without delving into specific algorithms or methodologies, which could limit the depth of the analysis.
Limited Discussion on Ethical Implications
The ethical implications of using artificial legal intelligence, such as bias and accountability, are not thoroughly explored, which is a significant oversight given the topic's importance.
Expert Commentary
The article 'Law as computation in the era of artificial legal intelligence: Speaking law to the power of statistics' offers a timely and insightful exploration of the intersection between law and artificial intelligence. The author's historical perspective provides a solid foundation for understanding the evolution of artificial legal intelligence, from the logic-based jurimetrics to the data-driven machine learning approaches of today. The contrast between traditional legal logic and modern computational methods is particularly compelling, as it highlights the potential for machine learning to enhance legal prediction and decision-making. However, the article could benefit from a more detailed examination of specific algorithms and methodologies, as well as empirical evidence to support the claims made. Additionally, the ethical implications of using artificial legal intelligence, such as bias and accountability, are not thoroughly explored, which is a significant oversight given the increasing integration of AI in legal practice. Overall, the article makes a valuable contribution to the ongoing discourse on the role of technology in law and sets the stage for further research and policy development in this critical area.
Recommendations
- ✓ Conduct empirical studies to validate the effectiveness of machine learning in legal prediction and decision-making.
- ✓ Explore the ethical implications of artificial legal intelligence, including issues of bias, accountability, and data privacy, to ensure responsible innovation in legal practice.
