23)
Copyright © 2023 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Published at http://ceur-ws.org. investigation. In the very near future, these advancements may contribute significantly to the enhanced efficiency and effectiveness of legal practitioners and law firms, enabling them to better serve their clients and navigate complex legal landscapes.
Furthermore, the integration of machine learning and other AI technologies over the past decade has substantially improved legal professionals' abilities to access, process, and analyze digital information. Advanced search algorithms, information extraction and visualization techniques, data summarization, classification, and review processes have all been significantly enhanced through AI breakthroughs. The advent of generative AI has further expanded the capabilities of these technologies, pushing the boundaries of what can be achieved in the legal domain.
However, as the adoption of AI in the legal field continues to grow, concerns regarding transparency and the limitations of fully automated approaches have come to the forefront. This has sparked a renewed interest in methodologies that combine human intelligence with AI, leading to the emergence of the "humanin-the-loop" approach. Rather than replacing human professionals, intelligent assistance (IA) seeks to augment their capabilities, leveraging the unique cognitive abilities and expertise that humans possess.
The debate over the role of AI in the legal profession, whether it should replace or augment human professionals, is not new. It spans over half a century, with perspectives vacillating over time. Currently, the pendulum is shifting towards the augmentation or IA perspective, recognizing the value of human expertise in conjunction with AI technologies. However, it is essential to emphasize that not all human-AI collaboration yields fruitful outcomes. Understanding the nature, extent, and efficiency of human contributions in various applications is crucial to ensuring effective deployment of resources and efforts.
Thus, the Third International Workshop on Artificial Intelligence and Intelligent Assistance for Legal Professionals in the Digital Workplace seeks to explore these themes in depth. It aims to facilitate interdisciplinary discussions and collaboration among legal professionals, AI researchers, and technologists. By sharing cutting-edge research, practical experiences, and thought-provoking discussions, the workshop aims to advance the understanding of AI and IA in the legal domain and explore ways to maximize the potential of human-AI collaboration.
In summary, this workshop provides a timely and valuable opportunity for legal professionals and AI researchers to come together and explore the transformative possibilities offered by AI in the legal field. By fostering dialogue and collaboration, we aim to shape the future of AI and IA in the legal profession, ensuring that these technologies serve as effective tools that augment and enhance the capabilities of legal professionals in the digital workplace.
This workshop will provide a platform for examining questions surrounding “AI as human augmentation” for legal tasks (a.k.a. Intelligent Assistance or IA), particularly those related to legal practitioners’ interaction with digital information. The focus of the workshop will be on better understanding the interaction between human and AI capabilities. The primary audience for the workshop will include working attorneys, legal researchers, computer science researchers, and AI providers in the legal industry.
Open questions remain about the conditions in which human interaction is necessary to produce more effective results, whether the human or AI should take the initiative in the collaboration, and whether or how increased interpretability and explainability of AI models is necessary for acceptable and successful human-AI collaboration in the legal domain. The ability of systems to analyze and identify exploitable patterns of human interaction and assessment in tasks like technology-aided discovery is a significant area of inquiry as well. Empirical comparisons between pure AI versus IA or human-augmented AI – favorable or unfavorable – in the form of user studies or simulations, are showcased. Proposals on how best to evaluate various methods of human augmentation are highlighted, as are analyses of the ethical implications of adopting AI as replacement versus AI as augmentation in legal applications.