Please enjoy this blog post co-authored by Christiane Matuch, Legal Innovation Manager, Greenberg Traurig, LLP and Paul Giedraitis, CEO, Orgaimi.
Many legal innovation professionals will tell you that innovation in a vacuum has minimal chance of successful adoption. As the adage goes, to find a solution that “sticks” you must first identify the problem(s) you are solving. While this principle generally holds true within the legal industry, in the rapidly evolving landscape of artificial intelligence, a traditional approach of focusing only on solving existing problems is no longer sufficient. Of course, addressing current challenges is essential. However, embracing thoughtful experimentation is equally important for driving innovation and unlocking the full potential of AI.
Experimentation in AI allows researchers, data scientists, and developers to venture beyond established boundaries. It encourages creative thinking and the exploration of unconventional ideas that might not have immediate practical applications. This creative freedom can lead to unexpected discoveries, much like how the internet itself emerged from experimental projects that initially had no clear commercial purpose.
Adapting to an Unpredictable Future
The future is inherently uncertain, and the problems we are solving today may not be the same ones tomorrow. By supporting a culture of experimentation, we expand from targeted problem solving into real grassroots innovation, which means finding truly new ways to support legal services and operations. Experimentation enables the development of flexible systems that can be repurposed or evolved to address new, unanticipated opportunities. This adaptability is becoming more and more essential in a world where technology and societal landscapes are constantly changing. Many of our most significant advancements have arisen from experiments that initially seemed irrelevant or tangential from an economic perspective. For instance, machine learning algorithms that were once theoretical exercises now underpin everything from voice assistants to document generation to autonomous vehicles.
Encouraging Interdisciplinary Collaboration
Experimentation often involves crossing disciplinary boundaries, bringing together diverse perspectives, skills, and expertise. In law, this interdisciplinary collaboration does not only come from spanning across practices or industries, but also by expanding solutions from the service delivery side to the enterprise level and vice versa. For example, applications that were developed to curate legal services content might be leveraged to curate enterprise-wide content to support internal operational needs. AI capabilities or analyses initially designed for legal teams to support their roles in legal service delivery can be quickly repurposed to enterprise firm functions and legal operations teams. When combined with an understanding of how people and internal processes work together, such collaboration can lead to more robust and human-centered AI solutions, fostering systems that are not only vastly more efficient but also ethically sound and socially beneficial.
Fostering a Culture of Learning
A critical component of an experimentation-based approach is nurturing a culture of continuous learning and improvement. It allows practitioners to learn from failures and iterate on ideas, leading to more refined and effective solutions that can quickly adapt to how stakeholders and teams actually work. This iterative process is essential for developing AI systems and applications that are resilient, reliable, and capable of tackling complex problems in dynamic environments.
In conclusion, while solving existing problems is a vital aspect of AI development, embracing thoughtful experimentation is what will truly drive our field forward in terms of innovation. By encouraging creativity, adaptability, and interdisciplinary collaboration, we can unlock new possibilities and prepare for the challenges of tomorrow. Looking to the future, experimentation is not just an option – it is a necessity for the continued evolution and success of artificial intelligence in the legal industry.
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