Conclusion
There is no question that the emergence of generative AI is transformative in many sectors, and it is predicted to have significant impact on the legal profession as well. There is a preponderance of tools on the market, and these are ever evolving and improving. Lawyers and firms must educate themselves on the potential benefits of using generative AI to deliver legal services while also educating themselves on associated risks and how to mitigate them. Legal professionals must keep abreast of technological initiatives that can assist in the delivery of legal services to their clients and consider the potential impacts upon quality of service and how legal fees are charged.
Lawyers must be mindful of their professional ethical obligations as outlined in the Model Code, paying particular attention to duties relating to competency, confidentiality, supervision, communication, treating tribunals with courtesy and respect, charging fees, guarding against discrimination, harassment and bias, integrity and honesty. In addition, lawyers must take care to ensure compliance with any applicable laws relating to generative AI use and must be aware of existing and emerging rules with extra-territorial impact (e.g. GDPR and EU AI Act).
Cases involving lawyers and their inappropriate use/reliance of generative AI to submit court documents, are unfortunate examples of the inexperienced use of a new technology without an understanding of its strengths and weaknesses.
Generative AI tools are not replacements for lawyers. Lawyers, equipped with their training and judgment, need to be the “humans in the loop” when legal services are with the use generative AI.
Before acquiring and using any generative AI tool, lawyers and firms should conduct appropriate research and undertake careful due diligence, about evolving best practices.
Lawyers and firms should responsibly anticipate risks and guard against them, including by developing human resources management tools to ensure organizational awareness of and compliance with AI policies and procedures internally. These should be regularly revised, tested, and updated. Internal committees should promote diversity and consider appropriate audit mechanisms that include ways to guard against discrimination and bias.