5 Best Practices for Responsible Use of Generative AI tools in the Legal Profession
Technological advancements have affected professionals throughout history. In fact, the shift from human labour to technological solutions was largely responsible for the 20th century’s productivity rise. The legal profession is in general notoriously averse. Even with the invention of typewriters then, lawyers and judges continued to produce their work by hand for centuries. In fact, some of them continue to write their drafts in this manner to this day. However, change happened quickly; by the turn of the century, the world of paper, which was familiar to lawyers, had given way to the electronic system of today.
Modern technology has since infiltrated law firms and courtrooms. One notable example in Uganda is the Judiciary’s Electronic Court Case Management Information System (ECCMIS), which allows lawyers and clerks to electronically submit pleadings and other court documents whenever and from anywhere, thereby minimizing the volume of paperwork.
We are now faced with the latest technological frontier; artificial intelligence. Generative AI tools can augment legal practice by providing efficient ways of solving problems and serving more clients however, they are a double-edged sword with possible risks and ethical dilemmas. The use of these tools must always adhere to the highest ethical standards of the legal profession where credibility is paramount and reputation is everything. This article delves into some of the best practices that can enable responsible use of Generative AI tools by legal professionals in Uganda and world over.
1. Understand the Technology
Ensure that you possess a good understanding of AI tools utilized in legal practice. Do not be a passive observer, take time to familiarize yourself with the capabilities, functionalities and potential legal implications of these tools. This can be through reading books, legal journals, regulations on AI or crash courses. Acquiring this knowledge will empower you to make informed decisions regarding appropriate and responsible utilization of these tools.
2. Prompt engineering
The real skill in using these systems lies in the questions you ask through prompts (input). Prompt engineering is the practice of creating and refining text prompts to guide generative AI tools towards generating desired outputs. It involves constructing specific and concise instructions for the AI model to process. Remember the quality of your prompt shapes the quality of your outcome. Most of these Gen AI tools follow the guiding parameters you provide, one can instruct the tool on what tones to use in its responses, how the responses should be formatted and even make it assume a specific role for a given output. Learn more about crafting good prompts here.
3. Private Large Language models (LLMs)
Large language models are super-powered language tools trained on massive sets of data to generate human-like output. Public LLMs like Chat GPT have open access and are trained on public data sets such as books, articles and websites. In contrast, Private LLMs have restricted access, are trained on the firm’s data and developed exclusively for and by the firm or enterprise.
Law firms can consider acquiring or developing their own AI models (Private LLMs). While costly, private LLMs are guardians of data privacy due to their exclusive use of in-house data ensuring confidentiality of sensitive information by granting access to only authorized personnel. Law firms in other jurisdictions have begun building their own AI models as seen here.
In a bid to acquire a private LLM, be sure to vet AI system vendors (programmers) thoroughly by asking about data handling, security measures and liability in case of a security breach.
4. Exercise Due Diligence
Never rely solely on information from a Generative AI output without conducting your own independent verification to confirm its accuracy. One should beware of common risks such as biases and hallucinations. It is critical to review output not just for accuracy but to make sure there is no potential infringement of copyright. As a general rule, all information produced must be cross-referenced.
5. Data Protection and Privacy
Lawyers should be mindful of feeding client data into Gen AI tools as these tools do not only process data offered by the user to generate responses but also employ it in enhancing their systems. These technologies have the ability to replicate information from one user’s query to the next user, which underscores the need for robust security measures to safeguard against unauthorized access or disclosure of sensitive data and adhere to legal obligations related to client confidentiality. Examples of robust security mechanisms include encryption protocols, user authentication, secure storage and regular audits to identify vulnerabilities.
In conclusion, the legal landscape is constantly evolving, responsible AI adoption is no longer a ‘maybe’ but a ‘must’. By embracing these practices, legal professionals can position themselves to be at the forefront of effective service delivery.