From Innovation to Implementation: The Ethics of Generative AI in Law Firms
This episode is sponsored by Lawline
In this episode of On Record PR, sponsored by Lawline, Gina Rubel goes on record with Shawn Swearingen, Chief Innovation Officer of Faegre Drinker, to discuss the practical applications of generative AI for the legal industry and its ethical challenges.
In the era of digital transformation, Artificial Intelligence (AI) has emerged as a powerful tool with transformative potential for the legal industry. As law firm administrators, managers, and marketers, it is crucial to understand the implications and opportunities that generative AI such as Large Language Models (LLMs) and other technologies present. This episode provides legal professionals with the knowledge and insights they need to navigate the complexities of the Generative AI Revolution while mitigating a myriad of risks. By adopting a balanced approach, law firms can leverage generative AI to improve efficiencies, deliver enhanced client services, and drive business excellence.
Key topics include:
- Review Generative AI: The underlying technologies, including machine learning and natural language processing, and use cases that demonstrate the potential of generative AI in legal research, contract analysis, document automation, and more.
- Identify Benefits and Opportunities: Insights into how generative AI can streamline routine tasks, improve decision-making processes, and enable lawyers to focus on higher-value activities, ultimately providing a competitive edge.
- Examine Policy Considerations: The ethical challenges surrounding bias, data privacy, confidentiality, and intellectual property risks, along with strategies to address these concerns and ensure responsible AI use.
- Change Management and Integration: Strategies for overcoming resistance, training, fostering user adoption, and nurturing a culture that embraces innovation.
For discounted access to the full CLE recording of this session on Lawline’s website, visit: www.lawline.com/furiarubel