Large Language Models

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This week we bring in Christian Lang, the CEO and founder of LEGA, a company that provides a secure platform for law firms and legal departments to safely implement and govern the use of large language models (LLMs) like Open AI’s GPT-4, Google’s Bard, and Anthropic’s Claude. Christian talks with us about why he started LEGA, the value LEGA provides to law firms and legal departments, the challenges around security, confidentiality, and other issues as LLMs become more widely used, and how LEGA helps solve those problems.

Christian started LEGA after gaining experience working with law firms through his previous company, Reynen Court. He saw an opportunity to give law firms a way to quickly implement and test LLMs while maintaining control and governance over data and compliance. LEGA provides a sandbox environment for law firms to explore different LLMs and AI tools to find use cases. The platform handles user management, policy enforcement, and auditing to give firms visibility into how the technologies are being used.

Christian believes law firms want to use technologies like LLMs but struggle with how to do so securely and in a compliant way. LEGA allows them to get started right away without a huge investment in time or money. The platform is also flexible enough to work with any model a firm wants to use. As law firms get comfortable, LEGA will allow them to scale successful use cases across the organization.

On the challenges law firms face, Christian points to Shadow IT as people will find ways to use the technologies with or without the firm’s permission. Firms need to provide good options to users or risk losing control and oversight. He also discusses the difficulty in training new lawyers as LLMs make some tasks too easy, the coming market efficiencies in legal services, and the strategic curation of knowledge that will still require human judgment.

Some potential use cases for law firms include live chatbots, document summarization, contract review, legal research, and market intelligence gathering. As models allow for more tailored data inputs, the use cases will expand further. Overall, Christian is excited for how LLMs and AI can transform the legal industry but emphasizes that strong governance and oversight are key to implementing them successfully.

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Twitter: ⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠, or ⁠⁠⁠⁠@glambert⁠⁠⁠⁠
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Music: ⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠

⁠⁠Transcript⁠

Continue Reading Christian Lang on Governing the Rise of LLMs: How LEGA Provides a Safe Space for Law Firms to Use AI (TGIR Ep. 206)

This week we have Damien Riehl, VP, Litigation Workflow and Analytics Content at FastCase, and one of the drivers behind SALI (Standards Advancement for   for the Legal Industry.) Damien is definitely a “big thinker” when it comes to the benefits of creating and using standards for the legal industry. SALI is a system of tagging legal information to allow for better filtering and analysis. It works like Amazon’s product tags, where a user can search for a specific area of law, such as patent law, and then choose between various services such as advice, registration, transactional, dispute, or bankruptcy services. The tags cover everything from the substance of law to the business of law, with over 13,000 tags in the latest version. SALI is being adopted by major legal information providers such as Thomson Reuters, Lexis, Bloomberg, NetDocuments, and iManage, with each provider using the same standardized identifiers for legal work. With this standardization, it will be possible to perform the same API query across different providers and receive consistent results. Imagine the potential of being able to ask one question that is understood by all your database and external systems?
In that same vein, we expand our discussion to include how Artificial Intelligence tools like Large Language Models (i.e., ChatGPT, Google BARD, Meta’s LLM) could assist legal professionals in their quest to find information, create documents, and help outline legal processes and practices.
He proposed three ways of thinking about the work being done by these models, which are largely analogous to traditional methods. The first way is what Riehl refers to as a “bullshitter,” where a model generates information without providing citations for the information. The second way is called a “searcher,” where a model generates a legal brief, but does not provide citations, forcing the user to search for support. The third way is called a “researcher,” where the model finds relevant cases and statutes, extracts relevant propositions, and crafts a brief based on them.
Riehl believes that option three, being a researcher, is the most likely to win in the future, as it provides “ground truth” from the start. He cites Fastcase’s acquisition of Judicata as an example of how AI can be used to help with research by providing unique identifiers for every proposition and citation, enabling users to evaluate the credibility of the information. In conclusion, Riehl sees a future where AI is used to help researchers by providing a pick list of the most common propositions and citations, which can then be further evaluated by the researcher.
One thing is very clear, we are just at the beginning of a shift in how the legal industry processes information. Riehl’s one-two combination of SALI Standards combined with additional AI and human capabilities will create a divide amongst the bullshitters, the searchers, and the researchers.

Listen on mobile platforms:  Apple Podcasts LogoApple Podcasts |  Spotify LogoSpotify
Contact Us:
Twitter: @gebauerm, or @glambert
Voicemail: 713-487-7821
Email: geekinreviewpodcast@gmail.com
Music: Jerry David DeCicca
Transcript

Continue Reading The Bullshitter, The Searcher, and The Researcher – Damien Riehl on the Dynamic Shift in How the Legal Profession Will Leverage Standards and Artificial Intelligence