Impact of Generative AI in Legal Practice

One of the big questions that should be occupying law firms and legal departments in the next year: how much of my existing tech stack will be / can be replaced by LLMs, for example by buying into an AI Legal Assistant or building a proprietary #AI chatbot? I've heard stories about firms hoping to replace their full enterprise search system with a custom LLM, or expecting that document automation will be fully replaced with generative AI. To that I say: not so fast. While this shiny new technology has astonishing capabilities, it cannot replace incumbents for complex use cases unless it is coupled with thoughtful UX and an interface that allows lawyers to leverage the technology sensibly within their practice. The successful market leaders in spaces like contract review, document automation, and search are successful not just because of underlying technology but because there has been a tremendous amount of thought given to the way users work, and what users need from a system within a particular workflow. Replacing or replicating really good UX for a specific problem takes time, and no amount of AI can cover up for the absence of UX. In this first of several articles exploring where law firms and legal departments can get real value from generative AI and LLMs, I look at a number of use cases to determine whether existing licenses can be replaced with new AI solutions, or whether it's worth hanging on to what you've got for a while longer. #legaltech #UXdesign #workflowautomation #processimprovement

Dr. Saju Skaria's Weekly Reflections: 20/2023 Intellectual Property (IP) issues and Generative AI The use of Generative AI has taken the industry by storm. I thought it’s imperative to touch on this critical issue, i.e., intellectual property, before we close the discussions on AI. AI technology, leveraging data lakes and question snippets to recover patterns and relationships, is helping immensely in creative industries. However, we have a critical issue that the legal fraternity is trying to address: copyright infringement, ownership of AI-generated work, and leveraging unlicensed content in training data. Trained AI tools can replicate copies of original work (for example, paintings or photographs), which is a copyright infringement. A further challenge is that the users might create copies of the original that need to be more transformative, thereby causing the credibility of the original work. These unauthorized derivatives can cause significant penalties, and the courts are already dealing with such issues. There is significant debate around the “fair use doctrine” that allows reviewing the copyrighted without the owner’s permission for purposes like criticism (including satire), comment, news reporting, teaching (including multiple copies for classroom use), scholarship, or research,” and for transformative use of the copyrighted material in a manner for which it was not intended. A word of caution for companies is how to use Generative AI and leverage content. It’s a tightrope walk. Not even accidentally using copyrighted content, directly or unintendedly, without adequate protection can cause significant penalties. How could we reduce the risk of getting stuck in an IP violation? Here are a few recommended steps. 1.     AI developers (individuals /organizations) must ensure that they comply with the law regarding acquiring data to train their models. 2.     Creators, both individual content creators and brands that create content, should take steps to examine risks to their intellectual property portfolios and protect them. 3.     Businesses should evaluate their transaction terms to write protections into contracts. As a starting point, they should demand terms of service from generative AI platforms that confirm proper licensure of the training data that feed their AI. Finally, with appropriate protection, businesses can build portfolios of works and branded materials, meta-tag them, and train their generative AI platforms to produce authorized, proprietary (paid-up or royalty-bearing) goods as sources of instant revenue streams. I welcome your thoughts and views on the topic. #AI #Leadership Bharat Amin, NACD.DC ML Kabir Sandeep (Sandy) M. Krishnan CA Randhir Mazumdar Dr. Swati Karve, PhD Psychology Ashish Saxena Shiny Skaria

In the vanguard of legal innovation, generative AI (GAI) is propelling the legal profession into a new era of efficiency and expanded capabilities. A recent survey reveals a significant embrace of GAI within the Am Law 200 firms, showcasing a shift from skepticism to adoption with compelling evidence of enhanced productivity, quality, and speed in legal tasks when leveraging tools like GPT-4. The impact of AI in law extends beyond mere productivity enhancements: -Evolving Lawyer Roles: As tasks become automated, lawyers are transitioning from doing to directing, focusing on integrating AI into workflows, managing automated processes, and ensuring precise engagement of resources. -Enhanced Predictive Analytics: Improved data quality from automation leads to more accurate case analysis and financial forecasting, enabling firms to optimize case selection and fee structures. -Access to Information Revolutionized: Natural Language Interfaces (NLIs) like Harvey offer direct, query-based access to legal information, simplifying research and compliance checks. -Emergence of New Legal Services: Nearly half of law firm leaders are exploring new billable services powered by GAI, including real-time regulatory compliance and data privacy services. As we stand at the precipice of this transformative period, it's clear that AI's role in legal practice is not just a fleeting trend but a cornerstone of future legal services. Transforming the Business of Law™ Let's explore how to future-proof your practice and offer innovative solutions to your clients. #LegalTech #AIInLaw #FutureOfLaw #LegalInnovation #GenerativeAI

The legal industry needs a more thoughtful approach to generative AI. Our customers are reporting larger gaps between what a tech company says they can do with AI vs. what they can actually do. Take these 7 steps to get the most out of your AI pilot: 1. Prepare a roadmap for what your legal department would like to achieve with 1-year, 3-year, and 5-year benchmarks — since almost all legal tasks can benefit from language models, pick a first use-case that will have the biggest impact or ROI. 2. Define what success would mean for you with this use-case. Ideally in a way that you can tie to objective metric-oriented results or outcomes. 3. Break the problem into pieces. Try to figure out how useful the AI you’re testing will be for this use-case in its broken down pieces. Test several language models to get a gold standard metric of quality on each component. 4. Prepare an evaluation dataset, so you know “this is in the input” and “this is the desired output” 5. Discover what the models you’re testing can do with no training (’zero shot’). Establish a baseline. 6. See how the models improve with low investment techniques like prompt engineering or “few shot” training where you embed a few examples into your prompt. Try to get numbers on the board. Are you achieving the success metrics you were shooting for? 7. Explore how higher-investment strategies like fine-tuning would improve the output. Although it can be tempting to let FOMO and excitement around generative AI push us to move fast, the companies who take the time to implement a thoughtful approach are in a better position to benefit the most from AI. Don’t let ROI become an afterthought.

There is some speculation in the legal industry that firms may be dragging their feet on AI adoption because it breaks their profit model. Why have a machine do work that takes hours in seconds — when doing so won't make you more money? But ARE firms dragging their feet? Interestingly, one of the spiciest findings of our 2024 State of Generative AI In Legal survey report released in March is that GenAI use is already pervasive across top-tier law firms. In the Global 100, 53% of firms responding to our survey last November reported they were using GenAI for billable work. And another 40% reported they were planning to do so within the next 6 months (i.e. they’re likely now already doing so). While some firms might be dragging their feet on GenAI, I think the more likely truth is that they’re already fast at work strategizing how GenAI will enable a new service delivery model and lines of profitability. The outstanding question is how that new model will pass on the benefit of these new efficiencies to their clients. As Moderna CLO Shannon Thyme Klinger shared in our latest webinar on AI in legal, there’s a lot more work to be done to reassess what value creation looks like between firms and legal departments. As firms design how they will leverage GenAI to enable a new service delivery model, clients need to be the ones leading the conversation to ensure that they are capturing the appropriate value from that new model.

Legal Eagles, Meet Your AI Copilot: How Generative AI Is Revolutionizing Legal Research The legal landscape is notoriously demanding. Mountains of precedent, evolving statutes, and ever-expanding case law create a dizzying maze for even the most seasoned legal minds. But imagine a powerful research assistant in your corner, capable of analyzing vast datasets, extracting pertinent information, and generating comprehensive insights – enter generative AI. This game-changer in legal research brings unprecedented speed, accuracy, and efficiency to the game: * Uncover Hidden Gems: AI can sift through oceans of legal data, identifying relevant cases, statutes, and scholarly articles you might have missed, even in obscure jurisdictions. No stone goes unturned in your search for the strongest arguments. * Go Deep, Dive Fast: Need precise legal arguments on a niche point? AI can analyze complex legal concepts and break them down into clear, actionable insights, saving you hours of painstaking research. * Predict Case Outcomes: Certain AI models can analyze past judgments and precedents to predict potential outcomes, giving you a crucial edge in crafting your legal strategy. The benefits extend far beyond just efficient research: * Enhanced Confidence: Informed by a comprehensive review of relevant legal material, you can approach your case with greater confidence, knowing you've left no stone unturned. * Improved Client Services: Dedicate more time to high-value client interaction and strategic planning, rather than getting bogged down in research. * Cost Savings: Streamlining research processes means saving time and resources, making your legal practice more efficient and cost-effective. Of course, embracing AI doesn't mean replacing human judgment. AI remains a powerful tool to augment your expertise, not replace it. Critical thinking, analytical skills, and strategic acumen are still the cornerstones of a successful legal career. Ready to level up your legal research game? 1) Share your biggest research challenges in the comments. 2) Let's discuss how AI can help you overcome them and build rock-solid legal arguments. #LegalAI #GenerativeAI #LegalResearch #LawPractice #Efficiency #Innovation P.S. Don't forget to like & share!

🔦 There's an interesting thing happening as generative AI use becomes more prevalent: it's shining a light on sloppy lawyering. 📰 I talk about this in my latest Above the Law Column, "Judges To Generative AI: You're Out Of Order!" ✅ In my article, I list many examples of cases in 2024 where lawyers relied on AI-generated false citations in papers submitted to courts. 💡 While some suggest GenAi is the problem, I disagree. What we're seeing is hard and fast evidence of what's been happening all along: some lawyers fail to review submissions before filing them with the court. ⚖ Judges are understandably frustrated by this clear, blatant negligence but are attempting to rein it in by shooting the messenger, GenAi, rather than addressing the problem: lawyer competence. ❌ Thus far 48 different court-sponsored efforts to regulate or ban AI usage are underway across the country in the form of promulgated or pending court orders, guidelines, and rules. 🔁 In other words, there’s disorder in the courts, with no clarity in sight. 🚫 Knee-jerk reactions to GenAi aren't the solution. ❎ Instead we need to focus on establishing a uniform approach to responsible AI use grounded in the timeless principles of careful review and thorough legal analysis. 🗣 At least, that's what I think. What's your take? Let us know in the comments. 🔗 Link to the article and the document that tracks the judicial orders in the comments. #legaltech #generativeAI #ethics #AI

#LLM #GENAI #LAW: #Hallucinate, much? Much anecdotal evidence supports that thesis in #GenerativeAI's clumsy foray into law, but research at Stanford University Human-Centered #ArtificialIntellience delivers hard data. Here are just a couple of findings from Stanford's recent study: - "[I]n answering queries about a court’s core ruling (or holding), models hallucinate at least 75% of the time. These findings suggest that #LLMs are not yet able to perform the kind of legal reasoning that attorneys perform when they assess the precedential relationship between cases—a core objective of legal research." - "Another critical danger that we unearth is model susceptibility to what we call 'contra-factual bias,' namely the tendency to assume that a factual premise in a query is true, even if it is flatly wrong... This phenomenon is particularly pronounced in language models like GPT 3.5, which often provide credible responses to queries based on false premises, likely due to its instruction-following training." Read the full article here: https://lnkd.in/gEab43qK

In a pioneering move, the California Bar has approved new ethics guidelines for lawyers using AI. This marks a significant advancement in integrating AI with legal ethics. Key Points:  1. Lawyers are encouraged to disclose the use of generative AI to clients. 2. Charging hourly fees for time saved by AI tools is discouraged. 3. Human scrutiny is essential to ensure AI outputs are free from inaccuracy and bias. These guidelines represent an interim step in adapting legal practices to evolving AI technologies, while future rules and regulations are developed. It's a move towards ensuring AI's potential is harnessed responsibly in the legal field.

✨ If you had asked me 5 years ago if I'd be using AI to review my executed contracts to extract metadata today, I would have thought you were nuts. At the time, I was beta testing an AI product as part of our CLM. Let's just say it appeared to create work, not reduce it. ✨ If you had asked me 3 years ago if I'd be using generative AI to review draft contracts, relying on it to highlight areas to be addressed, and leveraging AI-generated redlines, I would have thought you were nuts. At the time, I was helping train models to identify non-standard contract language. It seemed like a lot of work for little to no reward. ✨ Today, I rely on AI extracted metadata on the daily and I use generative AI playbooks to review contracts on first pass. The "me of the past" was clearly wrong, but I'm honestly glad I was proven wrong (even though there isn't much i hate more than being proven wrong). We're in legal - being skeptical and analyzing risk is part of our job. But this doesn't mean shying away from technology because they it is new and haven't been perfected yet. Give the tech time to mature. If you're early on your AI journey, you're right where you are supposed to be. Take your time in finding the right problems to solve with AI rather than rushing to use AI because it seems like everyone else is. ❓ Anyone else actually leveraging AI to augment their legal work? I'd love to hear how in the comments below (especially if, like me, you were a skeptic at first!) #legalops #legaltech #inhouselegal #legalinnovation #legalai