Articles and Columns for September 2023 Adding a ‘Group Advisory Layer’ to Your Use of Generative AI Tools Through Structured Prompting: The G-A-L Method – The emergence of Large Language Models (LLMs) in legal research signifies a transformative shift – Dennis Kennedy asks us to Imagine a world where expert advice is at your fingertips, instantly …
Dennis Kennedy asks us to Imagine a world where expert advice is at your fingertips, instantly available, tailored just for you. Think of a tool that’s always ready to give expert advice, without the need for complex coding or tech skills. The Group Advisory Layer Method (G-A-L Method™) revolutionizes decision-making by merging traditional principles of mastermind groups and advisory boards with the cutting-edge capabilities of generative AI. Traditional advisory boards, often hindered by logistics and time constraints, meet their match as the G-A-L Method offers on-demand, diverse, and tailored insights, all without the real-world hassle. It’s like having a virtual team you can chat with any time, made up of tireless AI-created ‘personas’ that act like real people. Instead of juggling schedules or waiting for feedback, you get quick and practical tips from this always-on expert team. The G-A-L Method pioneers dynamic group interactions using personas to give you practical, just-in-time expert advice. What’s more, it makes sure real people (like you) are involved where they add the most value. With the G-A-L Method, you’re not just listening to machines – you’re teaming up with them. This white paper by Dennis Kennedy, well-known legal tech and innovation advisor, law professor, infotech lawyer, professional speaker, author, and podcaster, is an invitation to unlock the untapped potential of these generative AI tools in a practical, structured way to move your efforts forward. Kennedy states that we are poised at the brink of a transformative era where informed decisions can be made rapidly and confidently. The G-A-L Method is more than a technique—it’s a game-changer.
The pace of generative AI development (and hype) over the past year has been intense, and difficult even for us experienced librarians, masters of information that we are, to follow. Not only is there a constant stream of new products, but also new academic papers, blog posts, newsletters, and more, from people evaluating, experimenting with, and critiquing those products. With that in mind, Rebecca Fordon shares her favorites, as well as recommendations from her co-bloggers.
Privacy and cybersecurity issues impact every aspect of our lives – home, work, travel, education, finance, health and medical records – to name but a few. On a weekly basis Pete Weiss highlights articles and information that focus on the increasingly complex and wide ranging ways technology is used to compromise and diminish our privacy and online security, often without our situational awareness. Four highlights from this week: Hundreds of millions of individuals’ personally identifiable information” is impacted by the privacy weaknesses, according to the Government Accountability Office; Report: Insider Cybersecurity Threats Have Jumped 40% in 4 Years; iOS 17: iPhone Users Report Worrying Privacy Settings Change After Update; and China Cyber Threat Overview and Advisories.
Professor Aarushi Bhandari was taken aback when she learned that not a single student had heard that the Writers Guild of America had reached a deal with the Alliance of Motion Picture and Television Producers, or AMPTP, after a nearly 150-day strike. This historic deal includes significant raises, improvements in health care and pension support, and – unique to our times – protections against the use of artificial intelligence to write screenplays. Across online media platforms, the WGA announcement on Sept. 24, 2023, ended up buried under headlines and posts about the celebrity duo of Taylor Swift and Chiefs tight end Travis Kelce. To Bhandari, this disconnect felt like a microcosm of the entire online media ecosystem.
Hallucinations in generative AI are not a new topic. If you watch the news at all (or read the front page of the New York Times), you’ve heard of the two New York attorneys who used ChatGPT to create fake cases entire cases and then submitted them to the court. After that case, which resulted in a media frenzy and (somewhat mild) court sanctions, many attorneys are wary of using generative AI for legal research. But vendors are working to limit hallucinations and increase trust. And some legal tasks are less affected by hallucinations. Law Librarian and attorney Rebecca Fordon guides us to an understanding of how and why hallucinations occur and how we can effectively evaluate new products and identify lower-risk uses.
Human factors engineer James Intriligator makes a clear and important distinction for researchers: that unlike a search engine, with static and stored results, ChatGPT never copies, retrieves or looks up information from anywhere. Rather, it generates every word anew. You send it a prompt, and based on its machine-learning training on massive amounts of text, it creates an original answer. Most importantly, each chat retains context during a conversation, meaning that questions asked and answers provided earlier in the conversation will inform responses it generates later. The answers, therefore, are malleable, and the user needs to participate in an iterative process to shape them into something useful.
Privacy and cybersecurity issues impact every aspect of our lives – home, work, travel, education, finance, health and medical records – to name but a few. On a weekly basis Pete Weiss highlights articles and information that focus on the increasingly complex and wide ranging ways technology is used to compromise and diminish our privacy and online security, often without our situational awareness. Four highlights from this week: New Privacy Badger Prevents Google From Mangling More of Your Links and Invading Your Privacy; Microsoft AI team accidentally leaks 38TB of private company data; California legislature passes ‘Delete Act’ to protect consumer data; and Starlink lost over 200 satellites in two months.
Jim Calloway, Director of the Oklahoma Bar Association’s Management Assistance Program and Julie Bays, OBA Practice Management Advisor, aiding attorneys in using technology and other tools to efficiently manage their offices, recommend that now is a good time to experiment with specific AI-powered tools and suggest the best techniques for using them.
Legaltech Hub’s Nicola Shaver discusses why it is time to level-set about advanced AI: it can’t do everything. Or perhaps more practically, a large language model can’t replace all of the other technology you already have. One of the main reasons for this is the importance of an interface and a built-out user experience (UX) that offers a journey through the system that is aligned with the way users actually work. There are other reasons a large language model (LLM) won’t replace all of your technology (one of which being advanced AI is simply unnecessary to do all things), but this article will focus on UX.