Generative AI is coming for legal work, whether lawyers like it or not, and much of what it brings will be genuinely useful. Discovery, though, is a different conversation. Jerry Lawson discuses why technology-assisted review (TAR), the old, reliable workhorse, should remain a critical component of your organizations’ privileged document access management.
Before the volcano erupts, smart lawyers may want to think twice about investing too heavily in AI or thinking it’s a panacea for all problems – by Stephen Embry and Melissa Rogozinsk. All four parts of this series are available via links on each part of this series.
This comprehensive article by Bonnie Schucha explores and demonstrates the capabilities of Google’s NotebookLM, a free document-grounded AI tool designed to work exclusively with the materials you upload, and discusses what it means for an AI to be document grounded, why that matters for legal work, and how to use it effectively while keeping privacy and confidentiality in mind.
Jordan Furlong shares salient, focused and actionable thoughts about the future relationship between Gen AI and the legal profession. Furlong states that the more you study how Generative AI works, the more parallels emerge with how lawyers think — and that has implications. With Gen AI getting better every day, we need to get our act together, fast.
AI tools can do amazing things, such as make 3D models of digitized versions of the items in museum collections, but only if there’s enough well-organized data about that item available. To see how AI can help museum collections, Bradley Wade Bishop’s team of researchers started by conducting focus groups with the people who managed museum collections. We asked what they are doing to get their collections used by both humans and AI.
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. Dr. Michael Townsen Hicks, Dr. James Humphries and Dr. Joe Slater argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. They distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. They further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
Professor Richard Forno highlights the fragility of our enterprise IT systems against the backdrop of the global information technology outage on July 19, 2024 that paralyzed organizations ranging from airlines to hospitals and the delivery of uniforms for the Olympic Games, representing a growing concern for cybersecurity professionals, businesses and governments.
Referencing an article in this month’s Georgetown Law Technology Review, “…traditional AI algorithms normally operate by carrying out a specific function or completing a task using a data set that contains information on how that function or task has previously been done In other words, traditional AI is able to follow a set of rules, make predictions, or utilize instructions to complete a task; but it is not creating anything new in doing so. Generative AI (GAI) has the ability to create something new, specifically new content.” Marcus P. Zillman’s new resource guide spans subject matters including law, economics, education, information technology, planning and strategic deployment and use of GAI, as well a best practices and governance.
In 2021, a company specializing in collecting and selling location data called Near bragged that it was “The World’s Largest Dataset of People’s Behavior in the Real-World,” with data representing “1.6B people across 44 countries.” Last year the company went public with a valuation of $1 billion (via a SPAC). Seven months later it filed for bankruptcy and has agreed to sell the company. Jon Keegan highlights the ramifications to the public.
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: Google brings privacy washing to Android; Xfinity discloses data breach after recent Citrix server hack; How to Check If Something Online Was Written by AI; and Artificial intelligence can find your location, alarming privacy experts.