An interview by Ryan Tate with the New York Times reporter and long time privacy journalist Kashmir Hill on how investigating Clearview AI helped her appreciate facial recognition—and envision a chaotic future.
Whether speaking with lawyers and law students who haven’t gotten around to trying ChatGPT or collaborating with post-doc explainable and legal AI experts with 20+ years of machine learning and Natural Language Processing experience, Colin Lachance, legal tech innovator and leader, is no closer to understanding in what way and precisely when permanent change will come, but is unshakeably convinced that change will be enormous, uneven, disruptive and, in many cases, invisible.
Dr. Ravi Sen discusses how Google, Microsoft and others boast that generative artificial intelligence tools like ChatGPT will make searching the internet better than ever for users. For example, rather than having to wade through a sea of URLs, users will be able to just get an answer combed from the entire internet. There are also some concerns with the rise of AI-fueled search engines, such as the opacity over where information comes from, the potential for “hallucinated” answers and copyright issues. But one other consequence is that I believe it may destroy the US$68 billion search engine optimization industry that companies like Google helped create.
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. Six highlights from this week: LinkedIn Phishing Scam Exploits Smart Links to Steal Microsoft Accounts; Digital Dystopia – The Danger in Buying What the EdTech Surveillance Industry is Selling; Login.gov to add facial recognition tech; Temporary moratorium on use of facial recognition in NY; The Fake Browser Update Scam Gets a Makeover; and How to Spot and Avoid Zelle Scams in 2023.
Crime predictions generated for the police department in Plainfield, New Jersey, rarely lined up with reported crimes, an analysis by The Markup has found, adding new context to the debate over the efficacy of crime prediction software. Geolitica, known as PredPol until a 2021 rebrand, produces software that ingests data from crime incident reports and produces daily predictions on where and when crimes are most likely to occur. Aaron Sankin, Investigative Reporter and Surya Mattu, Senior Data Engineer and Investigative Data Journalist examined 23,631 predictions generated by Geolitica between Feb. 25 to Dec. 18, 2018 for the Plainfield Police Department (PD). Each prediction they analyzed from the company’s algorithm indicated that one type of crime was likely to occur in a location not patrolled by Plainfield PD. In the end, the success rate was less than half a percent. Fewer than 100 of the predictions lined up with a crime in the predicted category, that was also later reported to police.
Jocelyn Stilwell-Tong, Law Librarian, California Court of Appeal, Sixth Appellate District, has determined that although free AI online is useful, the developing products from major legal research platforms show great promise. These paid products control for issues like hallucinations, and provide citations supporting their work so a researcher can confirm the accuracy and context of the materials the AI is pulling from. Issues surrounding data governance (what the company does with your uploaded material and search history) can be controlled by contract, and the legal vendors understand that this is a concern for most legal clients.
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: Delete your digital history from dozens of companies with this app; Need a VPN? Here Are the Ones You Can Officially Trust; H&R Block, Meta, and Google Slapped With RICO Suit; and 3 Chatbot Privacy Risks and Concerns You Should Know About.
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.