“The conversation about AI bias is broadening,” said psychologist Tara Behrend, PhD, a professor at Michigan State University’s School of Human Resources and Labor Relations who studies human-technology interaction and spoke at CES about AI and privacy. “Agencies and various academic stakeholders are really taking the role of psychology seriously.”
The NY State Bar Association (NYSBA) Task Force on Artificial Intelligence has issued a nearly 80 page report (Report) and recommendations on the legal, social and ethical impact of artificial intelligence (AI) and generative AI on the legal profession. This detailed Report also reviews AI-based software, generative AI technology and other machine learning tools that may enhance the profession, but which also pose risks for individual attorneys’ understanding of new, unfamiliar technology, as well as courts’ concerns about the integrity of the judicial process. It also makes recommendations for NYSBA adoption, including proposed guidelines for responsible AI use. This Report is perhaps the most comprehensive report to date by a state bar association. It is likely this Report will stimulate much discussion.
For those of you who want the “Cliff Notes” version of this report, here is a table that summarizes by topic the various rules mentioned and a concise summary of the associated guidance.
Abigail is a lecturer on two of the Law micro-credentials at University of Galway – Lawyering Technology & Innovation and Law & Analytics. Micro-credentials are short, flexible courses designed to fit around your busy life! They are designed in collaboration with industry to meet specific skills needs and are accredited by leading Irish universities.
The potential for AI’s impact is broad, as it has the ability to impact every aspect of human life, from home to work. It will impact our relationships to everything and everyone in our world. The implications for generative AI on the legal system, from how we deliver legal services to how we deliver justice, will be just as far reaching.
[N]ow we face the latest technological frontier: artificial intelligence (AI).… Law professors report with both awe and angst that AI apparently can earn Bs on law school assignments and even pass the bar exam. Legal research may soon be unimaginable without it. AI obviously has great potential to dramatically increase access to key information for lawyers and non-lawyers alike. But just as obviously it risks invading privacy interests and dehumanizing the law.
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When you can no longer sell the time it takes to achieve a client’s outcome, then you must sell the outcome itself and the client’s experience of getting there. That completely changes the dynamics of what law firms are all about.
Georgia State University College of Law faculty understand this need and designed the Legal Analytics & Innovation Initiative (LAII) to equip students with the competitive skills desired by law firms and other companies that align with the emerging technological environment.
“As faculty, we realized we need to be forward-thinking about incorporating technology into our curriculum. Students must understand new areas of law that arise from or are significantly altered by technological advances, like cybersecurity, privacy and AI. They also must understand how these advances change the practice of law,” said Kris Niedringhaus, associate dean for Law Library, Information Services, Legal Technology & Innovation.
As the legal profession continues to navigate the waters of digital transformation, the importance of use cases stands as a beacon guiding the journey. They are the litmus test for the practical value of technology, ensuring that innovations not only dazzle with potential but also deliver tangible benefits. In the quest to integrate AI and legal technology into legal practice, use cases are not just important but indispensable.
The future of legal tech is not about technology for technology’s sake. It’s about thoughtful, purpose-driven innovation that enhances the practice of law, improves client outcomes, and upholds the principles of justice. Use cases are the roadmap for this future, charting a course for technology that is meaningful, impactful, and aligned with the noble pursuit of law.
These librarians, entrepreneurs, lawyers and technologists built the world where artificial intelligence threatens to upend life and law as we know it – and are now at the forefront of the battles raging within.
… To create this first-of-its-kind guide, we cast a wide net with dozens of leaders in this area, took submissions, consulted with some of the most esteemed gurus in legal tech. We also researched the cases most likely to have the biggest impact on AI, unearthing the dozen or so top trial lawyers tapped to lead the battles. Many of them bring copyright or IP backgrounds and more than a few are Bay Area based. Those denoted with an asterisk are members of our Hall of Fame. .
descrybe.ai, a year-old legal research startup focused on using artificial intelligence to provide free and easy access to court opinions, has completed its goal of creating AI-generated summaries of all available state supreme and appellate court opinions from throughout the United States.
descrybe.ai describes its mission as democratizing access to legal information and leveling the playing field in legal research, particularly for smaller-firm lawyers, journalists, and members of the public.
As the FlexOS research study “Generative AI at Work” concluded based on a survey amongst knowledge workers, ChatGPT reigns supreme. … 2. AI Tool Usage is Way Higher Than People Expect – Beating Netflix, Pinterest, Twitch. As measured by data analysis platform Similarweb based on global web traffic tracking, the AI tools in this list generate over 3 billion monthly visits.
With 1.67 billion visits, ChatGPT represents over half of this traffic and is already bigger than Netflix, Microsoft, Pinterest, Twitch, and The New York Times.
Something unusual is happening in America. Demand for electricity, which has stayed largely flat for two decades, has begun to surge.
Over the past year, electric utilities have nearly doubled their forecasts of how much additional power they’ll need by 2028 as they confront an unexpected explosion in the number of data centers, an abrupt resurgence in manufacturing driven by new federal laws, and millions of electric vehicles being plugged in.
The tumult could seem like a distraction from the startup’s seemingly unending march toward AI advancement. But the tension, and the latest debate with Musk, illuminates a central question for OpenAI, along with the tech world at large as it’s increasingly consumed by artificial intelligence: Just how open should an AI company be?
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The meaning of the word “open” in “OpenAI” seems to be a particular sticking point for both sides — something that you might think sounds, on the surface, pretty clear. But actual definitions are both complex and controversial.
In partnership with the National Cancer Institute, or NCI, researchers from the Department of Energy’s Oak Ridge National Laboratory and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.
The early vibrations of AI have already been shaking the newsroom. One downside of the new technology surfaced at CNET and Sports Illustrated, where editors let AI run amok with disastrous results. Elsewhere in news media, AI is already writing headlines, managing paywalls to increase subscriptions, performing transcriptions, turning stories in audio feeds, discovering emerging stories, fact checking, copy editing and more.
Felix M. Simon, a doctoral candidate at Oxford, recently published a white paper about AI’s journalistic future that eclipses many early studies. Swinging a bat from a crouch that is neither doomer nor Utopian, Simon heralds both the downsides and promise of AI’s introduction into the newsroom and the publisher’s suite.
Unlike earlier technological revolutions, AI is poised to change the business at every level. It will become — if it already isn’t — the beginning of most story assignments and will become, for some, the new assignment editor. Used effectively, it promises to make news more accurate and timely. Used frivolously, it will spawn an ocean of spam. Wherever the production and distribution of news can be automated or made “smarter,” AI will surely step up. But the future has not yet been written, Simon counsels. AI in the newsroom will be only as bad or good as its developers and users make it.
We proposed EMO, an expressive audio-driven portrait-video generation framework. Input a single reference image and the vocal audio, e.g. talking and singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses, meanwhile, we can generate videos with any duration depending on the length of input video.
New experimental work from Adobe Research is set to change how people create and edit custom audio and music. An early-stage generative AI music generation and editing tool, Project Music GenAI Control allows creators to generate music from text prompts, and then have fine-grained control to edit that audio for their precise needs.
“With Project Music GenAI Control, generative AI becomes your co-creator. It helps people craft music for their projects, whether they’re broadcasters, or podcasters, or anyone else who needs audio that’s just the right mood, tone, and length,” says Nicholas Bryan, Senior Research Scientist at Adobe Research and one of the creators of the technologies.
There’s a lot going on in the world of generative AI, but maybe the biggest is the increasing number of copyright lawsuits being filed against AI companies like OpenAI and Stability AI. So for this episode, we brought on Verge features editor Sarah Jeong, who’s a former lawyer just like me, and we’re going to talk about those cases and the main defense the AI companies are relying on in those copyright cases: an idea called fair use.
The FCC’s war on robocalls has gained a new weapon in its arsenal with the declaration of AI-generated voices as “artificial” and therefore definitely against the law when used in automated calling scams. It may not stop the flood of fake Joe Bidens that will almost certainly trouble our phones this election season, but it won’t hurt, either.
The new rule, contemplated for months and telegraphed last week, isn’t actually a new rule — the FCC can’t just invent them with no due process. Robocalls are just a new term for something largely already prohibited under the Telephone Consumer Protection Act: artificial and pre-recorded messages being sent out willy-nilly to every number in the phone book (something that still existed when they drafted the law).
EIEIO…Chips Ahoy!— from dashmedia.co by Michael Moe, Brent Peus, and Owen Ritz
Here Come the AI Worms — from wired.com by Matt Burgess Security researchers created an AI worm in a test environment that can automatically spread between generative AI agents—potentially stealing data and sending spam emails along the way.
Now, in a demonstration of the risks of connected, autonomous AI ecosystems, a group of researchers have created one of what they claim are the first generative AI worms—which can spread from one system to another, potentially stealing data or deploying malware in the process. “It basically means that now you have the ability to conduct or to perform a new kind of cyberattack that hasn’t been seen before,” says Ben Nassi, a Cornell Tech researcher behind the research.
Last month, I discussed a GPT that I had created around enhancing prompts. Since then, I have been actively using my Prompt Enhancer GPT to much more effective outputs. Last week, I did a series of mini-talks on generative AI in different parts of higher education (faculty development, human resources, grants, executive leadership, etc) and structured it as “5 tips”. I included a final bonus tip in all of them—a tip that I heard from many afterwards was probably the most useful tip—especially because you can only access the Prompt Enhancer GPT if you are paying for ChatGPT.
Effectively integrating generative AI into higher education requires policy development, cross-functional engagement, ethical principles, risk assessments, collaboration with other institutions, and an exploration of diverse use cases.
Creating Guidelines for the Use of Gen AI Across Campus— from campustechnology.com by Rhea Kelly The University of Kentucky has taken a transdisciplinary approach to developing guidelines and recommendations around generative AI, incorporating input from stakeholders across all areas of the institution. Here, the director of UK’s Center for the Enhancement of Learning and Teaching breaks down the structure and thinking behind that process.
That resulted in a set of instructional guidelines that we released in August of 2023 and updated in December of 2023. We’re also looking at guidelines for researchers at UK, and we’re currently in the process of working with our colleagues in the healthcare enterprise, UK Healthcare, to comb through the additional complexities of this technology in clinical care and to offer guidance and recommendations around those issues.
My experiences match with the results of the above studies. The second study cited above found that 83% of those students who haven’t used AI tools are “not interested in using them,” so it is no surprise that many students have little awareness of their nature. The third study cited above found that, “apart from 12% of students identifying as daily users,” most students’ use cases were “relatively unsophisticated” like summarizing or paraphrasing text.
For those of us in the AI-curious bubble, we need to continually work to stay current, but we also need to recognize that what we take to be “common knowledge” is far from common outside of the bubble.
Despite general familiarity, however, technical knowledge shouldn’t be assumed for district leaders or others in the school community. For instance, it’s critical that any materials related to AI not be written in “techy talk” so they can be clearly understood, said Ann McMullan, project director for the Consortium for School Networking’s EmpowerED Superintendents Initiative.
To that end, CoSN, a nonprofit that promotes technological innovation in K-12, has released an array of AI resources to help superintendents stay ahead of the curve, including a one-page explainer that details definitions and guidelines to keep in mind as schools work with the emerging technology.
As college costs soar and demand for skilled labor rises, programs that prepare students for well-paid work are gaining popularity. About 85 percent of high school graduates in 2019 had taken at least one course in career and technical education, or CTE. In 2018, Congress increased annual funding for CTE, which now exceeds $1.4 billion. And in 2022, 36 states enacted policies promoting career training for high schoolers, college students, and adults, according to Advance CTE, a professional organization for state CTE leaders.
Yet many states struggle to answer a basic question: Is career education working?
Why are we doing this work? Over the past two years, the U.S. Department of Education has been committed to maintaining an ongoing conversation with educators, students, researchers, developers — and the educational community at large — related to the continuous progress of Artificial Intelligence (AI) development and its implications for teaching and learning.
Many educators are seeking resources clarifying what AI is and how it will impact their work and their students. Similarly, developers of educational technology (“edtech”) products seek guidance on what guardrails exist that can support their efforts. After the release of our May 2023 report Artificial Intelligence and the Future of Teaching and Learning, we heard the desire for more.
Moving from reaction to action, higher education stakeholders are currently exploring the opportunities afforded by AI for teaching, learning, and work while maintaining a sense of caution for the vast array of risks AI-powered technologies pose. To aid in these efforts, we present this inaugural EDUCAUSE AI Landscape Study, in which we summarize the higher education community’s current sentiments and experiences related to strategic planning and readiness, policies and procedures, workforce, and the future of AI in higher education.
Educational administrators should not worry about every AI development, but should, instead focus on the big picture, as those big picture changes will change the entire world and the educational system.
AI and related technologies (robotics, synthetic biology, and brain-computer interfaces) will continue to impact society and the entire educational system over the next 10 years. This impact on the system will be greater than anything that has happened over the last 100 years, including COVID-19, as COVID-19 eventually ended and the disruptive force of these technologies will only continue to develop.
AI is the bull in the China Shop, redefining the world and the educational system. Students writing a paper with AI is barely a poke in the educational world relative to what is starting to happen (active AI teachers and tutors; AI assessment; AI glasses; immersive learning environments; young students able to start their own business with AI tools; AIs replacing and changing jobs; deep voice and video fakes; intelligence leveling; individualized instruction; interactive and highly intelligent computers; computers that can act autonomously; and more).
verb
(of artificial intelligence) to produce false information contrary to the intent of the user and present it as if true and factual. Example: When chatbots hallucinate, the result is often not just inaccurate but completely fabricated.
Soon, every employee will be both AI builder and AI consumer— from zdnet.com by Joe McKendrick, via Robert Gibson on LinkedIn “Standardized tools and platforms as well as advanced low- or no-code tech may enable all employees to become low-level engineers,” suggests a recent report.
The time could be ripe for a blurring of the lines between developers and end-users, a recent report out of Deloitte suggests. It makes more business sense to focus on bringing in citizen developers for ground-level programming, versus seeking superstar software engineers, the report’s authors argue, or — as they put it — “instead of transforming from a 1x to a 10x engineer, employees outside the tech division could be going from zero to one.”
Along these lines, see:
TECH TRENDS 2024 — from deloitte.com Six emerging technology trends demonstrate that in an age of generative machines, it’s more important than ever for organizations to maintain an integrated business strategy, a solid technology foundation, and a creative workforce.
The ruling follows a similar decision denying patent registrations naming AI as creators.
The UK Supreme Court ruled that AI cannot get patents, declaring it cannot be named as an inventor of new products because the law considers only humans or companies to be creators.
The New York Times sued OpenAI and Microsoft for copyright infringement on Wednesday, opening a new front in the increasingly intense legal battle over the unauthorized use of published work to train artificial intelligence technologies.
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The suit does not include an exact monetary demand. But it says the defendants should be held responsible for “billions of dollars in statutory and actual damages” related to the “unlawful copying and use of The Times’s uniquely valuable works.” It also calls for the companies to destroy any chatbot models and training data that use copyrighted material from The Times.
On this same topic, also see:
? The historic NYT v. @OpenAI lawsuit filed this morning, as broken down by me, an IP and AI lawyer, general counsel, and longtime tech person and enthusiast.
Tl;dr – It’s the best case yet alleging that generative AI is copyright infringement. Thread. ? pic.twitter.com/Zqbv3ekLWt
ChatGPT and Other Chatbots
The arrival of ChatGPT sparked tons of new AI tools and changed the way we thought about using a chatbot in our daily lives.
Chatbots like ChatGPT, Perplexity, Claude, and Bing Chat can help content creators by quickly generating ideas, outlines, drafts, and full pieces of content, allowing creators to produce more high-quality content in less time.
These AI tools boost efficiency and creativity in content production across formats like blog posts, social captions, newsletters, and more.
Microsoft is getting ready to upgrade its Surface lineup with new AI-enabled features, according to a report from Windows Central. Unnamed sources told the outlet the upcoming Surface Pro 10 and Surface Laptop 6 will come with a next-gen neural processing unit (NPU), along with Intel and Arm-based options.
With the AI-assisted reporter churning out bread and butter content, other reporters in the newsroom are freed up to go to court, meet a councillor for a coffee or attend a village fete, says the Worcester News editor, Stephanie Preece.
“AI can’t be at the scene of a crash, in court, in a council meeting, it can’t visit a grieving family or look somebody in the eye and tell that they’re lying. All it does is free up the reporters to do more of that,” she says. “Instead of shying away from it, or being scared of it, we are saying AI is here to stay – so how can we harness it?”
This year, I watched AI change the world in real time.
From what happened, I have no doubts that the coming years will be the most transformative period in the history of humankind.
Here’s the full timeline of AI in 2023 (January-December):
What to Expect in AI in 2024 — from hai.stanford.edu by Seven Stanford HAI faculty and fellows predict the biggest stories for next year in artificial intelligence.
Forty years ago, the release of A Nation at Risk led to what we know today as the modern school reform movement. With its calls for increased academic rigor, more productive use of instructional time, more effective teaching, and more impactful leadership, A Nation at Risk set in motion policy and practice changes at every level of the education system. But after four decades, what has been the result? And where do we go from here?
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Forty years on, significant challenges remain. The COVID-19 pandemic has had devastating effects on student learning, and chronic absenteeism remains at alarming rates. Even prior to the pandemic, student achievement, as measured by standardized tests, seemed to have plateaued despite ever-increasing resources—in time, dollars, research, technology, and human capital—being devoted to school reform.
Much has been tried in the effort to improve our schools. Has any of it made a difference?
From DSC: Hhhhhmmmmm……not sure yet that this is a good idea. But I doubt there’s any stopping it.
We have formed a new global partnership with @AxelSpringer and its news products.
Real-time information from @politico, @BusinessInsider, European properties @BILD and @welt, and other publications will soon be available to ChatGPT users.
Recent advances in artificial intelligence (AI) have created a step change in how to measure poverty and other human development indicators. Our team has used a type of AI known as a deep convolutional neural network (DCNN) to study satellite imagery and identify some types of poverty with a level of accuracy close to that of household surveys.
E.U. reaches deal on landmark AI bill, racing ahead of U.S. — from washingtonpost.com by Anthony Faiola, Cat Zakrzewski and Beatriz Ríos (behind paywall) The regulation paves the way for what could become a global standard to classify risk, enforce transparency and financially penalize tech companies for noncompliance.
European Union officials reached a landmark deal Friday on the world’s most ambitious law to regulate artificial intelligence, paving the way for what could become a global standard to classify risk, enforce transparency and financially penalize tech companies for noncompliance.
Technology is all about solving big thorny problems. Yet one of the hardest things about solving hard problems is knowing where to focus our efforts. There are so many urgent issues facing the world. Where should we even begin? So we asked dozens of people to identify what problem at the intersection of technology and society that they think we should focus more of our energy on. We queried scientists, journalists, politicians, entrepreneurs, activists, and CEOs.
Some broad themes emerged: the climate crisis, global health, creating a just and equitable society, and AI all came up frequently. There were plenty of outliers, too, ranging from regulating social media to fighting corruption.
New York City Public Schools will launch an Artificial Intelligence Policy Lab to guide the nation’s largest school district’s approach to this rapidly evolving technology.
Kevin McCullen, an associate professor of computer science at the State University of New York at Plattsburgh, teaches a freshman seminar about AI and robotics. As part of the course, students read Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, by John Markoff. McCullen had the students work in groups to outline and summarize the first three chapters. Then he showed them what ChatGPT had produced in an outline.
“Their version and ChatGPT’s version seemed to be from two different books,” McCullen wrote. “ChatGPT’s version was essentially a ‘laundry list’ of events. Their version was narratives of what they found interesting. The students had focused on what the story was telling them, while ChatGPT focused on who did what in what year.” The chatbot also introduced false information, such as wrong chapter names.
The students, he wrote, found the writing “soulless.”
In the Wild West of generative AI, educators and institutions are working out how best to use the technology for learning. How can institutions define AI guidelines that allow for experimentation while providing students with consistent guidance on appropriate use of AI tools?
To find out, we spoke with Dr. Cristi Ford, vice president of academic affairs at D2L. With more than two decades of educational experience in nonprofit, higher education, and K-12 institutions, Ford works with D2L’s institutional partners to elevate best practices in teaching, learning, and student support. Here, she shares her advice on setting and communicating AI policies that are consistent and future-ready.
“If we want to use AI to improve education, we need more teachers at the table,” said Avery Pan, Class Companion co-founder and CEO. “Class Companion is designed by teachers, for teachers, to harness the most sophisticated AI and improve their classroom experience. Developing technologies specifically for teachers is imperative to supporting our next generation of students and education system.”
7 Questions on Generative AI in Learning Design — from campustechnology.com by Rhea Kelly Open LMS Adoption and Education Specialist Michael Vaughn on the challenges and possibilities of using artificial intelligence to move teaching and learning forward.
The potential for artificial intelligence tools to speed up course design could be an attractive prospect for overworked faculty and spread-thin instructional designers. Generative AI can shine, for example, in tasks such as reworking assessment question sets, writing course outlines and learning objectives, and generating subtitles for audio and video clips. The key, says Michael Vaughn, adoption and education specialist at learning platform Open LMS, is treating AI like an intern who can be guided and molded along the way, and whose work is then vetted by a human expert.
We spoke with Vaughn about how best to utilize generative AI in learning design, ethical issues to consider, and how to formulate an institution-wide policy that can guide AI use today and in the future.
I’ve written and spoken about this before but the rise of deepfakes is going to have a profound impact on courts throughout the world. This week we saw three major deepfake stories.
Whether you are a lawyer or not, this topic will impact you.So, please consider these questions as we will need to have answers for each one very soon (if not now).
How will we establish a reliable and consistent standard to authenticate digital evidence as genuine and not altered by deepfake technology?
Will the introduction of deepfakes shift the traditional burdens of proof or production, especially when digital evidence is introduced?
Will courts require expert witnesses for digital evidence authentication in every case, and what standards will be used to qualify these experts?
Are there existing technological tools or methods to detect deepfakes? (yes there is but it is not 100%) How can courts keep abreast of rapidly advancing technology?
…plus several more questions
From DSC: What are law schools doing about this? Are they addressing this?
And speaking of legal matters and law schools, this might be interesting or helpful to someone out there:
Take ownership of the file.
When you enter #biglaw, you’ll hear this constantly.
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