On the surface, ILTACON 2025, the International Legal Technology Association’s largest annual legal technology event, had all the makings of a great conference. But despite the thought-provoking sessions and keynotes, networking opportunities and PR fanfare, I couldn’t shake the sense that we were in the midst of a seismic shift in legal tech, surrounded by the restless energy of a boomtown.
… The gold rush
It wasn’t ILTACON that bothered me; it was the heady, gold-rushed, “anything goes and whatever sticks works” environment that was unsettling. While this year’s conference was pirate-themed, it felt more like the Wild West to me.
This attitude permeated the conference, driven largely by the frenzied, frontier-style artificial intelligence revolution. The AI train is hurtling forward at lightning speed, destination unknown, and everyone is trying to cash in before it derails.
Two themes emerged from my discussions. First, no matter who you spoke to, “agentic AI,” meaning AI that autonomously takes purposeful actions, was a buzzword that cropped up often, whether during press briefings or over drinks. Another key trend was the race to become the generative AI home base for legal professionals.
— Nicole Black
“We are at the start of the biggest disruption to the legal profession in its history.”
Is AI the technology that will finally force lawyer tech competence? With rapid advances and the ability to address numerous problems and pain points in our legal systems, AI simply can’t be ignored. Dennis & Tom welcome Bridget McCormack to discuss her perspectives on current AI trends and other exciting new tech applications in legal…
Another major AI lab just launched “education mode.”
Google introduced Guided Learningin Gemini, transforming it into a personalized learning companion designed to help you move from quick answers to real understanding.
Instead of immediately spitting out solutions, it:
Asks probing, open-ended questions
Walks learners through step-by-step reasoning
Adapts explanations to the learner’s level
Uses visuals, videos, diagrams, and quizzes to reinforce concepts
I’m not too naive to understand that, no matter how we present it, some students will always be tempted by “the dark side” of AI. What I also believe is that the future of AI in education is not decided. It will be decided by how we, as educators, embrace or demonize it in our classrooms.
My argument is that setting guidelines and talking to our students honestly about the pitfalls and amazing benefits that AI offers us as researchers and learners will define it for the coming generations.
Can AI be the next calculator? Something that, yes, changes the way we teach and learn, but not necessarily for the worse? If we want it to be, yes.
How it is used, and more importantly, how AI is perceived by our students, can be influenced by educators. We have to first learn how AI can be used as a force for good. If we continue to let the dominant voice be that AI is the Terminator of education and critical thinking, then that will be the fate we have made for ourselves.
AI Tools for Strategy and Research – GT #32 — from goodtools.substack.com by Robin Good Getting expert advice, how to do deep research with AI, prompt strategy, comparing different AIs side-by-side, creating mini-apps and an AI Agent that can critically analyze any social media channel
In this week’s blog post, I’ll share my take on how the instructional design role is evolving and discuss what this means for our day-to-day work and the key skills it requires.
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With this in mind, I’ve been keeping a close eye on open instructional design roles and, in the last 3 months, have noticed the emergence of a new flavour of instructional designer: the so-called “Generative AI Instructional Designer.”
Let’s deep dive into three explicitly AI-focused instructional design positions that have popped up in the last quarter. Each one illuminates a different aspect of how the role is changing—and together, they paint a picture of where our profession is likely heading.
Designers who evolve into prompt engineers, agent builders, and strategic AI advisors will capture the new premium. Those who cling to traditional tool-centric roles may find themselves increasingly sidelined—or automated out of relevance.
Google’s parent company announced Wednesday (8/6/25) that it’s planning to spend $1 billion over the next three years to help colleges teach and train students about artificial intelligence.
Google is joining other AI companies, including OpenAI and Anthropic, in investing in AI training in higher education. All three companies have rolled out new tools aimed at supporting “deeper learning” among students and made their AI platforms available to certain students for free.
Based on current technology capabilities, adoption patterns, and the mission of community colleges, here are five well-supported predictions for AI’s impact in the coming years.
15 Quick (and Mighty) Retrieval Practices — from edutopia.org by Daniel Leonard From concept maps to flash cards to Pictionary, these activities help students reflect on—and remember—what they’ve learned.
But to genuinely commit information to long-term memory, there’s no replacement for active retrieval—the effortful practice of recalling information from memory, unaided by external sources like notes or the textbook. “Studying this way is mentally difficult,” Willingham acknowledged, “but it’s really, really good for memory.”
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From low-stakes quizzes to review games to flash cards, there are a variety of effective retrieval practices that teachers can implement in class or recommend that students try at home. Drawing from a wide range of research, we compiled this list of 15 actionable retrieval practices.
When Zach Groshell zoomed in as a guest on a longstanding British education podcast last March, a co-host began the interview by telling listeners he was “very well-known over in the U.S.”
Groshell, a former Seattle-area fourth-grade teacher, had to laugh: “Nobody knows me here in the U.S.,” he said in an interview.
But in Britain, lots of teachers know his name. An in-demand speaker at education conferences, he flies to London “as frequently as I can” to discuss Just Tell Them, his 2024 book on explicit instruction. Over the past year, Groshell has appeared virtually about once a month and has made two personal appearances at events across England.
The reason? A discipline known as cognitive science. Born in the U.S., it relies on decades of research on how kids learn to guide teachers in the classroom, and is at the root of several effective reforms, including the Science of Reading.
ChatGPT can now do work for you using its own computer, handling complex tasks from start to finish.
You can now ask ChatGPT to handle requests like “look at my calendar and brief me on upcoming client meetings based on recent news,” “plan and buy ingredients to make Japanese breakfast for four,” and “analyze three competitors and create a slide deck.” ChatGPT will intelligently navigate websites, filter results, prompt you to log in securely when needed, run code, conduct analysis, and even deliver editable slideshows and spreadsheets that summarize its findings.
In a landmark deal that will undoubtedly reshape the legal tech landscape, law practice management company Clio has signed a definitive agreement to acquire the AI and legal research company vLex for $1 billion in cash and stock.
The companies say that the acquisition will “establish a new category of intelligent legal technology at the intersection of the business and practice of law, empowering legal professionals to seamlessly manage, research, and execute legal work within a unified system.”
Abstract In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities. This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.
As the class of 2025 enters the workforce, the Trump administration has dismantled career pathways for graduates interested in climate and sustainability work, international aid, public service and research across the natural, behavioral and social sciences. Federal jobs are disappearing, and the administration is eliminating grants and agency divisions that sustain university research programs and nonprofits that are crucial to launching careers.
The National Science Foundation, for example, halved graduate research fellowships, canceled some undergraduate research grants, stopped awarding new grants, froze funding for existing ones, and eliminated several hundred grants for focusing on diversity, equity and inclusion. In March, Robert F. Kennedy Jr. announced 10,000 layoffs at his agency, the Department of Health and Human Services; earlier buyouts and firings had already cut another 10,000 jobs.
74 percent of microschools have annual tuition and fees at or below $10,000, with 65 percent offering sliding scale tuition and discounts;
Among microschools that track academic growth data of students over time, 81 percent reported between 1 and 2 years of academic gains during one school year;
Children receive letter grades in just 29 percent of microschools, while observation-based reporting, portfolios, and tracking mastery are the most prevalent methods of tracking their impact;
The most important student outcomes for currently-operating microschools are growth in nonacademic learning, children’s happiness in their microschool, skills perceived as needed for future, and academic growth.
But the next step is what actually moves the needle. The rare, courageous thing to do is to develop an assertion.
What’s the difference between insights, suggestions, and assertions?
When you point out an insight, you’re calling attention to an observation, something you noticed and wanted to remark on. In response, your colleague could say, “Hmm interesting. That’s nice to know.” They carry on with their day. You carry on with yours. Nothing changes.
When you make a suggestion, you’re putting forth a recommendation. You’re proposing a few different options to choose from. But you’re still not on the hook because your boss ultimately decides what to do. And the person who decides holds the emotional burden of that decision.
When you make an assertion, all of a sudden, things get real. You’re on the hook because there’s more of you in what you’re positing. You’re now advocating for your point of view and trying to convince others to support you.
From DSC: Perhaps there’s something in here for academics when they write for the journals within their discipline. When I was getting my Masters Degree, I hated readying the same ol’ same ol’ –> “…this needs further research, blah, blah, blah.”
I wanted to know what the researcher/author had to actually say about the topic. Too often, they seemed to hold back any kind of thesis or what they believed to be true about a topic. They were far too reserved in my opinion.
So this edition is simple: a quick, practical guide to the major generative AI models available in 2025 so far. What they’re good at, what to use them for, and where they might fit into your legal work—from document summarization to client communication to research support.
From DSC: This comprehensive, highly informational posting lists what the model is, its strengths, the best legal use cases for it, and responsible use tips as well.
Of course AI will continue to make waves, but what other important legal technologies do you need to be aware of in 2025? Dennis and Tom give an overview of legal tech tools—both new and old—you should be using for successful, modernized legal workflows in your practice. They recommend solutions for task management, collaboration, calendars, projects, legal research, and more.
Later, the guys answer a listener’s question about online prompt libraries. Are there reputable, useful prompts available freely on the internet? They discuss their suggestions for prompt resources and share why these libraries tend to quickly become outdated.
If you follow legal tech at all, you would be justified in suspecting that Tom Martin has figured out how to use artificial intelligence to clone himself.
While running LawDroid, his legal tech company, the Vancouver-based Martin also still manages a law practice in California, oversees an annual legal tech awards program, teaches a law school course on generative AI, runs an annual AI conference, hosts a podcast, and recently launched a legal tech consultancy.
In January 2023, less than two months after ChatGPT first launched, Martin’s company was one of the first to launch a gen AI assistant specifically for lawyers, called LawDroid Copilot. He has since also launched LawDroid Builder, a no-code platform for creating custom AI agents.
In a profession that’s actively contemplating its future in the face of AI, legal organization leaders who demonstrate a genuine desire to invest in the next generation of legal professionals will undoubtedly set themselves apart
Artificial intelligence (AI) is here. And it’s already reshaping the way law firms operate. Whether automating repetitive tasks, improving risk management, or boosting efficiency, AI presents a genuine opportunity for forward-thinking legal practices. But with new opportunities come new responsibilities. And as firms explore AI tools, it’s essential they consider how to govern them safely and ethically. That’s where an AI policy becomes indispensable.
So, what can AI actually do for your firm right now? Let’s take a closer look.
DC: THIS could unfortunately be the ROI companies will get from large investments in #AI — reduced headcount/employees/contract workers. https://t.co/zEWlqCSWzI
Duolingo will “gradually stop using contractors to do work that AI can handle,” according to an all-hands email sent by cofounder and CEO Luis von Ahn announcing that the company will be “AI-first.” The email was posted on Duolingo’s LinkedIn account.
According to von Ahn, being “AI-first” means the company will “need to rethink much of how we work” and that “making minor tweaks to systems designed for humans won’t get us there.” As part of the shift, the company will roll out “a few constructive constraints,” including the changes to how it works with contractors, looking for AI use in hiring and in performance reviews, and that “headcount will only be given if a team cannot automate more of their work.”
Something strange, and potentially alarming, is happening to the job market for young, educated workers.
According to the New York Federal Reserve, labor conditions for recent college graduates have “deteriorated noticeably” in the past few months, and the unemployment rate now stands at an unusually high 5.8 percent. Even newly minted M.B.A.s from elite programs are struggling to find work. Meanwhile, law-school applications are surging—an ominous echo of when young people used graduate school to bunker down during the great financial crisis.
What’s going on? I see three plausible explanations, and each might be a little bit true.
The new workplace trend is not employee friendly. Artificial intelligence and automation technologies are advancing at blazing speed. A growing number of companies are using AI to streamline operations, cut costs, and boost productivity. Consequently, human workers are facing facing layoffs, replaced by AI. Like it or not, companies need to make tough decisions, including layoffs to remain competitive.
Corporations including Klarna, UPS, Duolingo, Intuit and Cisco are replacing laid-off workers with AI and automation. While these technologies enhance productivity, they raise serious concerns about future job security. For many workers, there is a big concern over whether or not their jobs will be impacted.
Key takeaway: Career navigation has remained largely unchanged for decades, relying on personal networks and static job boards. The advent of AI is changing this, offering personalised career pathways, better job matching, democratised job application support, democratised access to career advice/coaching, and tailored skill development to help you get to where you need to be.Hundreds of millions of people start new jobs every year, this transformation opens up a multi-billion dollar opportunity for innovation in the global career navigation market.
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A.4 How will AI disrupt this segment? Personalised recommendations: AI can consume a vast amount of information (skills, education, career history, even youtube history, and x/twitter feeds), standardise this data at scale, and then use data models to match candidate characteristics to relevant careers and jobs. In theory, solutions could then go layers deeper, helping you position yourself for those future roles. Currently based in Amsterdam, and working in Strategy at Uber and want to work in a Product role in the future? Here are X,Y,Z specific things YOU can do in your role today to align yourself perfectly. E.g. find opportunities to manage cross functional projects in your current remit, reach out to Joe Bloggs also at Uber in Amsterdam who did Strategy and moved to Product, etc.
No matter the school, no matter the location, when I deliver an AI workshop to a group of teachers, there are always at least a few colleagues thinking (and sometimes voicing), “Do I really need to use AI?”
Nearly three years after ChatGPT 3.5 landed in our lives and disrupted workflows in ways we’re still unpacking, most schools are swiftly catching up. Training sessions, like the ones I lead, are springing up everywhere, with principals and administrators trying to answer the same questions: Which tools should we use? How do we use them responsibly? How do we design learning in this new landscape?
But here’s what surprises me most: despite all the advances in AI technology, the questions and concerns from teachers remain strikingly consistent.
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In this article, I want to pull back the curtain on those conversations. These concerns aren’t signs of reluctance – they reflect sincere feelings. And they deserve thoughtful, honest answers.
This week, in advance of major announcements from us and other vendors, I give you a good overview of the AI Agent market, and discuss the new role of AI governance platforms, AI agent development tools, AI agent vendors, and how AI agents will actually manifest and redefine what we call an “application.”
I discuss ServiceNow, Microsoft, SAP, Workday, Paradox, Maki People, and other vendors. My goal today is to “demystify” this space and explain the market, the trends, and why and how your IT department is going to be building a lot of the agents you need. And prepare for our announcements next week!
DeepSeek has quietly launched Prover V2, an open-source model built to solve math problems using Lean 4 assistant, which ensures every step of a proof is rigorously verified.
What’s impressive about it?
Massive scale: Based on DeepSeek-V3 with 671B parameters using a mixture-of-experts (MoE) architecture, which activates only parts of the model at a time to reduce compute costs.
Theorem solving: Uses long context windows (32K+ tokens) to generate detailed, step-by-step formal proofs for a wide range of math problems — from basic algebra to advanced calculus theorems.
Research grade: Assists mathematicians in testing new theorems automatically and helps students understand formal logic by generating both Lean 4 code and readable explanations.
New benchmark: Introduces ProverBench, a new 325-question benchmark set featuring problems from recent AIME exams and curated academic sources to evaluate mathematical reasoning.
The need for deep student engagement became clear at Dartmouth Geisel School of Medicine when a potential academic-integrity issue revealed gaps in its initial approach to artificial intelligence use in the classroom, leading to significant revisions to ensure equitable learning and assessment.
From George Siemens “SAIL: Transmutation, Assessment, Robots e-newsletter on 5/2/25
All indications are that AI, even if it stops advancing, has the capacity to dramatically change knowledge work. Knowing things matters less than being able to navigate and make sense of complex environments. Put another way, sensemaking, meaningmaking, and wayfinding (with their yet to be defined subelements) will be the foundation for being knowledgeable going forward.
That will require being able to personalize learning to each individual learner so that who they are (not what our content is) forms the pedagogical entry point to learning.(DSC: And I would add WHAT THEY WANT to ACHIEVE.)LLMs are particularly good and transmutation. Want to explain AI to a farmer? A sentence or two in a system prompt achieves that. Know that a learner has ADHD? A few small prompt changes and it’s reflected in the way the LLM engages with learning. Talk like a pirate. Speak in the language of Shakespeare. Language changes. All a matter of a small meta comment send to the LLM. I’m convinced that this capability to change, transmute, information will become a central part of how LLMS and AI are adopted in education.
… Speaking of Duolingo– it took them 12 years to develop 100 courses. In the last year, they developed an additional 148. AI is an accelerant with an impact in education that is hard to overstate. “Instead of taking years to build a single course with humans the company now builds a base course and uses AI to quickly customize it for dozens of different languages.”
FutureHouse is launching our platform, bringing the first publicly available superintelligent scientific agents to scientists everywhere via a web interface and API. Try it out for free at https://platform.futurehouse.org.
AI agents arrive in US classrooms — from zdnet.com by Radhika Rajkumar Kira AI’s personalized learning platform is currently being implemented in Tennessee schools. How will it change education?
AI for education is a new but rapidly expanding field. Can it support student outcomes and help teachers avoid burnout?
On Wednesday, AI education company Kira launched a “fully AI-native learning platform” for K-12 education, complete with agents to assist teachers with repetitive tasks. The platform hosts assignments, analyzes progress data, offers administrative assistance, helps build lesson plans and quizzes, and more.
“Unlike traditional tools that merely layer AI onto existing platforms, Kira integrates artificial intelligence directly into every educational workflow — from lesson planning and instruction to grading, intervention, and reporting,” the release explains. “This enables schools to improve student outcomes, streamline operations, and provide personalized support at scale.”
“Teachers today are overloaded with repetitive tasks. A.I. agents can change that, and free up their time to give more personalized help to students,” Ng said in a statement.
Kira was co-founded by Andrea Pasinetti and Jagriti Agrawal, both longtime collaborators of Ng. The platform embeds A.I. directly into lesson planning, instruction, grading and reporting. Teachers can instantly generate standards-aligned lesson plans, monitor student progress in real time and receive automated intervention strategies when a student falls behind.
Students, in turn, receive on-demand tutoring tailored to their learning styles. A.I. agents adapt to each student’s pace and mastery level, while grading is automated with instant feedback—giving educators time to focus on teaching.
‘Using GenAI is easier than asking my supervisor for support’ — from timeshighereducation.com Doctoral researchers are turning to generative AI to assist in their research. How are they using it, and how can supervisors and candidates have frank discussions about using it responsibly?
Generative AI is increasingly the proverbial elephant in the supervisory room. As supervisors, you may be concerned about whether your doctoral researchers are using GenAI. It can be a tricky topic to broach, especially when you may not feel confident in understanding the technology yourself.
While the potential impact of GenAI use among undergraduate and postgraduate taught students, especially, is well discussed (and it is increasingly accepted that students and staff need to become “AI literate”), doctoral researchers often slip through the cracks in institutional guidance and policymaking.
When used thoughtfully and transparently, generative artificial intelligence can augment creativity and challenge assumptions, making it an excellent tool for exploring and developing ideas.
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The glaring contrast between the perceived ubiquity of GenAI and its actual use also reveals fundamental challenges associated with the practical application of these tools. This article explores two key questions about GenAI to address common misconceptions and encourage broader adoption and more effective use of these tools in higher education.
Like many of you, I spent the first part of this week at Learning Technologies in London, where I was lucky enough to present a session on the current state of AI and L&D.
In this week’s blog post, I summarise what I covered and share an audio summary of my paper for you to check out.
Bridging the AI Trust Gap— from chronicle.com by Ian Wilhelm, Derek Bruff, Gemma Garcia, and Lee Rainie
In a 2024 Chronicle survey, 86 percent of administrators agreed with the statement: “Generative artificial intelligence tools offer an opportunity for higher education to improve how it educates, operates, and conducts research.” In contrast, just 55 percent of faculty agreed, showing the stark divisions between faculty and administrative perspectives on adopting AI.
Among many faculty members, a prevalent distrust of AI persists — and for valid reasons. How will it impact in-class instruction? What does the popularity of generative AI tools portend for the development of critical thinking skills for Gen-Z students? How can institutions, at the administrative level, develop policies to safeguard against students using these technologies as tools for cheating?
Given this increasing ‘trust gap,’ how can faculty and administrators work together to preserve academic integrity as AI seeps into all areas of academia, from research to the classroom?
Join us for “Bridging the AI Trust Gap,” an extended, 75-minute Virtual Forum exploring the trust gap on campus about AI, the contours of the differences, and what should be done about it.
Teens, Social Media and Mental Health — from pewresearch.org by Michelle Faverio, Monica Anderson, and Eugenie Park Most teens credit social media with feeling more connected to friends. Still, roughly 1 in 5 say social media sites hurt their mental health, and growing shares think they harm people their age
Rising rates of poor mental health among youth have been called a national crisis. While this is often linked to factors like the COVID-19 pandemic or poverty, some officials, like former Surgeon General Vivek Murthy, name social media as a major threat to teenagers.
Our latest survey of U.S. teens ages 13 to 17 and their parents finds that parents are generally more worried than their children about the mental health of teenagers today.
And while both groups call out social media’s impact on young people’s well-being, parents are more likely to make this connection.1
Still, teens are growing more wary of social media for their peers. Roughly half of teens (48%) say these sites have a mostly negative effect on people their age, up from 32% in 2022. But fewer (14%) think they negatively affect them personally.