“Student Guide to AI”; “AI Isn’t Just Changing How We Work — It’s Changing How We Learn”; + other items re: AI in our LE’s

.Get the 2025 Student Guide to Artificial Intelligence — from studentguidetoai.org
This guide is made available under a Creative Commons license by Elon University and the American Association of Colleges and Universities (AAC&U).
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AI Isn’t Just Changing How We Work — It’s Changing How We Learn — from entrepreneur.com by Aytekin Tank; edited by Kara McIntyre
AI agents are opening doors to education that just a few years ago would have been unthinkable. Here’s how.

Agentic AI is taking these already huge strides even further. Rather than simply asking a question and receiving an answer, an AI agent can assess your current level of understanding and tailor a reply to help you learn. They can also help you come up with a timetable and personalized lesson plan to make you feel as though you have a one-on-one instructor walking you through the process. If your goal is to learn to speak a new language, for example, an agent might map out a plan starting with basic vocabulary and pronunciation exercises, then progress to simple conversations, grammar rules and finally, real-world listening and speaking practice.

For instance, if you’re an entrepreneur looking to sharpen your leadership skills, an AI agent might suggest a mix of foundational books, insightful TED Talks and case studies on high-performing executives. If you’re aiming to master data analysis, it might point you toward hands-on coding exercises, interactive tutorials and real-world datasets to practice with.

The beauty of AI-driven learning is that it’s adaptive. As you gain proficiency, your AI coach can shift its recommendations, challenge you with new concepts and even simulate real-world scenarios to deepen your understanding.

Ironically, the very technology feared by workers can also be leveraged to help them. Rather than requiring expensive external training programs or lengthy in-person workshops, AI agents can deliver personalized, on-demand learning paths tailored to each employee’s role, skill level, and career aspirations. Given that 68% of employees find today’s workplace training to be overly “one-size-fits-all,” an AI-driven approach will not only cut costs and save time but will be more effective.


What’s the Future for AI-Free Spaces? — from higherai.substack.com by Jason Gulya
Please let me dream…

This is one reason why I don’t see AI-embedded classrooms and AI-free classrooms as opposite poles. The bone of contention, here, is not whether we can cultivate AI-free moments in the classroom, but for how long those moments are actually sustainable.

Can we sustain those AI-free moments for an hour? A class session? Longer?

Here’s what I think will happen. As AI becomes embedded in society at large, the sustainability of imposed AI-free learning spaces will get tested. Hard. I think it’ll become more and more difficult (though maybe not impossible) to impose AI-free learning spaces on students.

However, consensual and hybrid AI-free learning spaces will continue to have a lot of value. I can imagine classes where students opt into an AI-free space. Or they’ll even create and maintain those spaces.


Duolingo’s AI Revolution — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 148 AI-Generated Courses Tell Us About the Future of Instructional Design & Human Learning

Last week, Duolingo announced an unprecedented expansion: 148 new language courses created using generative AI, effectively doubling their content library in just one year. This represents a seismic shift in how learning content is created — a process that previously took the company 12 years for their first 100 courses.

As CEO Luis von Ahn stated in the announcement, “This is a great example of how generative AI can directly benefit our learners… allowing us to scale at unprecedented speed and quality.”

In this week’s blog, I’ll dissect exactly how Duolingo has reimagined instructional design through AI, what this means for the learner experience, and most importantly, what it tells us about the future of our profession.


Are Mixed Reality AI Agents the Future of Medical Education? — from ehealth.eletsonline.com

Medical education is experiencing a quiet revolution—one that’s not taking place in lecture theatres or textbooks, but with headsets and holograms. At the heart of this revolution are Mixed Reality (MR) AI Agents, a new generation of devices that combine the immersive depth of mixed reality with the flexibility of artificial intelligence. These technologies are not mere flashy gadgets; they’re revolutionising the way medical students interact with complicated content, rehearse clinical skills, and prepare for real-world situations. By combining digital simulations with the physical world, MR AI Agents are redefining what it means to learn medicine in the 21st century.




4 Reasons To Use Claude AI to Teach — from techlearning.com by Erik Ofgang
Features that make Claude AI appealing to educators include a focus on privacy and conversational style.

After experimenting using Claude AI on various teaching exercises, from generating quizzes to tutoring and offering writing suggestions, I found that it’s not perfect, but I think it behaves favorably compared to other AI tools in general, with an easy-to-use interface and some unique features that make it particularly suited for use in education.

 

2025 EDUCAUSE Horizon Report | Teaching and Learning Edition — from library.educause.edu

Higher education is in a period of massive transformation and uncertainty. Not only are current events impacting how institutions operate, but technological advancement—particularly in AI and virtual reality—are reshaping how students engage with content, how cognition is understood, and how learning itself is documented and valued.

Our newly released 2025 EDUCAUSE Horizon Report | Teaching and Learning Edition captures the spirit of this transformation and how you can respond with confidence through the lens of emerging trends, key technologies and practices, and scenario-based foresight.

#teachingandlearning #highereducation #learningecosystems #learning #futurism #foresight #trends #emergingtechnologies #AI #VR #gamechangingenvironment #colleges #universities #communitycolleges #faculty #staff #IT

 

In many traditional school buildings, the design sends an unspoken message: “Sit down. Follow instructions. Stay within the lines.”

But imagine what students might believe about themselves and the world if their learning environment said instead:

“You belong here. Your ideas matter. Explore freely.”


For another item related to learning spaces, see:

Choosing the Right Technology for Today’s HyFlex Classroom — from edtechmagazine.com by Gaurav Bradoo
Long-lasting adoption of the HyFlex learning modality means higher education institutions shouldn’t be afraid to invest in tools that can enhance the student experience.

The answer? Solutions built for quick and easy installation, designed to work across multiple platforms and equipped with remote update and troubleshooting features. Anything we can do to reduce the number of cords, components and required steps during installation will assist AV staff. Prioritizing user-friendly design will cut down on help tickets across the lifespan of a device, and choosing features such as remote update capability can streamline maintenance. The bottom line is that simplicity and ease of deployment are not nice-to-haves. They are essential.

I’ve visited universities where instructors are faced with control panels with laminated cheat sheets next to them. These panels are often overloaded, acting as the room system as well, and not designed with simplicity or teaching flow in mind as it relates to capturing and streaming content for HyFlex teaching.


Along the lines of learning and working/office spaces…I’d like to thank Daan van Rossum for this next article (below emphasis from DSC). Daan mentioned that:

  • Phil Kirschner (ex-McKinsey, WeWork, JLL, Forbes contributor) just published a sharp piece on The Workline entitled Vibe Officing: The Antidote to Office Mandates.
  • In it, Phil introduces “Vibe Officing”—challenges the mandate-vs-flexibility debate with a third way: designing office spaces people want to return to, not because they’re told to, but because they actually enjoy being there. He also touches on how AI can enable personalized nudges to improve workplace journeys.


 

DC: I’m not necessarily recommending this, but the next two items point out how the use of agents continues to move forward:

The Future is Here: Visa Announces New Era of Commerce Featuring AI

  • Global leader brings its trusted brand and powerful network to enable payments with new technologies
  • Launches new innovations and partnerships to drive flexibility, security and acceptance

SAN FRANCISCO–(BUSINESS WIRE)–The future of commerce is on display at the Visa Global Product Drop with powerful AI-enabled advancements allowing consumers to find and buy with AI plus the introduction of new strategic partnerships and product innovations.

Also related/see:

Find and Buy with AI: Visa Unveils New Era of Commerce — from businesswire.com

  • Collaborates with Anthropic, IBM, Microsoft, Mistral AI, OpenAI, Perplexity, Samsung, Stripe and more
  • Will make shopping experiences more personal, more secure and more convenient as they become powered by AI

Introduced [on April 30th] at the Visa Global Product Drop, Visa Intelligent Commerce enables AI to find and buy. It is a groundbreaking new initiative that opens Visa’s payment network to the developers and engineers building the foundational AI agents transforming commerce.


AI agents are the new buyers. How can you market to them? — from aiwithallie.beehiiv.com by Allie Miller
You’re optimizing for people. But the next buyers are bots.

In today’s newsletter, I’m unpacking why your next major buyers won’t be people at all. They’ll be AI agents, and your brand might already be invisible to them. We’ll dig into why traditional marketing strategies are breaking down in the age of autonomous AI shoppers, what “AI optimization” (AIO) really means, and the practical steps you can take right now to make sure your business stays visible and competitive as the new digital gatekeepers take over more digital tasks.

AI platforms and AI agents—the digital assistants that browse and actually do things powered by models like GPT-4o, Claude 3.7 Sonnet, and Gemini 2.5 Pro—are increasingly becoming the gatekeepers between your business and potential customers.

“AI is the new front door to your business for millions of consumers.”

The 40-Point (ish) AI Agent Marketing Playbook 
Here’s the longer list. I went ahead and broke these into four categories so you can more easily assign owners: Content, Structure & Design, Technical & Dev, and AI Strategy & Testing. I look forward to seeing how this space, and by extension my advice, changes in the coming months.


Microsoft CEO says up to 30% of the company’s code was written by AI — from techcrunch.com by Maxwell Zeff

During a fireside chat with Meta CEO Mark Zuckerberg at Meta’s LlamaCon conference on Tuesday, Microsoft CEO Satya Nadella said that 20% to 30% of code inside the company’s repositories was “written by software” — meaning AI.


The Top 100Gen AI Consumer Apps — from a16z.com

In just six months, the consumer AI landscape has been redrawn. Some products surged, others stalled, and a few unexpected players rewrote the leaderboard overnight. Deepseek rocketed from obscurity to a leading ChatGPT challenger. AI video models advanced from experimental to fairly dependable (at least for short clips!). And so-called “vibe coding” is changing who can create with AI, not just who can use it. The competition is tighter, the stakes are higher, and the winners aren’t just launching, they’re sticking.

We turned to the data to answer: Which AI apps are people actively using? What’s actually making money, beyond being popular? And which tools are moving beyond curiosity-driven dabbling to become daily staples?

This is the fourth installment of the Top 100 Gen AI Consumer Apps, our bi-annual ranking of the top 50 AI-first web products (by unique monthly visits, per Similarweb) and top 50 AI-first mobile apps (by monthly active users, per Sensor Tower). Since our last report in August 2024, 17 new companies have entered the rankings of top AI-first web products.


Deep Research with AI: 9 Ways to Get Started — from wondertools.substack.com by Jeremy Caplan
Practical strategies for thorough, citation-rich AI research

The AI search landscape is transforming at breakneck speed. New “Deep Research” tools from ChatGPT, Gemini and Perplexity autonomously search and gather information from dozens — even hundreds — of sites, then analyze and synthesize it to produce comprehensive reports. While a human might take days or weeks to produce these 30-page citation-backed reports, AI Deep Research reports are ready in minutes.

What’s in this post

    • Examples of each report type I generated for my research, so you can form your own impressions.
    • Tips on why & how to use Deep Research and how to craft effective queries.
    • Comparison of key features and strengths/limitations of the top platforms

AI Agents Are Here—So Are the Threats: Unit 42 Unveils the Top 10 AI Agent Security Risks — from marktechpost.com

As AI agents transition from experimental systems to production-scale applications, their growing autonomy introduces novel security challenges. In a comprehensive new report, AI Agents Are Here. So Are the Threats,” Palo Alto Networks’ Unit 42 reveals how today’s agentic architectures—despite their innovation—are vulnerable to a wide range of attacks, most of which stem not from the frameworks themselves, but from the way agents are designed, deployed, and connected to external tools.

To evaluate the breadth of these risks, Unit 42 researchers constructed two functionally identical AI agents—one built using CrewAI and the other with AutoGen. Despite architectural differences, both systems exhibited the same vulnerabilities, confirming that the underlying issues are not framework-specific. Instead, the threats arise from misconfigurations, insecure prompt design, and insufficiently hardened tool integrations—issues that transcend implementation choices.


LLMs Can Learn Complex Math from Just One Example: Researchers from University of Washington, Microsoft, and USC Unlock the Power of 1-Shot Reinforcement Learning with Verifiable Reward — from marktechpost.com by Sana Hassan


 

 

..which links to:

Duolingo will replace contract workers with AI — from theverge.com by Jay Peters
The company is going to be ‘AI-first,’ says its CEO.

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.”


Relevant links:

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.


It’s Time To Get Concerned As More Companies Replace Workers With AI — from forbes.com by Jack Kelly

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.


The future of career navigation — from medium.com by Sami Tatar

  1. Career navigation market overview

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.

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.


Tales from the Front – What Teachers Are Telling Me at AI Workshops — from aliciabankhofer.substack.com by Alicia Bankhofer
Real conversations, real concerns: What teachers are saying about AI

“Do I really have to use AI?”

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.

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.


Welcome To AI Agent World! (Everything you need to know about the AI Agent market.) — from joshbersin.com by Josh Bersin

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 Unveils Prover V2 — from theaivalley.com

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.

Artificial Intelligence: Lessons Learned from a Graduate-Level Final Exam — from er.educause.edu by Craig Westling and Manish K. Mishra

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.


Deep Research with AI: 9 Ways to Get Started — from wondertools.substack.com by Jeremy Caplan
Practical strategies for thorough, citation-rich AI research
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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 Platform: Superintelligent AI Agents for Scientific Discovery — from futurehouse.org by Michael Skarlinski, Tyler Nadolski, James Braza, Remo Storni, Mayk Caldas, Ludovico Mitchener, Michaela Hinks, Andrew White, &  Sam Rodriques

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.”

Also relevant/see:

Coursera Founder Andrew Ng’s New Venture Brings A.I. to K–12 Classrooms — from observer.com by Victor Dey
Andrew Ng’s Kira Learning uses A.I. agents to transform K–12 education with tools for teachers, students and administrators.

“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.


AI as a Thought Partner in Higher Education — from er.educause.edu by Brian Basgen

When used thoughtfully and transparently, generative artificial intelligence can augment creativity and challenge assumptions, making it an excellent tool for exploring and developing ideas.

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.


AI for Automation or Augmentation of L&D? — from drphilippahardman.substack.com by Dr. Philippa Hardman
An audio summary of my Learning Technologies talk

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.

 

Record Law Grad Employment Rates Suggest AI Isn’t Killing Off Lawyers Just Yet — from lawnext.com by Bob Ambrogi

At a time when legal doomsayers have been predicting the imminent replacement of junior associates by AI legal assistants, the law school graduating class of 2024 has delivered a contrary verdict: Human lawyers aren’t going anywhere just yet.

According to the latest American Bar Association employment report, the legal job market is showing not just resilience, but growth. The data, reported as of March 17, 2025 — approximately 10 months after spring graduations — reveals that 82.2% of the 38,937 2024 law school graduates secured positions requiring bar admission — a two-point increase from the previous year.

Also see:


Leeds to host UK’s largest LegalTech event outside London as sector booms in the region by 50% — from yorkshirepost.co.uk by Jo Jessop
Leeds is gearing up to welcome hundreds of Legal and Tech professionals [on 4/24/25], as it hosts the fourth annual LegalTech in Leeds Conference – now the largest LegalTech event outside of London.

Set to take place on April 24 at Cloth Hall Court, Leeds, the 2025 conference comes at a time of extraordinary growth for the region’s LegalTech sector, which has seen a 50% increase in LegalTech firms between 2023 and 2024, according to a new report from Whitecap Consulting.

The event, themed “People & Technology,” will spotlight how digital innovation is transforming the legal sector while keeping human experience at its core. This year’s agenda will delve into the practical ways individuals and organisations can collaborate to deliver more efficient, accessible, and forward-thinking legal services. With hundreds of attendees expected, it’s set to be a landmark gathering of legal professionals, lawyers, tech professionals, entrepreneurs, academics and policymakers.


How Legal Tech is Reshaping the Broader Legal Ecosystem — from community.nasscom.in

The legal profession, long characterized by tradition and precedent, is undergoing a transformative shift driven by technological innovation. Legal technology, or “legal tech,” is not merely a tool for efficiency; it is a catalyst redefining the practice of law, the structure of legal services, and the accessibility of justice.

1. Streamlining Legal Operations
2. Enhancing Access to Justice
3. Transforming Legal Education and Roles
4. Redefining Client Expectations and Service Delivery
5. plus several more


 

Schools push career ed classes ‘for all,’ even kids heading to college — from hechingerreport.org by Javeria Salman
As backlash to ‘college for all’ grows, a new ‘CTE for all’ model blossoms. Backers say it engages students and prepares them for the future, but others worry it comes at a cost

The credit union is one small piece of a districtwide effort, Academies of Louisville, to embed career and technical education, or CTE, alongside core subjects like math and English and require every student to pick a career pathway by 10th grade. Piloted in 2017 at 11 high schools, the model has expanded to all 15 of the district’s main high schools. As part of that effort, the district has also launched a career exploration program at 14 middle schools, partnered with local colleges and universities to provide dual credit courses and smoothed the path for students to graduate with industry-recognized certifications.

The Academies of Louisville is one of roughly 30 such programs that are working to provide CTE for all students, regardless of whether they plan to go to college or directly into the workforce, according to Jessica Delgado, marketing and communications director of Ford Next Generation Learning, which supports school districts in adopting the approach.

 

What does ‘age appropriate’ AI literacy look like in higher education? — from timeshighereducation.com by Fun Siong Lim
As AI literacy becomes an essential work skill, universities need to move beyond developing these competencies at ‘primary school’ level in their students. Here, Fun Siong Lim reflects on frameworks to support higher-order AI literacies

Like platforms developed at other universities, Project NALA offers a front-end interface (known as the builder) for faculty to create their own learning assistant. An idea we have is to open the builder up to students to allow them to create their own GenAI assistant as part of our AI literacy curriculum. As they design, configure and test their own assistant, they will learn firsthand how generative AI works. They get to test performance-enhancement approaches beyond prompt engineering, such as grounding the learning assistant with curated materials (retrieval-augmented generation) and advanced ideas such as incorporating knowledge graphs.

They should have the opportunity to analyse, evaluate and create responsible AI solutions. Offering students the opportunity to build their own AI assistants could be a way forward to develop these much-needed skills.


How to Use ChatGPT 4o’s Update to Turn Key Insights Into Clear Infographics (Prompts Included) — from evakeiffenheim.substack.com by Eva Keiffenheim
This 3-step workflow helps you break down books, reports, or slide-decks into professional visuals that accelerate understanding.

This article shows you how to find core ideas, prompt GPT-4o3 for a design brief, and generate clean, professional images that stick. These aren’t vague “creative visuals”—they’re structured for learning, memory, and action.

If you’re a lifelong learner, educator, creator, or just someone who wants to work smarter, this process is for you.

You’ll spend less time re-reading and more time understanding. And maybe—just maybe—you’ll build ideas that not only click in your brain, but also stick in someone else’s.


SchoolAI Secures $25 Million to Help Teachers and Schools Reach Every Student — from globenewswire.com
 The Classroom Experience platform gives every teacher and student their own AI tools for personalized learning

SchoolAI’s Classroom Experience platform combines AI assistants for teachers that help with classroom preparation and other administrative work, and Spaces–personalized AI tutors, games, and lessons that can adapt to each student’s unique learning style and interests. Together, these tools give teachers actionable insights into how students are doing, and how the teacher can deliver targeted support when it matters most.

“Teachers and schools are navigating hard challenges with shrinking budgets, teacher shortages, growing class sizes, and ongoing recovery from pandemic-related learning gaps,” said Caleb Hicks, founder and CEO of SchoolAI. “It’s harder than ever to understand how every student is really doing. Teachers deserve powerful tools to help extend their impact, not add to their workload. This funding helps us double down on connecting the dots for teachers and students, and later this year, bringing school administrators and parents at home onto the platform as well.”


AI in Education, Part 3: Looking Ahead – The Future of AI in Learning — from rdene915.com by Dr. Rachelle Dené Poth

In the first and second parts of my AI series, I focused on where we see AI in classrooms. Benefits range from personalized learning and accessibility tools to AI-driven grading and support of a teaching assistant. In Part 2, I chose to focus on some of the important considerations related to ethics that must be part of the conversation. Schools need to focus on data privacy, bias, overreliance, and the equity divide. I wanted to focus on the future for this last part in the current AI series. Where do we go from here?


Anthropic Education Report: How University Students Use Claude — from anthropic.com

The key findings from our Education Report are:

  • STEM students are early adopters of AI tools like Claude, with Computer Science students particularly overrepresented (accounting for 36.8% of students’ conversations while comprising only 5.4% of U.S. degrees). In contrast, Business, Health, and Humanities students show lower adoption rates relative to their enrollment numbers.
  • We identified four patterns by which students interact with AI, each of which were present in our data at approximately equal rates (each 23-29% of conversations): Direct Problem Solving, Direct Output Creation, Collaborative Problem Solving, and Collaborative Output Creation.
  • Students primarily use AI systems for creating (using information to learn something new) and analyzing (taking apart the known and identifying relationships), such as creating coding projects or analyzing law concepts. This aligns with higher-order cognitive functions on Bloom’s Taxonomy. This raises questions about ensuring students don’t offload critical cognitive tasks to AI systems.

From the Kuali Days 2025 Conference: A CEO’s View of Planning for AI — from campustechnology.com by Mary Grush
A Conversation with Joel Dehlin

How can a company serving higher education navigate the changes AI brings to the ed tech marketplace? What will customers expect in this dynamic? Here, CT talks with Kuali CEO Joel Dehlin, who shared his company’s AI strategies in a featured plenary session, “Sneak Peek of AI in Kuali Build,” at Kuali Days 2025 in Anaheim.


How students can use generative AI — from aliciabankhofer.substack.com by Alicia Bankhofer
Part 4 of 4 in my series on Teaching and Learning in the AI Age

This article is the culmination of a series exploring AI’s impact on education.

Part 1: What Educators Need outlined essential AI literacy skills for teachers, emphasizing the need to move beyond basic ChatGPT exploration to understand the full spectrum of AI tools available in education.

Part 2: What Students Need addressed how students require clear guidance to use AI safely, ethically, and responsibly, with emphasis on developing critical thinking skills alongside AI literacy.

Part 3: How Educators Can Use GenAI presented ten practical use cases for teachers, from creating differentiated resources to designing assessments, demonstrating how AI can reclaim 5-7 hours weekly for meaningful student interactions.

Part 4: How Students Can Use GenAI (this article) provides frameworks for guiding student AI use based on Joscha Falck’s dimensions: learning about, with, through, despite, and without AI.


Mapping a Multidimensional Framework for GenAI in Education — from er.educause.edu by Patricia Turner
Prompting careful dialogue through incisive questions can help chart a course through the ongoing storm of artificial intelligence.

The goal of this framework is to help faculty, educational developers, instructional designers, administrators, and others in higher education engage in productive discussions about the use of GenAI in teaching and learning. As others have noted, theoretical frameworks will need to be accompanied by research and teaching practice, each reinforcing and reshaping the others to create understandings that will inform the development of approaches to GenAI that are both ethical and maximally beneficial, while mitigating potential harms to those who engage with it.


Instructional Design Isn’t Dying — It’s Specialising — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, how AI is impacting role & purpose of Instructional Design

Together, these developments have revealed something important: despite widespread anxiety, the instructional design role isn’t dying—it’s specialising.

What we’re witnessing isn’t the automation of instructional design and the death of the instructional designer, but rather the evolution of the ID role into multiple distinct professional pathways.

The generalist “full stack” instructional designer is slowly but decisively fracturing into specialised roles that reflect both the capabilities of generative AI and the strategic imperatives facing modern organisations.

In this week’s blog post, I’ll share what I’ve learned about how our field is transforming, and what it likely means for you and your career path.

Those instructional designers who cling to traditional generalist models risk being replaced, but those who embrace specialisation, data fluency, and AI collaboration will excel and lead the next evolution of the field. Similarly, those businesses that continue to view L&D as a cost centre and focus on automating content delivery will be outperformed, while those that invest in building agile, AI-enabled learning ecosystems will drive measurable performance gains and secure their competitive advantage.


Adding AI to Every Step in Your eLearning Design Workflow — from learningguild.com by George Hanshaw

We know that eLearning is a staple of training and development. The expectations of the learners are higher than ever: They expect a dynamic, interactive, and personalized learning experience. As instructional designers, we are tasked with meeting these expectations by creating engaging and effective learning solutions.

The integration of Artificial Intelligence (AI) into our eLearning design process is a game-changer that can significantly enhance the quality and efficiency of our work.

No matter if you use ADDIE or rapid prototyping, AI has a fit in every aspect of your workflow. By integrating AI, you can ensure a more efficient and effective design process that adapts to the unique needs of your learners. This not only saves time and resources but also significantly enhances the overall learning experience. We will explore the needs analysis and the general design process.

 

A new kind of high school diploma trades chemistry for carpentry — from hechingerreport.org by Ariel Gilreath
Starting this fall, Alabama high school students can choose to take state-approved career and technical education courses in place of upper level math and science, such as Algebra 2 or chemistry.

Alabama state law previously required students to take at least four years each of English, math, science and social studies to graduate from high school. The state is now calling that track the “Option A” diploma. The new “Option B” workforce diploma allows students to replace two math and two science classes with a sequence of three CTE courses of their choosing. The CTE courses do not have to be related to math or science, but they do have to be in the same career cluster. Already, more than 70 percent of Alabama high school students take at least one CTE class, according to the state’s Office of Career and Technical Education/Workforce Development.

***

BIRMINGHAM, Ala. — In a corner of Huffman High School, the sounds of popping nail guns and whirring table saws fill the architecture and construction classroom.

Down the hall, culinary students chop and saute in the school’s commercial kitchen, and in another room, cosmetology students snip mannequin hair to prepare for the state’s natural hair stylist license.

Starting this fall, Alabama high school students can choose to take these classes — or any other state-approved career and technical education courses — in place of upper level math and science, such as Algebra 2 or chemistry.

From DSC:
This is excellent. Provide more choice. Engage all kinds of students with all kinds of interests, gifts, and abilities. Make learning fun and enjoyable and practical for students. The setup in this article mentions that “many universities, including the state’s flagship University of Alabama, require at least three math credits for admission. The workforce diploma would make it more difficult for students on that track to get into those colleges.” But perhaps college is not where these students want to go. Or perhaps the colleges and universities across our land should offer some additional pathways into them as well as new sorts of curricula and programs.

 

Thomson Reuters Survey: Over 95% of Legal Professionals Expect Gen AI to Become Central to Workflow Within Five Year — from lawnext.com by Bob Ambrogi

Thomson Reuters today released its 2025 Generative AI in Professional Services Report, and it reveals that legal professionals have become increasingly optimistic about generative AI, with adoption rates nearly doubling over the past year and a growing belief that the technology should be incorporated into legal work.

According to the report, 26% of legal organizations are now actively using gen AI, up from 14% in 2024. While only 15% of law firm respondents say gen AI is currently central to their workflow, a striking 78% believe it will become central within the next five years.


AI-Powered Legal Work Redefined: Libra Launches Major Update for Legal Professionals — from lawnext.com by Bob Ambrogi

Berlin, April 14, 2025 – Berlin-based Legal Tech startup Libra is launching its most comprehensive update to date, leveraging AI to relieve law firms and legal departments of routine tasks, accelerate research, and improve team collaboration. “Libra v2” combines highly developed AI, a modern user interface, and practical tools to set a new standard for efficient and precise work in all legal areas.

“We listened intently to feedback from law firms and in-house teams,” said Viktor von Essen, founder of Libra. “The result is Libra v2: an AI solution that intelligently supports every step of daily legal work – from initial research to final contract review. We want legal experts to be able to fully concentrate on what is essential: excellent legal advice.”


The Three Cs of Teaching Technology to Law Students — from lawnext.com by Bob Ambrogi

In law practice today, technology is no longer optional — it’s essential. As practicing attorneys increasingly rely on technology tools to serve clients, conduct research, manage documents and streamline workflows, the question is often debated: Are law schools adequately preparing students for this reality?

Unfortunately, for the majority of law schools, the answer is no. But that only begs the question: What should they be doing?

A coincidence of events last week had me thinking about law schools and legal tech, chief among them my attendance at LIT Con, Suffolk Law School’s annual conference to showcase legal innovation and technology — with a portion of it devoted to access-to-justice projects developed by Suffolk Law students themselves.


While not from Bob, I’m also going to include this one here:

Your AI Options: 7 Considerations Before You Buy — from artificiallawyer.com by Liza Pestillos-Ocat

But here’s the problem: not all AI is useful and not all of it is built for the way your legal team works.

Most firms aren’t asking whether they should use AI because they already are. The real question now is what comes next? How do you expand the value of AI across more teams, more matters, and more workflows without introducing unnecessary risk, complexity, or cost?

To get this right, legal professionals need to understand which tools will solve real problems and deliver the most value to their team. That starts with asking better questions, including the ones that follow, before making your next investment in AI for lawyers.

 

From DSC:
After seeing Sam’s posting below, I can’t help but wonder:

  • How might the memory of an AI over time impact the ability to offer much more personalized learning?
  • How will that kind of memory positively impact a person’s learning-related profile?
  • Which learning-related agents get called upon?
  • Which learning-related preferences does a person have while learning about something new?
  • Which methods have worked best in the past for that individual? Which methods didn’t work so well with him or her?



 

Reflections on “Are You Ready for the AI University? Everything is about to change.” [Latham]

.
Are You Ready for the AI University? Everything is about to change. — from chronicle.com by Scott Latham

Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.

What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.

Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.

In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom. 

From DSC:
I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.

Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.

There are a few places where Scott and I differ.

  • The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:

To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.” 

Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”

— Satya Nitta, a longtime computer researcher at
IBM’s Watson
Research Center in Yorktown Heights, NY
.

By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.

  • Also, I would use the term learning preferences where Scott uses the term learning styles.

Scott also mentions:

“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”

It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).

That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.

So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!


Addendum later on 4/10/25:

U-M’s Ross School of Business, Google Public Sector launch virtual teaching assistant pilot program — from news.umich.edu by Jeff Karoub; via Paul Fain

Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.

The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.

The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.

 

The 2025 AI Index Report — from Stanford University’s Human-Centered Artificial Intelligence Lab (hai.stanford.edu); item via The Neuron

Top Takeaways

  1. AI performance on demanding benchmarks continues to improve.
  2. AI is increasingly embedded in everyday life.
  3. Business is all in on AI, fueling record investment and usage, as research continues to show strong productivity impacts.
  4. The U.S. still leads in producing top AI models—but China is closing the performance gap.
  5. The responsible AI ecosystem evolves—unevenly.
  6. Global AI optimism is rising—but deep regional divides remain.
  7. …and several more

Also see:

The Neuron’s take on this:

So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.

Just keep two big things in mind:

  1. Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
  2. Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.

So, use the tools, find what helps you, but don’t trust them completely.

We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.


Addendum on 4/16:

 

The 2025 ABA Techshow Startup Alley Pitch Competition Ended In A Tie – Here Are The Winners — from lawnext.com by Bob Ambrogi

This year, two startups ended up with an equal number of votes for the top spot:

  • Case Crafter, a company from Norway that helps legal professionals build compelling visual timelines based on case files and evidence.
  • Querious, a product that provides attorneys with real-time insights during client conversations into legal issues, relevant content, and suggested questions and follow-ups.
    .


AI academy gives law students a head start on legal tech, says OBA innovator — from canadianlawyermag.com by Branislav Urosevic

The Ontario Bar Association has recently launched a hands-on AI learning platform tailored for lawyers. Called the AI Academy, the initiative is designed to help legal professionals explore, experiment with, and adopt AI tools relevant to their practice.

Colin Lachance, OBA’s innovator-in-residence and the lead designer of the platform, says that although the AI Academy was built for practising lawyers, it is also well-suited for law students.


 
© 2025 | Daniel Christian