Tech check: Innovation in motion: How AI is rewiring L&D workflows — from chieflearningofficer.com by Gabrielle Pike
AI isn’t here to replace us. It’s here to level us up.

For today’s chief learning officer, the days of just rolling out compliance training are long gone. In 2025, learning and development leaders are architects of innovation, crafting ecosystems that are agile, automated and AI-infused. This quarter’s Tech Check invites us to pause, assess and get strategic about where tech is taking us. Because the goal isn’t more tools—it’s smarter, more human learning systems that scale with the business.

Sections include:

  • The state of AI in L&D: Hype vs. reality
  • AI in design: From static content to dynamic experiences
  • AI in development: Redefining production workflows
  • Strategic questions CLOs should be asking
  • Future forward: What’s next?
  • Closing thought

American Federation of Teachers (AFT) to Launch National Academy for AI Instruction with Microsoft, OpenAI, Anthropic and United Federation of Teachers — from aft.org

NEW YORK – The AFT, alongside the United Federation of Teachers and lead partner Microsoft Corp., founding partner OpenAI, and Anthropic, announced the launch of the National Academy for AI Instruction today. The groundbreaking $23 million education initiative will provide access to free AI training and curriculum for all 1.8 million members of the AFT, starting with K-12 educators. It will be based at a state-of-the-art bricks-and-mortar Manhattan facility designed to transform how artificial intelligence is taught and integrated into classrooms across the United States.

The academy will help address the gap in structured, accessible AI training and provide a national model for AI-integrated curriculum and teaching that puts educators in the driver’s seat.


Students Are Anxious about the Future with A.I. Their Parents Are, Too. — from educationnext.org by Michael B. Horn
The fast-growing technology is pushing families to rethink the value of college

In an era when the college-going rate of high school graduates has dropped from an all-time high of 70 percent in 2016 to roughly 62 percent now, AI seems to be heightening the anxieties about the value of college.

According to the survey, two-thirds of parents say AI is impacting their view of the value of college. Thirty-seven percent of parents indicate they are now scrutinizing college’s “career-placement outcomes”; 36 percent say they are looking at a college’s “AI-skills curriculum,” while 35 percent respond that a “human-skills emphasis” is important to them.

This echoes what I increasingly hear from college leadership: Parents and students demand to see a difference between what they are getting from a college and what they could be “learning from AI.”


This next item on LinkedIn is compliments of Ray Schroeder:



How to Prepare Students for a Fast-Moving (AI)World — from rdene915.com by Dr. Rachelle Dené Poth

Preparing for a Future-Ready Classroom
Here are the core components I focus on to prepare students:

1. Unleash Creativity and Problem-Solving.
2. Weave in AI and Computational Thinking.
3. Cultivate Resilience and Adaptability.


AI Is Reshaping Learning Roles—Here’s How to Future-Proof Your Team — from onlinelearningconsortium.org by Jennifer Mathes, Ph.D., CEO, Online Learning Consortium; via Robert Gibson on LinkedIn

Culture matters here. Organizations that foster psychological safety—where experimentation is welcomed and mistakes are treated as learning—are making the most progress. When leaders model curiosity, share what they’re trying, and invite open dialogue, teams follow suit. Small tests become shared wins. Shared wins build momentum.

Career development must be part of this equation. As roles evolve, people will need pathways forward. Some will shift into new specialties. Others may leave familiar roles for entirely new ones. Making space for that evolution—through upskilling, mobility, and mentorship—shows your people that you’re not just investing in AI, you’re investing in them.

And above all, people need transparency. Teams don’t expect perfection. But they do need clarity. They need to understand what’s changing, why it matters, and how they’ll be supported through it. That kind of trust-building communication is the foundation for any successful change.

These shifts may play out differently across sectors—but the core leadership questions will likely be similar.

AI marks a turning point—not just for technology, but for how we prepare our people to lead through disruption and shape the future of learning.


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How Do You Teach Computer Science in the A.I. Era? — from nytimes.com by Steve Lohr; with thanks to Ryan Craig for this resource
Universities across the country are scrambling to understand the implications of generative A.I.’s transformation of technology.

The future of computer science education, Dr. Maher said, is likely to focus less on coding and more on computational thinking and A.I. literacy. Computational thinking involves breaking down problems into smaller tasks, developing step-by-step solutions and using data to reach evidence-based conclusions.

A.I. literacy is an understanding — at varying depths for students at different levels — of how A.I. works, how to use it responsibly and how it is affecting society. Nurturing informed skepticism, she said, should be a goal.

At Carnegie Mellon, as faculty members prepare for their gathering, Dr. Cortina said his own view was that the coursework should include instruction in the traditional basics of computing and A.I. principles, followed by plenty of hands-on experience designing software using the new tools.

“We think that’s where it’s going,” he said. “But do we need a more profound change in the curriculum?”

 

In A Mega Deal, Clio Buys vLex for $1 Billion, Merging AI, Research and Practice Management — from lawnext.com by Bob Ambrogi

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.”

 

Transform Public Speaking with Yoodli: Your AI Coach — from rdene915.com by Paula Johnson

Yoodli is an AI tool designed to help users improve their public speaking skills. It analyzes your speech in real-time or after a recording and gives you feedback on things like:

    • Filler words (“um,” “like,” “you know”)
    • Pacing (Are you sprinting or sedating your audience?)
    • Word choice and sentence complexity
    • Eye contact and body language (with video)
    • And yes, even your “uhhh” to actual word ratio

Yoodli gives you a transcript and a confidence score, plus suggestions that range from helpful to brutally honest. It’s basically Simon Cowell with AI ethics and a smiley face interface.


[What’s] going on with AI and education? — from theneuron.ai by Grant Harvey
With students and teachers alike using AI, schools are facing an “assessment crisis” where the line between tool and cheating has blurred, forcing a shift away from a broken knowledge economy toward a new focus on building human judgment through strategic struggle.

What to do about it: The future belongs to the “judgment economy,” where knowledge is commoditized but taste, agency, and learning velocity become the new human moats. Use the “Struggle-First” principle: wrestle with problems for 20-30 minutes before turning to AI, then use AI as a sparring partner (not a ghostwriter) to deepen understanding. The goal isn’t to avoid AI, but to strategically choose when to embrace “desirable difficulties” that build genuine expertise versus when to leverage AI for efficiency.

The Alpha-School Program in brief:

    • Students complete core academics in just 2 hours using AI tutors, freeing up 4+ hours for life skills, passion projects, and real-world experiences.
    • The school claims students learn at least 2x faster than their peers in traditional school.
    • The top 20% of students show 6.5x growth. Classes score in the top 1-2% nationally across the board.
    • Claims are based on NWEA’s Measures of Academic Progress (MAP) assessments… with data only available to the school. Hmm…

Austen Allred shared a story about the school, which put it on our radar.


Featured Report:  Teaching for Tomorrow: Unlocking Six Weeks a Year With AI — from gallup.com
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In the latest installment of Gallup and the Walton Family Foundation’s research on education, K-12 teachers reveal how AI tools are transforming their workloads, instructional quality and classroom optimism. The report finds that 60% of teachers used an AI tool during the 2024–25 school year. Weekly AI users report reclaiming nearly six hours per week — equivalent to six weeks per year — which they reinvest in more personalized instruction, deeper student feedback and better parent communication.

Despite this emerging “AI dividend,” adoption is uneven: 40% of teachers aren’t using AI at all, and only 19% report their school has a formal AI policy. Teachers with access to policies and support save significantly more time.

Educators also say AI improves their work. Most report higher-quality lesson plans, assessments and student feedback. And teachers who regularly use AI are more optimistic about its benefits for student engagement and accessibility — mirroring themes from the Voices of Gen Z: How American Youth View and Use Artificial Intelligence report, which found students hesitant but curious about AI’s classroom role. As AI tools grow more embedded in education, both teachers and students will need the training and support to use them effectively.

Also see:

  • 2-Hour Learning
    • What if children could crush academics in 2 hours, 2x faster? 
    • What if children could get back their most valuable resource, which is time?
    • What if children could pursue the things they want during their afternoons and develop life skills?

Amira Learning: Teaching With The AI-Powered Reading Tool — from techlearning.com by Erik Ofgang
Amira Learning is a research-backed AI reading tutor that incorporates the science of reading into its features.

What Is Amira Learning?
Amira Learning’s system is built upon research led by Jack Mostow, a professor at Carnegie Mellon who helped pioneer AI literacy education. Amira uses Claude AI to power its AI features, but these features are different than many other AI tools on the market. Instead of focusing on chat and generative response, Amira’s key feature is its advanced speech recognition and natural language processing capabilities, which allow the app to “hear” when a student is struggling and tailor suggestions to that student’s particular mistakes.

Though it’s not meant to replace a teacher, Amira provides real-time feedback and also helps teachers pinpoint where a student is struggling. For these reasons, Amira Learning is a favorite of education scientists and advocates for science of reading-based literacy instruction. The tool currently is used by more than 4 million students worldwide and across the U.S.


 
 

The résumé is dying, and AI is holding the smoking gun — from arstechnica.com by Benj Edwards
As thousands of applications flood job posts, ‘hiring slop’ is kicking off an AI arms race.

Employers are drowning in AI-generated job applications, with LinkedIn now processing 11,000 submissions per minute—a 45 percent surge from last year, according to new data reported by The New York Times.

Due to AI, the traditional hiring process has become overwhelmed with automated noise. It’s the résumé equivalent of AI slop—call it “hiring slop,” perhaps—that currently haunts social media and the web with sensational pictures and misleading information. The flood of ChatGPT-crafted résumés and bot-submitted applications has created an arms race between job seekers and employers, with both sides deploying increasingly sophisticated AI tools in a bot-versus-bot standoff that is quickly spiraling out of control.

The Times illustrates the scale of the problem with the story of an HR consultant named Katie Tanner, who was so inundated with over 1,200 applications for a single remote role that she had to remove the post entirely and was still sorting through the applications three months later.


Job seekers are leaning into AI — and other happenings in the world of work — from LinkedIn News

Job growth is slowing — and for many professionals, that means longer job hunts and more competition. As a result, more job seekers are turning to AI to streamline their search and stand out.

From optimizing resumes to preparing for interviews, AI tools are becoming a key part of today’s job hunt. Recruiters say it’s getting harder to sift through application materials and identify what is AI-generated and decipher which applicants are actually qualified — but they also say they prefer candidates with AI skills.

The result? Job seekers are growing their familiarity with AI faster than their non-job-seeking counterparts and it’s shifting how they view the workplace. According to LinkedIn’s latest Workforce Confidence survey, over half of active job seekers (52%) believe AI will eventually take on some of the mundane, manual tasks that they’re currently focused on, compared to 46% of others not actively job seeking.


OpenAI warns models with higher bioweapons risk are imminent — from axios.com by Ina Fried

OpenAI cautioned Wednesday that upcoming models will head into a higher level of risk when it comes to the creation of biological weapons — especially by those who don’t really understand what they’re doing.

Why it matters: The company, and society at large, need to be prepared for a future where amateurs can more readily graduate from simple garage weapons to sophisticated agents.

Driving the news: OpenAI executives told Axios the company expects forthcoming models will reach a high level of risk under the company’s preparedness framework.

    • As a result, the company said in a blog post, it is stepping up the testing of such models, as well as including fresh precautions designed to keep them from aiding in the creation of biological weapons.
    • OpenAI didn’t put an exact timeframe on when the first model to hit that threshold will launch, but head of safety systems Johannes Heidecke told Axios “We are expecting some of the successors of our o3 (reasoning model) to hit that level.”

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“Using AI Right Now: A Quick Guide” [Molnick] + other items re: AI in our learning ecosystems

Thoughts on thinking — from dcurt.is by Dustin Curtis

Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself. 


Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them

Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.

First, the easy stuff.

Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.

Also see:


Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.

The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.


The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures

On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.

Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.

Of course, that would be a mistake.

We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.




Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng

By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.


This AI Model Never Stops Learning — from link.wired.com by Will Knight

Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.

The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.

The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.


Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing

Highlights:

  • Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
  • Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
 

AI will kill billable hour, says lawtech founder — from lawgazette.co.uk by John Hyde

A pioneer in legal technology has predicted the billable hour model cannot survive the transition into the use of artificial intelligence.

Speaking to the Gazette on a visit to the UK, Canadian Jack Newton, founder and chief executive of lawtech company Clio, said there was a ‘structural incompatibility’ between the productivity gains of AI and the billable hour.

Newton said the adoption of AI should be welcomed and embraced by the legal profession but that lawyers will need an entrepreneurial mindset to make the most of its benefits.

Newton added: ‘There is enormous demand but the paradox is that the number one thing we hear from lawyers is they need to grow their firms through more clients, while 77% of legal needs are not met.

‘It’s exciting that AI can address these challenges – it will be a tectonic shift in the industry driving down costs and making legal services more accessible.’


Speaking of legaltech-related items, also see:

Legal AI Platform Harvey To Get LexisNexis Content and Tech In New Partnership Between the Companies — from lawnext.com by Bob Ambrogi

The generative AI legal startup Harvey has entered into a strategic alliance with LexisNexis Legal & Professional by which it will integrate LexisNexis’ gen AI technology, primary law content, and Shepard’s Citations within the Harvey platform and jointly develop advanced legal workflows.

As a result of the partnership, Harvey’s customers working within its platform will be able to ask questions of LexisNexis Protégé, the AI legal assistant released in January, and receive AI-generated answers grounded in the LexisNexis collection of U.S. case law and statutes and validated through Shepard’s Citations, the companies said.

 

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI — from papers.ssrn.com by Barbara Oakley, Michael Johnston, Kenzen Chen, Eulho Jung, and Terrence Sejnowski; via George Siemens

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.

Keywords
cognitive offloading, memory, neuroscience of learning, declarative memory, procedural memory, generative AI, Flynn Effect, education reform, schemata, digital tools, cognitive load, cognitive architecture, reinforcement learning, basal ganglia, working memory, retrieval practice, schema theory, manifolds

 

Mary Meeker AI Trends Report: Mind-Boggling Numbers Paint AI’s Massive Growth Picture — from ndtvprofit.com
Numbers that prove AI as a tech is unlike any other the world has ever seen.

Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.

  • AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
  • ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
  • ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.

Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg
How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.

The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.

 

Also see Meeker’s actual report at:

Trends – Artificial Intelligence — from bondcap.com by Mary Meeker / Jay Simons / Daegwon Chae / Alexander Krey



The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.

The details:

  • Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
  • The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
  • The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
  • Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.

Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.

 

“The AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course. 


How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.


In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.


Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.




AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.


What can we do about generative AI in our teaching?  — from linkedin.com by Kristina Peterson

So what can we do?

  • Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
  • Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
  • Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.

In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

 

Cultivating a responsible innovation mindset among future tech leaders — from timeshighereducation.com by Andreas Alexiou from the University of Southampton
The classroom is a perfect place to discuss the messy, real-world consequences of technological discoveries, writes Andreas Alexiou. Beyond ‘How?’, students should be asking ‘Should we…?’ and ‘What if…?’ questions around ethics and responsibility

University educators play a crucial role in guiding students to think about the next big invention and its implications for privacy, the environment and social equity. To truly make a difference, we need to bring ethics and responsibility into the classroom in a way that resonates with students. Here’s how.

Debating with industry pioneers on incorporating ethical frameworks in innovation, product development or technology adoption is eye-opening because it can lead to students confronting assumptions they hadn’t questioned before.

Students need more than just skills; they need a mindset that sticks with them long after graduation. By making ethics and responsibility a key part of the learning process, educators are doing more than preparing students for a career; they’re preparing them to navigate a world shaped by their choices.

 

The 2025 Global Skills Report— from coursera.org
Discover in-demand skills and credentials trends across 100+ countries and six regions to deliver impactful industry-aligned learning programs.

GenAI adoption fuels global skill demands
In 2023, early adopters flocked to GenAI, with approximately one person per minute enrolling in a GenAI course on Coursera —a rate that rose to eight per minute in 2024.  Since then, GenAI has continued to see exceptional growth, with global enrollment in GenAI courses surging 195% year-over-year—maintaining its position as one of the most rapidly growing skill domains on our platform. To date, Coursera has recorded over 8 million GenAI enrollments, with 12 learners per minute signing up for GenAI content in 2025 across our catalog of nearly 700 GenAI courses.

Driving this surge, 94% of employers say they’re likely to hire candidates with GenAI credentials, while 75% prefer hiring less-experienced candidates with GenAI skills over more experienced ones without these capabilities.8 Demand for roles such as AI and Machine Learning Specialists is projected to grow by up to 40% in the next four years.9 Mastering AI fundamentals—from prompt engineering to large language model (LLM) applications—is essential to remaining competitive in today’s rapidly evolving economy.

Countries leading our new AI Maturity Index— which highlights regions best equipped to harness AI innovation and translate skills into real-world applications—include global frontrunners such as Singapore, Switzerland, and the United States.

Insights in action

Businesses
Integrate role-specific GenAI modules into employee development programs, enabling teams to leverage AI for efficiency and innovation.

Governments
Scale GenAI literacy initiatives—especially in emerging economies—to address talent shortages and foster human-machine capabilities needed to future-proof digital jobs.

Higher education
Embed credit-eligible GenAI learning into curricula, ensuring graduates enter the workforce job-ready.

Learners
Focus on GenAI courses offering real-world projects (e.g., prompt engineering) that help build skills for in-demand roles.

 

Scientific breakthrough: artificial blood for all blood groups — from getsuperintel.com by Kim “Chubby” Isenberg
Japan’s universal artificial blood could revolutionize emergency medicine and global healthcare resilience.

They all show that we are on the threshold of a new era – one in which technological systems are no longer just tools, but independent players in medical, cognitive and infrastructural change.

This paradigm shift means that AI will no longer be limited to static training data, but will learn through open exploration, similar to biological organisms. This is nothing less than the beginning of an era of autonomous cognition.


From DSC:
While there are some promising developments involving AI these days, we need to look at what the potential downsides might be of AI becoming independent players, don’t you think? Otherwise, what could possibly go wrong?


 

AI & Schools: 4 Ways Artificial Intelligence Can Help Students — from the74million.org by W. Ian O’Byrne
AI creates potential for more personalized learning

I am a literacy educator and researcher, and here are four ways I believe these kinds of systems can be used to help students learn.

  1. Differentiated instruction
  2. Intelligent textbooks
  3. Improved assessment
  4. Personalized learning


5 Skills Kids (and Adults) Need in an AI World — from oreilly.com by Raffi Krikorian
Hint: Coding Isn’t One of Them

Five Essential Skills Kids Need (More than Coding)
I’m not saying we shouldn’t teach kids to code. It’s a useful skill. But these are the five true foundations that will serve them regardless of how technology evolves.

  1. Loving the journey, not just the destination
  2. Being a question-asker, not just an answer-getter
  3. Trying, failing, and trying differently
  4. Seeing the whole picture
  5. Walking in others’ shoes

The AI moment is now: Are teachers and students ready? — from iblnews.org

Day of AI Australia hosted a panel discussion on 20 May, 2025. Hosted by Dr Sebastian Sequoiah-Grayson (Senior Lecturer in the School of Computer Science and Engineering, UNSW Sydney) with panel members Katie Ford (Industry Executive – Higher Education at Microsoft), Tamara Templeton (Primary School Teacher, Townsville), Sarina Wilson (Teaching and Learning Coordinator – Emerging Technology at NSW Department of Education) and Professor Didar Zowghi (Senior Principal Research Scientist at CSIRO’s Data61).


Teachers using AI tools more regularly, survey finds — from iblnews.org

As many students face criticism and punishment for using artificial intelligence tools like ChatGPT for assignments, new reporting shows that many instructors are increasingly using those same programs.


Addendum on 5/28/25:

A Museum of Real Use: The Field Guide to Effective AI Use — from mikekentz.substack.com by Mike Kentz
Six Educators Annotate Their Real AI Use—and a Method Emerges for Benchmarking the Chats

Our next challenge is to self-analyze and develop meaningful benchmarks for AI use across contexts. This research exhibit aims to take the first major step in that direction.

With the right approach, a transcript becomes something else:

  • A window into student decision-making
  • A record of how understanding evolves
  • A conversation that can be interpreted and assessed
  • An opportunity to evaluate content understanding

This week, I’m excited to share something that brings that idea into practice.

Over time, I imagine a future where annotated transcripts are collected and curated. Schools and universities could draw from a shared library of real examples—not polished templates, but genuine conversations that show process, reflection, and revision. These transcripts would live not as static samples but as evolving benchmarks.

This Field Guide is the first move in that direction.


 
© 2025 | Daniel Christian