training / L&D

Three items re: AI in our learning ecosystems

On 05/26/2026, in adjunct faculty, business, career development, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, policy, productivity / tips and tricks, student-related, teaching & learning, training / L&D, United States, universities, vision/possibilities, workplace, by Daniel Christian

I Was a University AI Czar. I’m Not Equipped to Teach in the Age of AI. — from jgellers.substack.com by Josh Gellers, PhD

The reason that I claim I am not well-suited to thrive as an instructor in the age of AI is because both AI Enthusiasts and AI Resisters put a lot of thought and energy into completely redesigning their classes in response to AI. This is the one takeaway that I don’t think the Exhausted Majority has fully accepted yet—to excel as a teacher in this AI era, you need to totally revise how you teach and how you assess what students learn in your classes.

I can say this much—whatever solution our industry comes up with, it’s likely to emerge from teaching and learning centers. Contrary to what Paul Schofield wrote in the Chronicle of Higher Education, pedagogy experts are the best hope we have to equip today’s faculty with the tools required to succeed in this uncertain educational environment. As I always tell my students, “I was trained for 7 years to become a researcher and 2 days to become a teacher.” The idea that only disciplinary experts know how to teach and have nothing to learn from so-called “nonscholars” is so laughable that one has to wonder whether an AI agent jokingly wrote that sad opinion piece to troll the whole academe.

Also from Dr. Gellers, see:

The Worst AI Policy in Higher Ed
How Berkeley Law Boalt-ed From Expertise in Favor of Abstinence

Last week, one of the top law schools in the United States, the University of California, Berkeley School of Law, released its final policy on artificial intelligence, effective summer 2026. In the span of a breezy 1.5 pages, the school outlined the challenge AI poses to legal education and how it plans to address this problem. Despite these intentions, this AI policy is, in my estimation, the worst AI policy in higher education I have seen.

From AI Tutors to AI Study Mates— from drphilippahardman.substack.com by Dr Philippa Hardman
New research reveals how AI can enable real learning — not just productivity gains

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The point isn’t that AI is inherently bad for learning — it’s that the meta-analyses showing that LLMs improve assignment and performance scores are measuring the wrong thing. They’re measuring performance with the AI present, not learning that persists once it’s gone.

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From DSC:
Notice that when an AI-based learning system can remember what you’ve worked on and how you are doing — where you are struggling or doing well — it can have a positive impact on your longer-term learning. That, to me, is where long-term based learner profiles come in.

Later in the article, Dr. Hardman points out that “if we want to deliver AI tooling which supports substantive learning, we need to intentionally create a new category of AI tool for ‘learning at work’ which prioritises learning and development over productivity.” While I agree with that, I do wonder if businesses will care, so long as the work gets done and gets done well. But this calls into mind the word “experience” — something that traditionally has been hard fought to get in the corporate world. But the corporate realm often doesn’t like to pay for experience (beyond key AI-based jobs) when they perceive it’s getting too expensive. Ask all those 50 and over who had or have a target on their backs.

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What is L&D’s role when AI is already part of work, information and capability? [Taylor & Vinauskaite]

On 05/21/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, business, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, emerging technologies, human-computer interaction (HCI), instructional design, intelligent systems, learning, learning ecosystem, Learning Experience Design, training / L&D, United States, by Daniel Christian

Here is Don Taylor’s posting on LinkedIn.com

Also relevant/see:

Here is Egle Vinauskaite’s posting on LinkedIn.com

Deans for Impact Releases New Edition of The Science of Learning — from deansforimpact.org
Second edition of seminal report reflects new research amidst growing momentum for evidence-based instruction in teacher preparation and PK-12.

AUSTIN, Texas (May 19, 2026) – Deans for Impact (DFI) today released the second edition of The Science of Learning, a report translating cognitive-science research into practical implications for teaching. The updated edition includes new research on memory, attention, motivation, and learning misconceptions, offering educators a research-based foundation for understanding how to support durable student learning.

First released in 2015, The Science of Learning is DFI’s most widely-used and cited resource, with more than one million downloads. Since its publication, DFI has supported nearly 300 teacher-preparation programs to make instructional quality a priority in the way teachers are prepared, directly impacting more than 110,000 teachers over the last decade.

The second edition arrives at a moment when more than 40 states have made meaningful investments in strengthening evidence-based instruction, particularly in early literacy, mathematics, and the use of high-quality instructional materials. The science of learning supports future teachers to build a comprehensive foundation for instructional decision-making that cuts across content areas and grade levels.
…

The report has been endorsed by more than 100 field experts and leading organizations across the United States and internationally.

Download the report at deansforimpact.org/thescienceoflearning.

An example excerpt:

“The sad fact is that we don’t teach learners how to be good at learning. Whether K12, higher ed, or organizations, it’s just not there.”

— from Clark Quinn’s posting entitled, Thoughts on meta-coaching!

From DSC:
I agree. We could do a much better job at this.

Three items re: AI in our learning ecosystems

On 05/16/2026, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, library / librarians, organizational change, pace of change, skills, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, vendors, workplace, by Daniel Christian

LinkedIn Grad’s Guide 2026: Starting your career in the AI era — from linkedin.com by Gianna Prudente
To help you head off in the right direction, we’ve identified where those starting their careers are finding opportunity, based on data from millions of LinkedIn member profiles.

While all of this is happening, colleges are still catching up. Many students are graduating without having spent much time learning how AI actually fits into day-to-day work — even as employers seek out those exact skills.

“Colleges are moving into an era of, we’ll let the faculty decide, which leads to a very uneven experience for students because some faculty are really into AI and other faculty are not,” says Jeff Selingo, a higher education strategist. “Employers are the same; they don’t really know how to act around early careers.”

Taken together, new grads are entering a uniquely challenging environment: fewer traditional entry points, slower turnover and a workplace that’s evolving faster than the systems preparing people for it.

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I knew my writing students were using AI. Their confessions led to a powerful teaching moment — from theguardian.com by Micah Nathan
The problem wasn’t just the perfectly polished, yet mediocre prose. It’s what’s lost when we surrender the struggle to translate thought into words

For a few moments, all was quiet except the classroom’s ticking radiators. Then, a teary-eyed confession: one of the ostensible authors said she only used AI because she was scared of looking stupid, of being criticized for bad writing. She said she loved writing stories and hated having used AI. But she couldn’t stop herself, recounting a sequence similar to an addict’s descent: at first she fed her story into AI for a grammar check, it suggested line edits and she accepted, then it asked if she wanted structural edits, then it offered to rewrite the entire piece.

The other would-be author admitted he had never written a short story before and he had an idea but didn’t know where to start. I asked him why he didn’t reach out to me for help. He shrugged.

One of the other students raised her hand, saying she didn’t understand why it was bad for AI to write stories as long as the stories are based on their ideas. More students spoke: one wanted to know how using AI was any different from using a human editor. Another wanted me to answer why, at a university that launched one of the world’s first AI research programs in 1959, were we even having this debate? Isn’t AI meant to make everyone’s life easier? Less stressful? Isn’t the point of AI to free humans from the tedium of rote tasks?

The conversation that followed their confessions was one of the most productive teaching moments of my eight years at MIT. Writing, I told them, isn’t supposed to be easy, and of course it can be tedious but that doesn’t make it rote. Writing isn’t just the production of sentences – it’s the training of endurance by way of sustained attention. It’s a way of learning what one thinks by attempting to say it.

This $10K AI School Promises to Future-Proof Your Career — from builtin.com by Matthew Urwin
Khan Academy, TED and ETS are starting a new program to equip students and professionals with the skills to thrive in an increasingly AI-driven economy. Here’s what you need to know.

Summary: The Khan TED Institute is a higher-education program that will teach students and workers how to use AI through interactive learning. The program’s AI-centric curriculum is an unproven approach, though, casting doubt on whether it will actually improve learning outcomes and career prospects.

When anyone can build a course, the real job is deciding which ones shouldn’t exist [Hardman]

On 05/11/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, business, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, innovation, instructional design, intelligent systems, learning ecosystem, Learning Experience Design, training / L&D, trends, UK, by Daniel Christian

When anyone can build a course, the real job is deciding which ones shouldn’t exist — from drphilippahardman.substack.com by Dr. Philippa Hardman
Why deciding is the only L&D skill AI can’t replace.

The biggest AI risk that L&D faces isn’t that it gets left behind: it’s that we build more — and flood the organisation with meh-quality content nobody needed in the first place.

In this post, I’ll make the case that:

The L&D job has just split in two — and most of us are still working on the wrong half.
There’s a new operating model coming for the role, and it’s already running inside a lot of the companies you’ve heard of.
The smartest critique of everything I’m about to argue comes from Ethan Mollick — and I think he’s half right.

The question we’ve been asking for the last two years — “how do I get faster at building?” — was the wrong one.

The real question is: can I look at fifteen AI-generated learning assets and decide which three are worth scaling — and put my name to that decision?

Dr. Hardman’s post on LinkedIn
and/or
See Dr. Hardman’s post on substack.com entitled:

The Illusion AI Productivity Gains
Why your AI tools aren’t delivering the ROI you were promised — and what to do about it

The TalentLMS 2026 Annual L&D Benchmark Report — from talentlms.com
From year-over-year training benchmarks to learner–leader gaps, see the data that defines the new era of learning. To turn insight into action, the report lays out 10 evidence-backed interventions to hardwire development. Plus, lift the lid on Learning Debt: What it is and how to spot it.

Executive summary
The skills economy is being rewritten in real time. AI is reshaping what people need to know, do, and deliver, faster than organizational structures can adapt. The result is a workplace caught between acceleration and inertia. Companies are racing to reskill for an AI-driven future while relying on structures built for yesterday’s world.

This TalentLMS 2026 L&D Benchmark Report captures that inflection point. Based on data collected through 2025, and compared with earlier findings from 2022 to 2024, it explores how learning is evolving and what’s holding it back.

Our research integrates two vantage points: HR leaders overseeing learning initiatives and employees receiving formal training. Together, they offer a dual perspective on how learning is managed and how it’s experienced.

The analysis also draws on insights from external research and leading L&D practitioners, anchoring the report in both evidence and practice.

Combined, the findings point to a structural fault line: Learning is expanding in scope but contracting in space. Organizations are multiplying programs, tools, and ambitions, yet the conditions for learning — time, focus, and cognitive bandwidth — keep shrinking.

The data from this report underscores this critical conflict: According to half of the surveyed employees and learning leaders, high workloads leave little room for training, even when it’s needed.

Employees work inside a permanent sprint, where attention is fragmented and reflection is sidelined. The space for learning is collapsing under the weight of doing. Sixty-five percent of employees say performance expectations have risen this year, yet lack of time remains the biggest barrier to learning.

The numbers confirm what employees and learning leaders both feel: Technology can advance overnight. But people and cultures can’t.

Which Jobs Are Most at Risk From AI? New Anthropic Data Offers Clues. — from builtin.com by Matthew Urwin
Anthropic set out in its latest study to predict how artificial intelligence could impact the labor market. Instead, its findings raise more questions than answers for tech workers as the U.S. government refuses to regulate the AI industry.

Summary:
In its latest labor market study, Anthropic found that artificial intelligence poses the greatest threat to software jobs, women and younger professionals. As the Trump administration takes a hands-off approach to AI, tech workers may be left to grapple with these findings on their own.

Matthew links to:

Labor market impacts of AI: A new measure and early evidence — from anthropic.com

Key findings

We introduce a new measure of AI displacement risk, observed exposure, that combines theoretical LLM capability and real-world usage data, weighting automated (rather than augmentative) and work-related uses more heavily
AI is far from reaching its theoretical capability: actual coverage remains a fraction of what’s feasible
Occupations with higher observed exposure are projected by the BLS to grow less through 2034
Workers in the most exposed professions are more likely to be older, female, more educated, and higher-paid
We find no systematic increase in unemployment for highly exposed workers since late 2022, though we find suggestive evidence that hiring of younger workers has slowed in exposed occupations

The Course Is Dying as the Unit of Learning. Here’s why, and what’s replacing It [Hardman]

On 04/07/2026, in adult learning, corporate / business world, corporate universities / corporate training, emerging technologies, ideas, instructional design, intelligent systems, learning, learning agents, learning ecosystem, Learning Experience Design, productivity / tips and tricks, training / L&D, UK, workplace, by Daniel Christian

The Course Is Dying as the Unit of Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Here’s why, and what’s replacing It

What the Bleeding Edge Looks like in Practice
So what does “the new stack” actually look like when organisations lean into this? Here are four real patterns already in play.

Engineering: from engine courses to in-workflow AI coaching.
Product development: from courses to craft-specific agents.
Compliance: from annual course to nudge systems.|
Enablement systems, not catalogues.

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“Agentic AI isn’t coming for training programs. It’s coming for the trainers who can’t adapt.” [Martin] + other items re: AI in our learning ecosystems

On 03/23/2026, in Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, ethics, experimentation, future, game-changing environment, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, morals/values, platforms, productivity / tips and tricks, tools, training / L&D, UK, universities, vendors, workplace, by Daniel Christian

Here is Chris Martin’s posting on LinkedIn.com:

Here is Dominik Mate Kovacs’ posting on LinkedIn.com:

The AI ‘hivemind’: Why so many student essays sound alike — from hechingerreport.org by Jill Barshay
A study of more than 70 large language models found similar answers to brainstorming and creative writing prompts

The answers were frequently indistinguishable across different models by different companies that have different architectures and use different training data. The metaphors, imagery, word choices, sentence structures — even punctuation — often converged. Jiang’s team called this phenomenon “inter-model homogeneity” and quantified the overlaps and similarities. To drive the point home, Jiang titled her paper, the “Artificial Hivemind.” The study won a best paper award at the annual conference on Neural Information Processing Systems in December 2025, one of the premier gatherings for AI research.

AI Has No Moral Compass. Do You? — from michelleweise.substack.com by Michelle Weise & Dana Walsh
Why the Age of AI Demands We Take Character Formation Seriously

Here’s something to chew on:

Anthropic, the company behind Claude — a chatbot used by 30 million users per month — has exactly one person (whom we know of) working on AI ethics. One. A young Scottish philosopher is doing the vital work of training a large language model to discern right from wrong.

I don’t say this to shame Anthropic. In fact, Anthropic appears to be the only company (that we know of) being explicit about the moral foundations and reasoning of its chatbot. Hundreds of millions of users worldwide are leveraging tools from other LLMs that do not appear to have an explicit moral compass being cultivated from within.

I raise this because this is yet another example of where we are: extraordinary technical power advancing without an equally strong moral infrastructure to support it.

Why do we keep producing people who are skilled but not wise?

Check out some of the features an AI-powered LMS provides you with!

On 03/23/2026, in 21st century, 24x7x365 access, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, assessment, business, career development, cloud-based computing / apps / other cloud-related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, educational games / serious games, emerging technologies, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, languages and translation, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, platforms, skills, training / L&D, United States, workplace, by Daniel Christian

Here is Pradnya’s posting out on LinkedIn.com:

From DSC…note these excerpts from Pradnya’s posting:

I’m not manually assigning 400 people anymore ? They’re actually taking relevant courses now
Shows me the data ? Suggests courses to fix it ? I look like a strategic genius
Completion rates up 34% ? Nobody’s “stuck” anymore

Pradnya links to a page out at ParadisoSolutions.com. Check out some of the functionality this AI-powered system provides:

Also from Pradnya, see this posting:

How to Get Consistent, On-Brand Course Images from Any AI Image Tool — from drphilippahardman.substack.com by Dr. Philippa Hardman
A 3-step workflow that works every time — whatever AI tool you’re using

Most designers try to describe their way to an image. That’s the wrong approach. The goal is to show the tool the world it should be working in, then give it the minimum it needs to place your subject inside that world.

Every long, over-specified prompt is a sign that your visual inputs aren’t doing enough work.

The fix is an 3-step process which gives you superpowers in AI image generation…

How AI Could Transform, or Replace, the LMS — from futureupodcast.com by Jeff Selingo, Michael Horn, and Matthew Pittinsky

Tuesday, March 10, 2026 – For 30 years now, colleges have relied on the Learning Management System, or LMS, as a key portal for professors and students to teach and learn. It’s a tool that has helped colleges adapt to online learning and bring digital tools to classroom teaching. But generative AI seems poised to disrupt the LMS. And it’s unclear whether the LMS will evolve—or be replaced altogether. For this episode, Jeff and Michael talk with a pioneer of the technology, Matthew Pittinsky, about the lessons of past moments of tech disruption like the smartphone and cloud computing and about what could be different this time. This episode is made with support from Ascendium Education Group.

Gemini, Explained — from wondertools.substack.com by Jeremy Caplan
5 features worth your time — tested and compared

Google’s AI, Gemini, has quickly become one of the AI tools I rely on most. It builds dashboards and creates remarkable infographics. It spins out comprehensive research reports in minutes that would once have taken days to assemble.

It’s improving every month. On March 13, Google announced Ask Maps, so you can query Gemini about things like “Which nearby tennis courts are open with lights so I can play tonight?” On March 10, Gemini added new integrations to build, summarize, and analyze your Google Docs, Sheets, and Slides.

In today’s post below: catch up on the Gemini features worth your time, candid comparisons with other AI tools, and answers to the questions I hear most.

How we’re reimagining Maps with Gemini — from blog.google
Ask Maps answers your real-world questions with a conversation, and Immersive Navigation makes your route more intuitive.

Today, Google Maps is fundamentally changing what a map can do. By bringing together the world’s freshest map with our most capable Gemini models, we’re transforming exploration into a simple conversation and making driving more intuitive than ever with our biggest navigation upgrade in over a decade.

Ask anything about any place
We’re introducing Ask Maps, a new conversational experience that answers complex, real-world questions a map could never answer before. Now you can ask for things like, “My phone is dying — where can I charge it without having to wait in a long line for coffee?” or “Is there a public tennis court with lights on that I can play at tonight?” Previously, finding this information meant lots of research and sifting through reviews. But now, you can just tap the “Ask Maps” button and get your questions answered conversationally, with a customized map to help you visualize your options.

The Future of Learning Looks Like Workforce Infrastructure — from workshift.org by Bruno V. Manno

For years, “ed tech” was an umbrella term grouping schools, online platforms, courses, credentials, and software under one idea: technology applied to education. That shorthand made it easier for investors, policymakers, and institutions to talk about innovation without rethinking how learning fits into the economy. Today, it no longer explains what’s happening.

That’s the central insight of “The European Learning & Work Funding Report” by Brighteye Ventures, a research and advisory firm tracking investment at the intersection of learning, work, and productivity. The report’s seventh edition shows that learning is no longer funded primarily as education. It is increasingly funded as part of how work gets done.

Across Europe, and increasingly the U.S., capital is flowing not toward courses or credentials but toward systems that are closer to production, including hiring platforms, staffing firms, clinical decision tools, payroll systems, and compliance software. These are not educational products, though learning is embedded throughout them.

In these systems, learning is not the point. Outcomes are.

Build hybrid institutions that erase boundaries. Stop forcing learners to navigate disconnected systems. Create partnerships that blend K-12 schools, community colleges, training providers, and employers into one integrated system, so students move through one coherent system, not four separate bureaucracies.

Learning Ecosystems

The Course Is Dying as the Unit of Learning. Here’s why, and what’s replacing It [Hardman]

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