generational differences

New tests show that AI can design like an expert Instructional Designer: so what next? [Hardman]

On 10/16/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, tools, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

Here is Phillipa’s posting on LinkedIn.

The Age of Perpetual Change — from educause.edu
Artificial intelligence (AI) has risen to the number one spot on the 2027 EDUCAUSE Top 10. But its rank signals urgency more than consensus, and higher education is still grappling with what AI-driven change could mean for institutions. In many ways, AI embodies a broader reality: We’re living in an age of perpetual change.

2027 Top 10 Overview
Technological innovation is outpacing our ability to manage and harness it. The political and economic winds around us are erratic. And higher education itself is undergoing profound shifts that will reshape how our institutions function.

While this atmosphere breeds uncertainty and anxiety, it can also inspire innovation and growth. The 2027 EDUCAUSE Top 10 highlights how the higher education technology community is responding to those opportunities.

New study: 15 community college presidents on what it will take to lead higher ed’s next chapter [eddesignlab.org]

On 09/19/2026, in career development, change, changing business models, community colleges, competency-based learning/education, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, skills, student-related, teaching & learning, United States, workplace, by Daniel Christian

New study: 15 community college presidents on what it will take to lead higher ed’s next chapter — from eddesignlab.org

Community colleges are at a pivotal moment.

As learners, employers, and regional economies change, these institutions have an opportunity to lead the next evolution of higher education — if they can move beyond structures built for a different era.

In the Lab’s new study, Insights from 15 Community College Presidents on the Future of Learning in a New Economy, leaders share their perspectives on the opportunities and barriers facing the sector, as well as the institutional changes needed to help more learners access economic mobility.

Their insights validate Education Design Lab’s Future of Learning framework, which asks five essential design questions:

How might we make skills and competencies visible?
How might we create stackable pathways that credential skills along the way?
How might we make learning universally flexible through multiple modalities?
How might we guarantee applied learning opportunities for every learner?
How might we ensure every learner has access to adequate support services?

Per Anthropic’s CEO: “We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.”

On 09/14/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, change, communities of practice, dangers of the status quo, future, game-changing environment, generational differences, global, legislatures / government / legal, pace of change, society, technology (general), the downsides of how people use tech, trends, vendors, vision/possibilities, by Daniel Christian

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.

Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our…

— Dario Amodei (@DarioAmodei) September 12, 2026

Dario Amodei’s article here:
We Must Pace the Frontier — from darioamodei.com

But like many technologies before it, AI brings risks, and because it is such a powerful technology, these risks are serious. I’ve written a lot about them too. They include the risk of losing control of AI systems, misuse of AI for cyberattacks and bioterrorism, and serious economic disruption. A race to the bottom, spurred by commercial incentives, can make these risks more acute.

Along with my co-founders and employees, I have grappled with this duality of risk and benefit since the beginning of Anthropic.

Also relevant/see:

I left Anthropic’s safety team two weeks ago. Now feels like a good moment to explain why.

AI companies are racing to build machines that are much smarter than any human, and we may not survive this. I want to work from the outside to ensure the public is informed about these…

— Joe Benton (@JoeJBenton) September 11, 2026

[GIFTED ARTICLE]
Anthropic CEO calls for the AI industry to slow down — from washingtonpost.com by Ted Hesson, Ian Duncan, and Gerrit De Vynck
Anthropic CEO Dario Amodei said he was worried about the ability to control self-improving AI models.

Three of the nation’s leading artificial intelligence executives endorsed slowing down the blistering pace of technological advancement, revealing the growing unease with its potential dangers at the industry’s very highest levels.

The call was first made in an essay Anthropic chief executive Dario Amodei posted online Saturday. The idea has gained ground in recent weeks as AI companies have struggled in some cases to keep their creations under control, even as they usher in an age in which AI systems themselves can build the more powerful next generation of the technology.

[GIFTED ARTICLE]
For years, they warned AI could kill all humans. Now people are listening. — from washingtonpost.com by Nitasha Tiku
A doomsaying community once on the periphery of the tech industry has gained influence, as AI “agents” perform amazing and alarming feats.

But when Hubinger issued a similar warning this week in a post on X, his message was viewed tens of millions of times, prompting state and federal lawmakers to echo his concern. Now he spoke as a team lead at Anthropic, developer of the chatbot Claude and a company set to go public at a valuation of over $1 trillion.

“AI could kill all humans … I personally think it is >10% within the next decade,” Hubinger wrote, in response to the resignation of his colleague Jacob Coxon, who accused Anthropic of racing ahead despite the dangers.
.

Several items re: the changes needed within higher education

On 09/14/2026, in 21st century, adjunct faculty, business side of he, career development, change, changing business models, collaboration, colleges, communities of practice, community colleges, corporate / business world, cost of getting a degree, culture, dangers of the status quo, entrepreneurship, expectations, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, leadership, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, new business models, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, traditional / tradition, United States, universities, youth, by Daniel Christian

Below are several items that were either mentioned by Matt Tower or I came across them via offshoots of items that he linked to:

Future Universities Alliance Names Inaugural Innovation Sandbox Cohort — from provost.duke.edu
Program incubated by Duke brings together higher education innovators from 23 countries for year-long peer exchange

The Future Universities Alliance has selected 49 institutions from 23 countries for the inaugural cohort of its Innovation Sandbox, a 12-month peer learning program for higher education leaders advancing ambitious, institution-level innovation.The cohort brings together founders of new universities, administrators and faculty leading high-stakes changes within established institutions, and leaders of proven models exploring how their innovations can travel to new contexts. Participants were chosen through a competitive process that drew applicants from around the world in its inaugural year.

A makeover for college: No gym, no meal plan and two years of work — from npr.org by Jon Marcus

An entirely new college is being planned here to change not only how higher education is delivered, but at what price. It also proposes to highlight ways the current business model no longer works, as evidenced by the 152 colleges and universities that have closed or merged since 2016, and the 442 others that a new projection says are at risk.

So deeply entrenched are the problems confronting higher education that a growing chorus of innovators says the easiest way to fix them is to begin again from scratch.

All undergraduates should get work-based learning, v-cs say — from timeshighereducation.com by Jack Grove. NOTE: this item is behind a paywall.
Bold plan to support graduate employment would require placements for 1.4 million students annually

‘You can’t just lecture students any more’ — from timeshighereducation.com by Debra Page
GenAI does not make lecturers redundant, but it does weaken one-way content delivery as a reason to bring students together, writes Debra Page. She shares four practical shifts to teaching in the age of AI

This does not make lecturers redundant; it makes one-way content delivery a weaker reason to bring students together. Expert explanation, intellectual storytelling and the modelling of disciplinary thinking still matter, but in-person teaching must also help students apply knowledge, question claims, build arguments and encounter perspectives beyond their own.

The problem is not lecturing; it is speaking for an hour and treating content coverage as evidence that learning has occurred.

These four practical shifts can make lectures more valuable in the age of AI.

OpenAI’s chief scientist says no lab should keep scaling at maximum speed [Constantin]

On 09/10/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, experimentation, game-changing environment, generational differences, global, legislatures / government / legal, Open AI, platforms, policy, political science, the downsides of how people use tech, United States, by Daniel Christian

OpenAI’s chief scientist says no lab should keep scaling at maximum speed — from thenextweb.com by Ana Maria Constantin
OpenAI put out two posts on Sunday. Its research organisation now uses 3.1 agent-workdays for every human one, and its chief scientist says no lab has solved alignment well enough to keep scaling at full speed. The case for an OpenAI slowdown arrived with the numbers against it.

Chief scientist Jakub Pachocki wrote the second post, an essay called An Alien Mind. It closes on a line that reads oddly from the man who runs research at the company shipping fastest.

“Currently I believe that no lab has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed for much longer,” he wrote.

…
He is not gentle about the stakes either. “This is a time that calls for extreme caution. I am concerned no one is prepared for the consequences of a continued rapid rise in machine intelligence,” Pachocki wrote.

We are at a tipping point. In the next 25 years, technologies like AI, clean energy, and bioengineering are poised to reshape society on a scale few can imagine.

Peter Leyden draws on decades of observing technological revolutions and historical patterns to show how old systems collapse, new ones rise, and humanity faces both extraordinary risk and unprecedented opportunity.

0:00 We’re on the cusp of an era of progress
0:37 The Great Progression
1:08 What was the ‘Long Boom?’
4:56 How often do these epoch resets happen?
6:12 3 Tipping points
6:39 Artificial Intelligence
7:13 Clean energy technologies
7:32 Biotechnology
9:00 The 80-year cycle
13:27 The Gilded Age
17:50 The Founding Era
22:46 The new enlightenment
32:18 The clean energy revolution
37:13 Bioengineering the genome
39:43 Industrial production vs biological engineering
47:40 What will the future think?

Will this new company be the largest company on the Internet by 2030? [Christian]

On 08/01/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), career development, cloud-based computing / apps / other cloud-related, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, credentialing, curriculum, Daniel S. Christian, digital learning, disruption, education, education technology, elearning, emerging technologies, engagement / engaging students, future, future of higher education, game-changing environment, generational differences, global, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, internet, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, lifelong learning, love of learning, more voice more choice more control, motivation, online learning, online media, online tutoring, pathways, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, society, staying relevant, student-related, teachers, teaching & learning, training / L&D, United States, vision/possibilities, web-based collaboration, youth, by Daniel Christian

From DSC:
The vision that I’ve been tracking for well over a decade begins with this graphic:
.

Could LearnVector be this next-generation company/platform? Perhaps. Time will tell.

Per Matt Tower via The EdSheet Vol. 38 dated 7/31/26:

Coursera bets $100M on its own co-founder: Andrew Ng’s new venture LearnVector lands one of the largest single checks in edtech this year — from Coursera, the company he founded 14 years ago.
.

LearnVector.ai

From DSC:
Below is an item on futures thinking. Don’t blow this off. This topic — and skill/strategy — is important not only to traditional institutions of higher education, but also to businesses and organizations of all sizes. In fact, even students can practice developing a list of potential scenarios and implement their plans of action if one of those scenarios occurs.

Chris Mayer’s posting on LinkedIn.com

The AI-native university, AI literacy, AI and accessibility + other items re: AI in our learning ecosystems

On 07/22/2026, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, data related items, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, personalized/customized learning, productivity / tips and tricks, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, by Daniel Christian

AI & Accessibility: 5 Practical Ways to Use LLMs to Support Inclusive Learning — from learningguild.com by Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)

The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.
…
Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.

Instructional designers can integrate AI copilots, LLM-powered conversational interfaces, into learning environments to provide on-demand clarification. These tools can act as digital coaches, helping learners understand concepts through simplified explanations and relevant examples.

This approach supports learners who benefit from additional processing time and personalized guidance.

Sample Prompt (for IDs Configuring Copilot Behavior)
You are a workplace learning coach.

Explain the following concept in a clear, simple way:

- Use plain language
- Provide one practical, job-relevant example
- Avoid jargon unless necessary (and define it if used)

Then ask one follow-up question to check for understanding.

Jeff’s posting on LinkedIn.

Teaching AI Literacy with Susan Ray — from intentionalteaching.buzzsprout.com by Derek Bruff and Susan Ray

Per Derek Bruff:
In my conversation with Susan, we talk about that syllabus activity, as well as the AI transparency journals she asks her students to keep during her courses. We also talk about how her personal background prepared her to navigate the challenges and opportunities that AI has posed to her teaching, how she approaches assessing student learning in this age of AI—especially in her online asynchronous courses—and much more.

Building the AI-Native University: Student Success and Lifelong Learning — from coursera.org

In this episode, you’ll discover:

Why building an AI-native campus requires a data-first foundation
How to build an “achievement architecture” for lifelong success
How faculty-built AI tutors cut one program’s course attrition from 40% to 10%
What it means to be a lifelong learning companion

We’re Raising the First AI Generation. They’re Pushing Back. (Rebecca Winthrop, Brookings) — from humanistxyz.substack.com by Allison Dulin Salisbury
“Young people harbor real anger about AI because they’re already experiencing its consequences in their schools, relationships, job prospects, and feeds.”

As Rebecca told me:

“Kids harbor real anger. They’re pissed about climate impacts. They’re upset about job prospects. They’re outraged about AI being used to plagiarize writing and produce counterfeit artwork. Their relationships are being affected, and they’re seeing deepfakes in their feeds.”

Our conversation explores what follows from taking those concerns seriously. We discuss cognitive stunting, the case for small, purpose-built AI models over frontier models in education, why students should spend far more time in explorer mode, and how schools can cultivate agency, curiosity, and independent thinking in an age of AI.

The interview ends with one of Rebecca’s most practical recommendations: every school should have a student AI council, not as a symbolic gesture, but with real influence over the tools their schools adopt, the ways they’re used, and the data students are asked to hand over.

Every generation of technology seems to relearn the same lesson: build with people, not for them. AI should be no exception.

The Law School Deans Driving AI Innovation in Legal Education — from natlawreview.com by Shivani Vedhere, AI & the Law Newsletter; via Colin S. Levy

Artificial intelligence is no longer a peripheral issue for legal education. It is quickly becoming one of the central questions facing law schools: how to prepare future lawyers for a profession in which AI will affect research, client counseling, litigation strategy, access to justice, and the business of law.

For decades, law schools treated legal technology as an elective or a niche interest for students already inclined toward innovation. That era is ending. Law firms are adopting AI tools at scale and even investing in developing their own tools. Clients are asking harder questions about efficiency, cost, and competence. Courts are sanctioning lawyers and litigants for AI-generated hallucinations, with the number of identified cases in the United States now exceeding 1,000. Students entering the profession will be expected to keep up with this rapidly changing landscape.

The most forward-looking law schools are responding accordingly. That transformation is being driven in large part by a group of innovative law school deans who are treating AI not as a passing trend, but as a structural change in legal education.

These initiatives signal a broader shift in legal academia where law schools are no longer merely debating whether AI belongs in the curriculum. The more pressing question is how deeply, how early, and how responsibly AI should be integrated into legal education.

The Current State of Play: AI in Higher Education and the Road Ahead [Gamby, Kil, Koblic, LeBlanc, Moldoveanu & Siemens]

On 06/29/2026, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business side of he, career development, change, colleges, community colleges, corporate / business world, culture, emerging technologies, ethics, expectations, experimentation, faculty/staff, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, intelligent systems, IT in HE, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, liberal arts, morals/values, organizational change, pace of change, parents/guardians, personalized/customized learning, policy, reinvent, relationships, skills, society, strategy, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

The Current State of Play: AI in Higher Education and the Road Ahead — from er.educause.edu by Tanya Gamby, David Kil, Rachel Koblic, Paul LeBlanc, Mihnea Moldoveanu and George Siemens

The conventional explanation for this strategic vacuum points to the speed of technological change; it is moving too fast for institutions built for deliberation. That is true. . . and incomplete. The deeper issue is cultural. In fairness to higher education, many industries are struggling to keep up with the pace of AI advances. Higher education, however, moves even more slowly and is not built for the kind of transformational speed now underway. Getting institutional stakeholders to engage, rethink the work, and move faster may be the central challenge facing presidents and chancellors today, and that’s saying a lot in such volatile times.

From DSC:
I highlighted this paragraph because it hits upon the key item involved here — culture. “The deeper issue is cultural.” I think that’s a very true statement.

Part of the culture and setup of many institutions includes giving faculty members full rein of their classes and their departments. Faculty members have a great deal of leeway and power in how they do things. So trying to get X faculty members to get on board — including the Department Chairs — is not an easy task.

Another part of culture involves being willing — or not — to change in the first place. Some institutions are like Google and are used to making changes and being more innovative. But those institutions are not the norm, at least in my experience. And this doesn’t even address another topic the article mentioned — the pace of these changes. As the authors point out, most institutions of traditional higher education are not equipped to deal with the current pace of change (nor are most of our other types of institutions and our corporations as well).

I’m going to end this posting with another brief excerpt from the article:

Institutions rooted in human relationships, committed to truth-seeking, and oriented toward the full development of persons play a central role. AI cannot manufacture the experience of mattering to another human being. It cannot model intellectual courage or ethical discernment. It cannot build the kind of community in which students discover who they are and what they believe.

These are not small things. They are, in fact, the things most worth doing. At their best, colleges and universities are not only preparing better workers but shaping individuals and strengthening society.

Important insights from this PwC global jobs report — from linkedin.com by Ross Dawson & PwC

Three items re: AI in our LE’s (involving corporate training, higher ed, and K-12)

On 06/10/2026, in 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, attention, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, student-related, teachers, teaching & learning, training / L&D, United States, universities, youth, by Daniel Christian

Rethinking Learning Design in Elementary Schools — from edcircuit.com
Why K–5 leaders must redesign—not just adopt—technology to restore attention, deepen thinking, and align AI with how children actually learn

Rethinking learning design in elementary schools is critical as screen time and AI reshape attention, thinking, and student engagement.

Designing for Thinking, Not Just Doing
At its core, learning design must shift from task completion to thinking development.

This requires creating environments where students:

Spend time processing ideas
Work through confusion without immediate answers
Build persistence through challenge

It also requires clarity around the role of technology.

Technology should:

Extend thinking
Provide meaningful feedback
Support exploration

It should not:

Replace effort
Short-circuit reasoning
Eliminate productive struggle

The goal is not to reduce technology use.

It is to ensure that students remain the ones doing the thinking.

Should We Integrate AI into Our Teaching?: Evidence-Based Guidelines for Deciding When AI Belongs — from Faculty Focus by Norman Eng, EdD

Four Questions for Deciding Whether to Use AI

Question 1: Will this AI tool help students use, recall, and demonstrate understanding of core disciplinary content?
Question 2: Will this AI tool require students to apply their learning to a new context?
Question 3: Will this AI tool support—not replace—independent, evidence-based reasoning?
Question 4: Will this AI integration preserve meaningful human interaction?

Learning Ecosystems

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