emerging technologies

4 Strategies For Teaching With AI Effectively — from techlearning.com by Erik Ofgang
Health sciences professor Humberto López Castillo urges students to use AI to help with science research, but never to lose sight of the human element.

Castillo, a trained pediatrician and professor in the Department of Health Sciences, has also seen students use AI in creative ways to promote public health understanding, and as a research tool. For one project, Castillo asks students to explain health concepts from class to non-experts, and since he started encouraging students to use AI, he’s seen the projects get better. Students have created health-themed board games and Hamilton-style rap songs. Others have designed AI to aid in health research in ways that wouldn’t be possible without the technology.

This compassionate and student-centered approach to AI use is part of why Castillo was named Superhuman (formerly Grammarly’s) 2026 Educator of the Year.
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“You are the one who’s responsible for that writing,” Castillo tells his students. “Your name is the only name that’s going to be among the published authors, so you are the one who needs to verify those sources.”

He adds that rather than being a drawback, allowing students to make these types of mistakes with AI use in the college setting has value.

“It is a teaching opportunity,” Castillo says. “This is the moment to make those mistakes.”

GenAI practice blossoms through the open exchange of insights — from timeshighereducation.com by Samuel Doherty, who is the education and innovation coordinator at the University of Newcastle in Australia
How a structured GenAI professional development series, built around practice, peer voices and multiple entry points, fosters open exchange among colleagues, universities and industry

Connect internal practice to sector-wide thinking
Whatever is happening within any single institution is only part of the picture. Effective GenAI practice grows through open exchange of insights among colleagues, universities, professional bodies and industry, and a development programme that is entirely inward-looking risks missing both useful knowledge and important shifts in expectation.

Our AI sector voices sessions aim to bring external contributors into the programme: researchers, practitioners and sector representatives working at the intersection of GenAI and higher education. The aim is to situate institutional practice within the wider conversation and to signal to staff that the institution is genuinely engaged with that conversation, not just managing it internally.

In the Australian context, the Tertiary Education Quality and Standards Agency (Teqsa) people pillar positions staff as drivers, enablers, users and innovators of GenAI practice, and identifies a lack of information or understanding as one of the primary barriers to ethical and effective engagement. That framing is useful regardless of regulatory context: institutions that treat their people as active participants in shaping practice, rather than recipients of policy, are likely to develop more durable capability.

Regular, lightweight communications, a weekly community of practice update and a monthly all-staff digest can maintain momentum between sessions without adding significantly to anyone’s workload.

Workplace Readiness: Can Higher Education Develop AI-Ready Students? — from learningguild.com by Eddie Lin and Roshan Bharwaney

For higher education to remain relevant, curricula must evolve. Here are some overarching recommendations for directions in higher education to bridge the skills gaps between universities and workplaces:

AI ethics and safety: Prepare students to navigate issues of fairness, bias, privacy, and societal impact.
Tackling complex questions: Emphasize open-ended challenges that blend structured and unstructured skills and reduce reliance on standardized tests and repetitive drills.
Critical thinking: Develop new assessments for judgment, creativity, and metacognition—essential to supervise AI outputs.
Human-AI synergy: Embed AI fluency across all disciplines, encouraging students to find the niches where human value is maximized.
Industry connection: Maintain close industry partnerships and collaborations including open innovation opportunities and collective intelligence approaches (Bharwaney & Sleeva, 2024).

Experiential learning and communities of practice are central to this vision. Internships, simulations, and cross-disciplinary projects can help students practice human-AI collaboration, resilience, and decision-making in environments that mirror the workplace’s ambiguity and complexity.

Universities that condemn the use of AI by students risk isolating themselves from the realities of today’s workplace, where interns and new hires are expected to be or quickly become adept at using AI for routine tasks and complex projects.

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

Global AI Diffusion — Q1 2026 Trends and Insights [Microsoft]

On 05/21/2026, in 21st century, Africa, Artificial Intelligence/Agents/LLMs/and Related, Asia, Australia, Canada, emerging technologies, Europe, game-changing environment, global / globalization, human-computer interaction (HCI), India, innovation, Microsoft, platforms, trends, UK, United States, by Daniel Christian

Global AI Diffusion Q1 2026 Trends and Insights — from Microsoft

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A New Era of Security: Frontier AI Defense — from paloaltonetworks.com by Sam Rubin

For the last several months, we have had early, unbounded access to the latest frontier AI models. What we’ve seen from that vantage point has made it clear that the window for organizations to get ahead of what’s coming is shorter than most leaders realize.

We have moved past the era of incremental AI improvements into a threat landscape shift. Our testing has revealed a step-change in capability that demonstrates an intuitive understanding of software vulnerabilities. This is more than faster code generation, it is a shift from AI as an assistant to AI as an autonomous agent capable of discovering and chaining flaws at a scale that most defenders aren’t prepared for.

These capabilities will not stay confined to controlled environments for long. When Mythos first launched, we predicted a six-month window before attackers gained access. We now believe that timeline has accelerated significantly.

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.

This $10K AI School Promises to Future-Proof Your Career [Urwin]

On 05/12/2026, in 21st century, 24x7x365 access, accessibility / UDL, Alternatives, Artificial Intelligence/Agents/LLMs/and Related, collaboration, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, digital learning, education, education reform, education technology, emerging technologies, entrepreneurship, experimentation, faculty/staff, Google, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, K-12 related, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning spaces, Microsoft, pace of change, platforms, productivity / tips and tricks, real-world assignments, reinvent, skills, staying relevant, student-related, teaching online, United States, universities, vendors, by Daniel Christian

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.

Higher education might be on the verge of a radical overhaul to bring it up to speed in the age of artificial intelligence. At the TED2026 conference, Khan Academy, TED and ETS announced that they’re partnering to establish the Khan TED Institute — a new program that reorients the college curriculum around AI. By joining forces, the education technology trio aims to develop an alternative to traditional universities that better tracks student progress, teaches more relevant skills and provides a more personalized learning experience.

Accessibility is another major tenet of the Khan TED Institute. Its virtual nature allows anyone with an internet connection to participate in the program and makes it easier for students to move at their preferred pace. And because its curriculum prioritizes competency over course credits, advanced learners can complete the program in a shorter period. Time isn’t the only thing students can save on, either: The Institute promises a bachelor’s degree for less than $10,000, offering a much more affordable alternative to the typical four-year degree.

From DSC:
Faculty senates don’t do well with this pace of change. But to their credit, few organizations can begin to deal with this pace of change.

Nvidia gets into #legaltech

On 05/02/2026, in Access to Justice (A2J), Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, Legal operations, legal reform, legal technologies, legislatures / government / legal, NVIDIA, platforms, productivity / tips and tricks, society, tools, vendors, by Daniel Christian

Nvidia just invested in the AI legal startup that’s splashing Jude Law ads everywhere — from cnbc.com by Kai Nicol-Schwarz

Key Points

Nvidia has backed Swedish AI legal tech Legora in a $50 million Series D extension, CNBC can reveal.
The chip giant has been ramping up startup investments in recent years.
Investors have been piling into to promising young AI companies as they bet big on the commercial potential of tech to reshape entire industries and bring big efficiency gains.

Legora is its first bet in the legal tech sector, according to Dealroom data.
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The AI startup is building AI agents and tools to help lawyers automate and streamline workflows.

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.

Why Sal Khan’s AI revolution hasn’t happened yet, according to Sal Khan — from chalkbeat.org by Matt Barnum

Three years ago, as Khan Academy founder Sal Khan rolled out an AI-powered tutoring chatbot, he predicted a revolution in learning.

So far, the revolution hasn’t happened, he acknowledges.

“For a lot of students, it was a non-event,” Khan told me recently about his eponymous chatbot, Khanmigo. “They just didn’t use it much.”

Khan gives this analogy: Imagine he walked into a class, sat in the back of the room, and waited for students to seek out help. “Some will; most won’t,” he said. That’s been the experience with AI tutoring, he said. It doesn’t necessarily make students motivated to learn or fill in gaps in knowledge needed to ask questions.

“AI is going to help,” said Khan of this reimagined Khan Academy. “But I think our biggest lever is really investing in the human systems.”

An Attack on Sam Altman Sends a Terrifying Message [Gifted opinion article by Aaron Zamost]

On 04/27/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, corporate / business world, emerging technologies, ethics, intelligent systems, morals/values, platforms, society, United States, vendors, by Daniel Christian

An Attack on Sam Altman Sends a Terrifying Message — from the nytimes.com; this is a gifted opinion article by Aaron Zamost

Lawless political violence landed on Silicon Valley’s doorstep this month when an attacker hurled a Molotov cocktail at the San Francisco compound of Sam Altman, OpenAI’s chief executive. The incident was a disturbing sign that simmering public anger about A.I. is spilling out of polling data and social media posts and into the real world.

The attack shook many tech employees, who in quiet conversations about safety wondered whether this was a watershed moment for the industry. I believe it should be — the whole thing is disturbing and jarring, but I’m hopeful it will change how some tech leaders deal with the societal consequences of their success.
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If these companies sold food, cars, medicine or any other consumer goods, their products would almost certainly be recalled while federal regulators investigated the allegations.
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You would think an industry creating this kind of outrage would reflect or recalibrate. Business experts teach us that companies facing customer backlash should acknowledge the failure, change their approach and earn back public trust. But the titans of tech no longer seem interested in convincing the public.

The foundation of Silicon Valley’s appeal has always been the implicit promise that great technology serves you, and that the people behind it understand your problems and want to solve them. That promise is starting to feel broken. Fixing it requires something much of Silicon Valley has forgotten how to do: listen and learn.

A Molotov cocktail is the absolute wrong way to send a message to tech. Its leaders need to hear it anyway.

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