Researchers hid a prompt injection inside a PNG, and AI fell for it — from digitaltrends.com by Shimul Sood

A team of security researchers (professor Sudipta Chattopadhyay and researcher Murali Ediga) has demonstrated an unusual attack that doesn’t target the AI model directly. Instead, it targets what the AI doesn’t pay enough attention to during code reviews. Rather than hiding malicious instructions in lines of code, the researchers tucked them inside an image file. Since many AI review tools treat images as decorative assets rather than as something worth inspecting, the pull request can appear perfectly harmless and sail through the review.

They argue that AI review tools need to become “multimodal” in the truest sense — treating images, documentation, configuration files, and other non-code assets with the same level of scrutiny as source code. If an AI can read a picture, it also needs to understand that the picture could be trying to manipulate it. For developers, this is another reminder that AI coding tools still need supervision. They can dramatically speed up software development, but they also open entirely new attack surfaces that didn’t exist before. The next security risk might not be hidden in thousands of lines of code — it could be sitting inside an image that nobody thought was worth opening.


AI has already fallen into the wrong hands and they’re using it to make bombs — from digitaltrends.com by Shimul Sood

Artificial intelligence has quickly become the go-to tool for everything from writing emails and summarizing meetings to helping students study or developers debug code. But the same technology that saves people time can also be misused, and a new report suggests that terrorist organizations are finding ways to do exactly that.

According to a research paper shared with The New York Times ahead of its publication, researchers found evidence that members of Boko Haram have been using popular AI chatbots to support both day-to-day activities and combat-related tasks. Interviews with 27 former members conducted in Nigeria over the past two years suggest that tools such as ChatGPT, Gemini, Claude, Grok, Meta AI, and DeepSeek were used to gather technical information, troubleshoot weapons, and even assist with planning attacks.

This wasn’t just a few bad actors messing around
What makes the findings especially concerning is that this wasn’t described as the work of a few individuals experimenting with AI. The report claims the group’s use of AI had become organized, with dedicated teams, internal training, and knowledge shared between members. Researchers also say some users managed to bypass built-in safety protections designed to prevent AI from responding to requests related to violence.

 

Microsoft Discovery Platform Brings Agentic AI to Scientific Research — from campustechnology.com by Chris Paoli

Key Takeaways

  • Microsoft Discovery reaches general availability, bringing agentic AI to scientific research and development workflows.
  • AI agents support hypothesis generation, experimentation, data analysis, and knowledge management at scale.
  • New Discovery app preview enables researchers to explore AI-driven scientific discovery with lower adoption barriers.
 

“Teachers ban it. Employers demand it.”

 


Also relevant/see:


The Shifting Career Ladder — from nafez.substack.com by Nafez Dakkak
AI is changing how work works and quietly removing the pathways through which young people learn to become experts.

AI is reshaping how people build skills, enter professions, and move along the career ladder and through the labour market.

In this conversation, I sit down with Matt Sigelmen founder of LightCast and now the President of Burning Glass Institute. Matt has dedicated his career to understanding the labor market and helping society improve the connections within in it.

Matt and I explore why people and opportunities are often only “a few skills apart,” why entry-level work may be losing its traditional role as the first rung of expertise, and why schools, universities, and employers now need to rethink the pathways that turn potential into mastery.

Educators need to be deeply aligned with what these changes are, and they need to shift the AI discourse from “how” questions to “what” questions. What do we need to teach? What do we need to keep in the curriculum?

 

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.

 

A Comprehensive Report on Teens, Tweens, and AI — from commonsensemedia.org

To find out what that actually looks like day-to-day, we surveyed more than a thousand 9- to 17-year-olds across the country. We asked them how they use AI, how often, and for what.

The Common Sense Media Census: AI Use by Tweens and Teens (2026) is the first in a series we’ll repeat every year to learn how this generation’s relationship with AI evolves over time.

A few things stood out:

  • Kids are using AI for many things. It’s not just a homework helper anymore. For some kids, AI has become a confidant, even though our research is clear that AI companionship is not safe for anyone under 18.
  • Guardrails are thin to nonexistent. Schools are talking about rules more than safety. Three-quarters of kids say their school has discussed what they can and cannot use AI for, but just over half have been taught how to use AI safely.
  • Just like we saw with smartphones and social media, the conversation is once again lagging behind the technology. Nearly half of kids have never had a conversation with their parents about AI safety.
 

Instructional Design Trends: What’s Shaping The Future Of Learning? — from elearningindustry.com by Christopher Pappas

Table of contents

1. Why Instructional Design Is Entering A New Era
2. The State Of Instructional Design Today
3. Top Instructional Design Trends Shaping 2026
4. The Future Of Instructional Design And Technology


Also from elearningindustry.com, see:

The Future Of Personalized Learning And The Leaders Being Trained To Deliver It — by Ryan Ayers

Table of contents

1. Personalized Learning For Future Leaders
2. Where Personalized Learning Is Heading
3. What Implementing Personalized Learning At Scale Actually Requires
4. The Educational Leaders Being Trained To Deliver This Future
5. Conclusion

 

NotebookLM’s 60-second videos turned my doomscrolling curse into something useful — from digitaltrends.com by Shimul Sood

Google has announced Short Video Overviews for NotebookLM, a feature that turns dense documents and complicated sources into 60-second vertical videos that explain key ideas. Instead of staring at pages of notes, you get a quick visual walkthrough of the concept you’re trying to understand.


 

Stanford Online Launches Immersive Learning Studio — from campustechnology.com by Matt Jones

Key Takeaways

  • Stanford Online celebrated its 30th anniversary by launching a new immersive learning studio that combines VR, AR, and AI technologies to create more engaging and personalized educational experiences.
  • The studio provides faculty with advanced production tools — including a 4K LED wall, cinematic cameras, AI-enabled workflows, and extensive editing and storage infrastructure — to develop innovative learning content at scale.
  • University leaders see the studio as a major step toward expanding faculty-led, research-based education globally, leveraging AI and immersive technologies to reach learners in ways previously not possible.
 

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.

 

From DSC:
I used to be able to bring up Firefly on the web and use it “free” of charge — I didn’t have to go purchase tokens or credits. (I was actually paying for the Adobe Creative Cloud Pro suite of tools…so it wasn’t really free.)

But the other day I was trying to figure out what the latest pricing is at Adobe with that suite of tools and the use of credits for AI-based features. They say Adobe Creative Cloud Pro users get 4000 credits a month. Well, I have that suite and I’m still getting prompted to purchase credits. Firefly for individuals runs from $9.99 (2,000 credits/month) to $139.91 per month (50,000 credits per month). Not inexpensive, right? Below are other items along these lines.


The Era of Affordable AI Is Over. What Comes Next? — from builtin.com by Ameya Kanitkar
AI providers are shifting to usage-based billing for their services. AI fluency is more important now than ever to make the most of your tools to avoid unnecessary spending.

Summary: The era of cheap, flat-rate AI is ending as providers shift to usage-based billing. Every prompt now carries a direct cost, turning casual use into major budget risks, as seen when Uber depleted its 2026 AI budget in four months. Leaders must now track real-time value and token efficiency.

For a brief window, companies had access to the most transformative technology in a generation at the cost of a streaming subscription. Tools like ChatGPT put AI within reach of anyone with a browser and time for experimentation, while GitHub Copilot came in at just $10 a month, with token costs remaining relatively low. In the beginning, experimentation felt cost-effective, easy and relatively low-risk. 

But that era is ending, and the bill is coming due faster than a lot of enterprise leaders anticipated. 


The Fable of AI in Education — from downes.ca by Stephen Downes
Marc Watkins, Rhetorica, Jun 17, 2026

Tokenomics will be a hot topic of discussion on university campuses because, as Marc Watkins notes in this article, there is no realistic path forward to providing all students with access to advanced AI.


From this posting on LinkedIn.com from Dr. Nick Jackson:

And now there is a third layer emerging. Institutions are waking up to a systems-level question they are likely not remotely prepared for. Who pays for AI? How are budgets managed when there are unclear token consumption pricing models? How is AI procured? Who decides what tools get used and by whom and who gets access and at what level?

.


 

From DSC:
Following are several companies that are using AI to connect people to work. That’s a significant piece of my Learning from the Living [AI-Based Class] Room vision.

These companies were listed on an article entitled,
Can AI be an effective career coach?
— from achievepartners.com and Ryan Craig


FutureFit AI
Bridge the gap between talent, training, and employment at scale

AI-powered workforce technology connecting people to careers, employers to talent, and workforce partners to tools for integrated and intelligent workforce systems.

PathPilot AI

Empowering every job seeker with personalized AI coaching. Helping organizations scale career services and improve outcomes.

Empower Students with Career-Ready Skills
Help students discover career pathways, develop essential skills, and connect with opportunities. PathPilot provides personalized guidance that scales across your entire institution.

  • AI-powered career exploration and pathway planning
  • Skills assessment aligned with NACE competencies
  • Resume builder and interview preparation tools
  • Job matching with local and national employers
  • Institutional analytics and outcome tracking
  • Integration with existing career services systems

Pathific — Design your future
The all-in-one platform that connects your strengths to programs, careers, and real salary outcomes — powered by AI.

High school, post-secondary, newcomer to Canada, or career change — Pathific meets you where you are.

Your all-in-one career compass
Quality career guidance shouldn’t depend on where you go to school, when you start your journey, or where you come from. Using the latest AI and comprehensive Canadian data, we built a platform that gives everyone clear, data-driven pathways to their future. No more one-size-fits-all advice. No more guessing. Just your strengths, connected to real data.

OpportuNext

See Where Your Skills Can Take You | Find new career path opportunities with one simple search.

OpportuNext from Signal49 Research is a free-to-use career tool created in partnership with the Future Skills Centre. Using big data, it matches a person’s skills with viable career paths — often including some you have not considered.

 

Two years ago, AI broke assessment. Now, it’s helping us to reinvent it. — from linkedin.com by Dr. Philippa Hardman


Also from Dr. Hardman, see:


A new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how. — from linkedin.com by Dr. Philippa Hardman

…a new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how.

Google DeepMind just shared the results of a randomised trial involving 1,763 students. Half used Gemini’s “Guided Learning” to learn maths; half didn’t.

The result: the group working with AI gained the equivalent of 1.2 to 1.7 years of extra progress compared to those who didn’t.

It’s tempting to read this as “Gemini’s Guided Learning mode works!” But the key point here is that Gemini didn’t work alone….

Look closer, and what made the difference wasn’t just the tech — it was a great teacher making expert use of it.

 
 

Why Students Aren’t All In on AI—And What They Want From Colleges — from insidehighered.com by  Colleen Flaherty
New Student Voice data reveal students are embracing AI as a learning tool while worrying about dependence, career disruption and inconsistent institutional responses.

Read on for six takeaways from the survey and additional insights—including how institutions can start to close the gap between students’ optimism about AI as a learning tool and their faith in their colleges’ ability to help them navigate change.

Takeaway 1: More students are using AI than ever for coursework, while a significant share—20 percent—remain resisters.

Takeaway 2: “Worried about dependence” is the most common student stance on AI.

Takeaway 3: A majority of all students expect AI to somewhat (39 percent) or very (16 percent) negatively impact their career prospects.

Takeaway 4: Just one in 10 students says that their institution is handling AI’s rise very well, in a thoughtful and proactive way.

…and more >>

 

 


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?


 
© 2025 | Daniel Christian