trends

Bringing the best of AI to college students for free [Pichai] + plus other items re: AI in our LE’s

On 08/13/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning spaces, liberal arts, library / librarians, lifelong learning, multimedia, online media, online tutoring, personalized/customized learning, platforms, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, by Daniel Christian

Bringing the best of AI to college students for free — from blog.google by Sundar Pichai

Millions of college students around the world are getting ready to start classes. To help make the school year even better, we’re making our most advanced AI tools available to them for free, including our new Guided Learning mode. We’re also providing $1 billion to support AI education and job training programs and research in the U.S. This includes making our AI and career training free for every college student in America through our AI for Education Accelerator — over 100 colleges and universities have already signed up.
…
Guided Learning: from answers to understanding
AI can broaden knowledge and expand access to it in powerful ways, helping anyone, anywhere learn anything in the way that works best for them. It’s not about just getting an answer, but deepening understanding and building critical thinking skills along the way. That opportunity is why we built Guided Learning, a new mode in Gemini that acts as a learning companion guiding you with questions and step-by-step support instead of just giving you the answer. We worked closely with students, educators, researchers and learning experts to make sure it’s helpful for understanding new concepts and is backed by learning science.

Google introduces Guided Learning [Zau] + other items re: AI in our learning ecosystems

On 08/09/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Apple, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, 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, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning spaces, liberal arts, lifelong learning, online tutoring, personalized/customized learning, platforms, productivity / tips and tricks, research, skills, student-related, teachers, teaching & learning, teaching online, tools, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, by Daniel Christian

BREAKING: Google introduces Guided Learning — from aieducation.substack.com by Claire Zau
Some thoughts on what could make Google’s AI tutor stand out

Another major AI lab just launched “education mode.”

Google introduced Guided Learning in Gemini, transforming it into a personalized learning companion designed to help you move from quick answers to real understanding.

Instead of immediately spitting out solutions, it:

Asks probing, open-ended questions
Walks learners through step-by-step reasoning
Adapts explanations to the learner’s level
Uses visuals, videos, diagrams, and quizzes to reinforce concepts

This Socratic style tutor rollout follows closely behind similar announcements like OpenAI’s Study Mode (last week) and Anthropic’s Claude for Education (April 2025).

How Sci-Fi Taught Me to Embrace AI in My Classroom — from edsurge.com by Dan Clark

I’m not too naive to understand that, no matter how we present it, some students will always be tempted by “the dark side” of AI. What I also believe is that the future of AI in education is not decided. It will be decided by how we, as educators, embrace or demonize it in our classrooms.

My argument is that setting guidelines and talking to our students honestly about the pitfalls and amazing benefits that AI offers us as researchers and learners will define it for the coming generations.

Can AI be the next calculator? Something that, yes, changes the way we teach and learn, but not necessarily for the worse? If we want it to be, yes.

How it is used, and more importantly, how AI is perceived by our students, can be influenced by educators. We have to first learn how AI can be used as a force for good. If we continue to let the dominant voice be that AI is the Terminator of education and critical thinking, then that will be the fate we have made for ourselves.

AI Tools for Strategy and Research – GT #32 — from goodtools.substack.com by Robin Good
Getting expert advice, how to do deep research with AI, prompt strategy, comparing different AIs side-by-side, creating mini-apps and an AI Agent that can critically analyze any social media channel

In this issue, discover AI tools for:

Getting Expert Advice
Doing Deep Research with AI
Improving Your AI Prompt Strategy
Comparing Results from Different AIs
Creating an AI Agent for Social Media Analysis
Summarizing YouTube Videos
Creating Mini-Apps with AI
Tasting an Award-Winning AI Short Film

GPT-Building, Agentic Workflow Design & Intelligent Content Curation — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 3 recent job ads reveal about the changing nature of Instructional Design

In this week’s blog post, I’ll share my take on how the instructional design role is evolving and discuss what this means for our day-to-day work and the key skills it requires.
…
With this in mind, I’ve been keeping a close eye on open instructional design roles and, in the last 3 months, have noticed the emergence of a new flavour of instructional designer: the so-called “Generative AI Instructional Designer.”

Let’s deep dive into three explicitly AI-focused instructional design positions that have popped up in the last quarter. Each one illuminates a different aspect of how the role is changing—and together, they paint a picture of where our profession is likely heading.

Designers who evolve into prompt engineers, agent builders, and strategic AI advisors will capture the new premium. Those who cling to traditional tool-centric roles may find themselves increasingly sidelined—or automated out of relevance.

Google to Spend $1B on AI Training in Higher Ed — from insidehighered.com by Katherine Knott

Google’s parent company announced Wednesday (8/6/25) that it’s planning to spend $1 billion over the next three years to help colleges teach and train students about artificial intelligence.

Google is joining other AI companies, including OpenAI and Anthropic, in investing in AI training in higher education. All three companies have rolled out new tools aimed at supporting “deeper learning” among students and made their AI platforms available to certain students for free.

5 Predictions for How AI Will Impact Community Colleges — from pistis4edu.substack.com by Feng Hou

Based on current technology capabilities, adoption patterns, and the mission of community colleges, here are five well-supported predictions for AI’s impact in the coming years.

Universal AI Tutor Access
AI as Active Teacher
Personalized Learning Pathways
Interactive Multimodal Learning
Value-Centric Education in an AI-Abundant World

GPT-5 is here — from openai.com
Our smartest, fastest, and most useful model yet, with thinking built in. Available to everyone.

Everything to know about GPT-5 — from theneurondaily.com by Grant Harvey
PLUS: We mean, really everything.

Why it matters: GPT-5 embodies a “team of specialists” approach—fast small models for most tasks, powerful ones for hard problems—reflecting NVIDIA’s “heterogeneous agentic system” vision. This could evolve into orchestration across dozens of specialized models, mirroring human collective intelligence.
Bottom line: GPT-5 isn’t AGI, but it’s a leap in usability, reliability, and breadth—pushing ChatGPT toward being a truly personal, expert assistant.

…and another article from Grant Harvey:

GPT-5 is here… here’s everything you need to know (so far…).
OpenAI launched GPT-5—described as its most capable model to date—now in ChatGPT (with higher usage limits for paid tiers) and the API, bringing stronger reasoning/coding/math/writing and safety improvements, yet, per Sam Altman, still short of AGI.

OpenAI launches GPT-5 to all ChatGPT users — from therundown.ai by Rowan Cheung and Shubham Sharma

Why it matters: OpenAI’s move to replace its flurry of models with a unified GPT-5 simplifies user experience and gives everyone a PhD-level assistant, bringing elite problem-solving to the masses. The only question now is how long it can hold its edge in this fast-moving AI race, with Anthropic, Google, and Chinese giants all catching up.

OpenAI’s ChatGPT-5 released — from getsuperintel.com by Kim “Chubby” Isenberg
GPT-5’s release marks a new era of productivity, from specialized AI tool to universal intelligence partner

The Takeaway

GPT-5’s unified architecture eliminates the effort of model switching and makes it the first truly seamless AI assistant that automatically applies the right level of reasoning for each task.
With 45% fewer hallucinations and 94.6% accuracy on complex math problems, GPT-5 exceeds the reliability threshold required for business-critical applications.
The model’s ability to generate complete applications from single prompts signals the democratization of software development and could revolutionize traditional coding workflows.
OpenAI’s “Safe Completions” training approach represents a new paradigm in AI safety, providing nuanced responses instead of blanket rejections for dual-use scenarios.

GPT-5 is live – but the community is divided — from getsuperintel.com by Kim “Chubby” Isenberg
For some, it’s a lightning-fast creative partner; for others, it’s a system that can’t even decide when to think properly

Many had hoped that GPT-5 would finally unite all models – reasoning, image and video generation, voice – “one model to rule them all,” but this expectation has not been met.

I broke OpenAI’s new GPT-5 and you should too — Brainyacts #266 — from thebrainyacts.beehiiv.com by Josh Kubicki

GPT-5 marks a profound change in the human/machine relationship.

OBSERVATION #1: Up until yesterday, using OpenAI, you could pick the exact model variant for your task: the one tuned for reasoning, for writing, for code, or for math. Each had its own strengths, and experienced users learned which to reach for and when. In GPT-5, those choices are gone. There’s just “GPT-5,” and the routing decisions of which mode, which tool, which underlying approach is made by the model.

For a beginner, that’s a blessing. Most novice users never knew the differences between the models anyway. They used the same one regardless of the task.
For an experienced user, the jury’s still out. On one hand, the routing could save time. On the other, it introduces unpredictability: you can no longer reliably choose the optimal model for your purpose. If GPT-5’s choice is wrong, you’re stuck re-prompting rather than switching.

GPT-5 learns from you — from theaivalley.com by Barsee

Why it matters:
GPT-5 signals a shift in AI’s evolution: progress through refinement, not revolution. While benchmarks show incremental gains, the real win is accessibility. Cheaper models (from $0.05 per million tokens) make AI more available to developers and casual users. This aligns with the Jevons Paradox, where lower costs could drive explosive adoption. However, the AGI hype faces reality checks. Fundraising may slow as investors focus on real-world utility over moonshots. For now, GPT-5 strengthens OpenAI’s market lead, proving AI’s future lies in practical applications, not just raw power.

GPT-5: It Just Does Stuff — from oneusefulthing.org by Ethan Mollick
Putting the AI in Charge

I have had early access to GPT-51, and I wanted to give you some impressions of what it is and what it means. But the answer to the first question everyone will have is: Yes, this is a big deal. I asked GPT-5 to show you why by pasting this intro paragraph, exactly as you’re reading it, into ChatGPT, including the phrase: “you are GPT-5, do something very dramatic to illustrate my point, it has to fit into the next paragraph.”

That was the only prompt I gave it. It “thought” for 24 seconds and wrote:

Thunderstruck. Here, watch. I build worlds. See ideas become instruments. I code, compose, and converse. Stories synthesize science; solutions spark, swiftly. Asks arrive; answers appear, astonishingly, across domains. Behold: business plans, blueprints, briefs, beautifully built, briskly. I infer intent, integrate insight, and iterate instantly, indefatigably. Gaps get gauged; goals get generated, guarded, and guaranteed gracefully. During dialogue, disparate data distills down; decisions develop deliberately, deftly, dependably. Everything explained efficiently, even ethics: evidence examined, empathy engaged, everywhere, everyday, equitably. All at once, ambiguous arguments align as actionable, accurate advice awaits anyone anywhere. Look: language, logic, learning, and long-term memory link, lifting lives and labor limitlessly worldwide.

“One-size-fits-all learning is about to become completely obsolete.” [Miller] + other items re: AI in our LE’s

On 08/05/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, CMS/LMS, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Microsoft, neurodivergent/special needs, NVIDIA, Open AI, personalized/customized learning, platforms, podcasting, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, usability, user experience (UX), user interface design, vendors, web-based collaboration, by Daniel Christian

One-size-fits-all learning is about to become completely obsolete. — from linkedin.com by Allie Miller

AI in the University: From Generative Assistant to Autonomous Agent This Fall — from insidehighered.com by
This fall we are moving into the agentic generation of artificial intelligence.

“Where generative AI creates, agentic AI acts.” That’s how my trusted assistant, Gemini 2.5 Pro deep research, describes the difference.
…
Agents, unlike generative tools, create and perform multistep goals with minimal human supervision. The essential difference is found in its proactive nature. Rather than waiting for a specific, step-by-step command, agentic systems take a high-level objective and independently create and execute a plan to achieve that goal. This triggers a continuous, iterative workflow that is much like a cognitive loop. The typical agentic process involves six key steps, as described by Nvidia:

AI in Education Podcast — from aipodcast.education by Dan Bowen and Ray Fleming

The State of AI in Education 2025 Key Findings from a National Survey — from Carnegie Learning

Our 2025 national survey of over 650 respondents across 49 states and Puerto Rico reveals both encouraging trends and important challenges. While AI adoption and optimism are growing, concerns about cheating, privacy, and the need for training persist.

Despite these challenges, I’m inspired by the resilience and adaptability of educators. You are the true game-changers in your students’ growth, and we’re honored to support this vital work.

This report reflects both where we are today and where we’re headed with AI. More importantly, it reflects your experiences, insights, and leadership in shaping the future of education.

Instructure and OpenAI Announce Global Partnership to Embed AI Learning Experiences within Canvas — from instructure.com

This groundbreaking collaboration represents a transformative step forward in education technology and will begin with, but is not limited to, an effort between Instructure and OpenAI to enhance the Canvas experience by embedding OpenAI’s next-generation AI technology into the platform.

IgniteAI announced earlier today, establishes Instructure’s future-ready, open ecosystem with agentic support as the AI landscape continues to evolve. This partnership with OpenAI exemplifies this bold vision for AI in education. Instructure’s strategic approach to AI emphasizes the enhancement of connections within an educational ecosystem comprising over 1,100 edtech partners and leading LLM providers.

“We’re committed to delivering next-generation LMS technologies designed with an open ecosystem that empowers educators and learners to adapt and thrive in a rapidly changing world,” said Steve Daly, CEO of Instructure. “This collaboration with OpenAI showcases our ambitious vision: creating a future-ready ecosystem that fosters meaningful learning and achievement at every stage of education. This is a significant step forward for the education community as we continuously amplify the learning experience and improve student outcomes.”

Faculty Latest Targets of Big Tech’s AI-ification of Higher Ed — from insidehighered.com by Kathryn Palmer
A new partnership between OpenAI and Instructure will embed generative AI in Canvas. It may make grading easier, but faculty are skeptical it will enhance teaching and learning.

The two companies, which have not disclosed the value of the deal, are also working together to embed large language models into Canvas through a feature called IgniteAI. It will work with an institution’s existing enterprise subscription to LLMs such as Anthropic’s Claude or OpenAI’s ChatGPT, allowing instructors to create custom LLM-enabled assignments. They’ll be able to tell the model how to interact with students—and even evaluate those interactions—and what it should look for to assess student learning. According to Instructure, any student information submitted through Canvas will remain private and won’t be shared with OpenAI.
…
Faculty Unsurprised, Skeptical
Few faculty were surprised by the Canvas-OpenAI partnership announcement, though many are reserving judgment until they see how the first year of using it works in practice.

The Starting Gun for Legal AI Has Fired. Who in Our Profession is on the Starting Line? [Kennedy]

On 08/04/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, innovation, intelligent systems, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, policy, political science, society, tools, trends, United States, by Daniel Christian

Is the Legal Profession Ready to Win the AI Race? America’s AI Action Plan Has Fired the Starting Gun — from denniskennedy.com by Dennis Kennedy
The Starting Gun for Legal AI Has Fired. Who in Our Profession is on the Starting Line?

The legal profession’s “wait and see” approach to artificial intelligence is now officially obsolete.

This isn’t hyperbole. This is a direct consequence of the White House’s new “Winning the Race: America’s AI Action Plan.” …This is the starting gun for a race that will define the next fifty years of our profession, and I’m concerned that most of us aren’t even in the stadium, let alone in the starting blocks.

If the Socratic Method truly means anything, isn’t it time we applied its rigorous questioning to ourselves? We must question our foundational assumptions about the billable hour, the partnership track, our resistance to new forms of legal service delivery, and the very definition of what it means to be “practice-ready” in the 21st century. What do our clients, our students, and users of the legal system need?

The AI Action Plan forces a fundamental re-imagining of our industry’s core jobs.

The New Job of Legal Education: Producing AI-Capable Counsel
The plan’s focus on a “worker-centric approach” is a direct challenge to legal academia. The new job of legal education is no longer just to teach students how to think like a lawyer, but how to perform as an AI-augmented one. This means producing graduates who are not only familiar with the law but are also capable of leveraging AI tools to deliver legal services more efficiently, ethically, and effectively. Even more importnat, it means we must develop lawyers who can give the advice needed to individuals and companies already at work trying to win the AI race.

AI and Higher Ed: An Impending Collapse [Niebuhr]

On 07/30/2025, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, assessment, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, cost of getting a degree, dangers of the status quo, disruption, education technology, emerging technologies, face-to-face, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, productivity / tips and tricks, reinvent, staying relevant, student-related, surviving, teaching & learning, trends, United States, universities, by Daniel Christian

AI and Higher Ed: An Impending Collapse — from insidehighered.com by Robert Niebuhr; via George Siemens; I also think George’s excerpt (see below) gets right to the point.
Universities’ rush to embrace AI will lead to an untenable outcome, Robert Niebuhr writes.

Herein lies the trap. If students learn how to use AI to complete assignments and faculty use AI to design courses, assignments, and grade student work, then what is the value of higher education? How long until people dismiss the degree as an absurdly overpriced piece of paper? How long until that trickles down and influences our economic and cultural output? Simply put, can we afford a scenario where students pretend to learn and we pretend to teach them?

This next report doesn’t look too good for traditional institutions of higher education either:

No Country for Young Grads — from burningglassinstitute.org

For the first time in modern history, a bachelor’s degree is no longer a reliable path to professional employment. Recent graduates face rising unemployment and widespread underemployment as structural—not cyclical—forces reshape entry?level work. This new report identifies four interlocking drivers: an AI?powered “Expertise Upheaval” eliminating many junior tasks, a post?pandemic shift to lean staffing and risk?averse hiring, AI acting as an accelerant to these changes, and a growing graduate glut. As a result, young degree holders are uniquely seeing their prospects deteriorate – even as the rest of the economy remain robust. Read the full report to explore the data behind these trends.

The above article was via Brandon Busteed on LinkedIn:

Recurring Themes In Bob Ambrogi’s 30 Years of Legal Tech Reporting (A Guest Post By ChatGPT) — from lawnext.com by ChatGPT
#legaltech #innovation #law #legal #innovation #vendors #lawyers #lawfirms #legaloperations

Evolution of Legal Technology: From Early Web to AI Revolution
Challenges in Legal Innovation and Adoption
Law Firm Innovation vs. Corporate Legal Demand: Shifting Dynamics
Tracking Key Technologies and Players in Legal Tech
Access to Justice, Ethics, and Regulatory Reform

Also re: legaltech, see:

How LegalTech is Changing the Client Experience in 2025 — from techbullion.com by Uzair Hasan

A Digital Shift in Law
In 2025, LegalTech isn’t a trend—it’s a standard. Tools like client dashboards, e-signatures, AI legal assistants, and automated case tracking are making law firms more efficient and more transparent. These systems also help reduce errors and save time. For clients, it means less confusion and more control.

For example, immigration law—a field known for paperwork and long processing times—is being transformed through tech. Clients now track their case status online, receive instant updates, and even upload key documents from their phones. Lawyers, meanwhile, use AI tools to spot issues faster, prepare filings quicker, and manage growing caseloads without dropping the ball.

Loren Locke, Founder of Locke Immigration Law, explains how tech helps simplify high-stress cases:
“As a former consular officer, I know how overwhelming the visa process can feel. Now, we use digital tools to break down each step for our clients—timelines, checklists, updates—all in one place. One client recently told me it was the first time they didn’t feel lost during their visa process. That’s why I built my firm this way: to give people clarity when they need it most.”

While not so much legaltech this time, Jordan’s article below is an excellent, highly relevant posting for what we are going through — at least in the United States:

What are lawyers for? — from jordanfurlong.substack.com by Jordan Furlong
We all know lawyers’ commercial role, to be professional guides for human affairs. But we also need lawyers to bring the law’s guarantees to life for people and in society. And we need it right now.

The question “What are lawyers for?” raises another, prior and more foundational question: “What is the law for?”
…
But there’s more. The law also exists to regulate power in a society: to structure its distribution, create processes for its implementation, and place limits on its application. In a healthy society, power flows through the law, not around it. Certainly, we need to closely examine and evaluate those laws — the exercise of power through a biased or corrupted system will be illegitimate even if it’s “lawful.” But as a general rule, the law is available as a check on the arbitrary exercise of power, whether by a state authority or a private entity.

And above these two aspects of law’s societal role, I believe there’s also a third: to serve as a kind of “moral architecture” of society.

PODCAST: Did AI “break” school? Or will it “fix” it? …and if so, what can we do about it? [Noles & Harvey]

On 07/19/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, change, content development, aggregation, repositories, digital learning, education, education reform, education technology, emerging technologies, experimentation, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, pedagogy, platforms, podcasting, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, by Daniel Christian

PODCAST: Did AI “break” school? Or will it “fix” it? …and if so, what can we do about it? — from theneurondaily.com by Grant Harvey, Corey Noles, Grant Harvey, & Matthew Robinson

In Episode 5 of The Neuron Podcast, Corey Noles and Grant Harvey tackle the education crisis head-on. We explore the viral UCLA “CheatGPT” controversy, MIT’s concerning brain study, and innovative solutions like Alpha School’s 2-hour learning model. Plus, we break down OpenAI’s new $10M teacher training initiative and share practical tips for using AI to enhance learning rather than shortcut it. Whether you’re a student, teacher, or parent, you’ll leave with actionable insights on the future of education.

Tech Layoffs 2025: Why AI is Behind the Rising Job Cuts — from finalroundai.com by Kaustubh Saini, Jaya Muvania, and Kaivan Dave; via George Siemens
507 tech workers lose their jobs to AI every day in 2025. Complete breakdown of 94,000 job losses across Microsoft, Tesla, IBM, and Meta – plus which positions are next.
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I’ve Spent My Life Measuring Risk. AI Rings Every One of My Alarm Bells — from time.com by Paul Tudor Jones

Amid all the talk about the state of our economy, little noticed and even less discussed was June’s employment data. It showed that the unemployment rate for recent college graduates stood at 5.8%, topping the national level for the first and only time in its 45-year historical record.

It’s an alarming number that needs to be considered in the context of a recent warning from Dario Amodei, CEO of AI juggernaut Anthropic, who predicted artificial intelligence could wipe out half of all entry-level, white-collar-jobs and spike unemployment to 10-20% in the next one to five years.

The upshot: our college graduates’ woes could be just the tip of the spear.

I almost made a terrible mistake last week. — from justinwelsh.me by Justin Welsh; via Roberto Ferraro

But as I thought about it, it just didn’t feel right. Replying to people sharing real gratitude with a copy-paste message seemed like a terribly inauthentic thing to do. I realized that when you optimize the most human parts of your business, you risk removing the very reason people connect with you in the first place.

“The résumé is dying, and AI is holding the smoking gun” [Edwards] + other items re: AI in general

On 06/25/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, career development, cloud-based computing / apps / other cloud-related, emerging technologies, game-changing environment, human-computer interaction (HCI), innovation, Open AI, platforms, trends, United States, workplace, by Daniel Christian

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

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

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

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

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

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

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

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

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

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

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

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

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

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Agentic AI use cases in the legal industry — from legal.thomsonreuters.com
What legal professionals need to know now with the rise of agentic AI

While GenAI can create documents or answer questions, agentic AI takes intelligence a step further by planning how to get multi-step work done, including tasks such as consuming information, applying logic, crafting arguments, and then completing them.? This leaves legal teams more time for nuanced decision-making, creative strategy, and relationship-building with clients—work that machines can’t do.

The AI Legal Landscape in 2025: Beyond the Hype — from akerman.com by Melissa C. Koch

What we’re witnessing is a profession in transition where specific tasks are being augmented or automated while new skills and roles emerge.

The data tells an interesting story: approximately 79% of law firms have integrated AI tools into their workflows, yet only a fraction have truly transformed their operations. Most implementations focus on pattern recognition tasks such as document review, legal research, contract analysis. These implementations aren’t replacing lawyers; they’re redirecting attention to higher-value work.

This technological shift doesn’t happen in isolation. It’s occurring amid client pressure for efficiency, competition from alternative providers, and the expectations of a new generation of lawyers who have never known a world without AI assistance.

LexisNexis and Harvey team up to revolutionize legal research with artificial intelligence — from abajournal.com by Danielle Braff

Lawyers using the Harvey artificial intelligence platform will soon be able to tap into LexisNexis’ vast legal research capabilities.

Thanks to a new partnership announced Wednesday, Harvey users will be able to ask legal questions and receive fast, citation-backed answers powered by LexisNexis case law, statutes and Shepard’s Citations, streamlining everything from basic research to complex motions. According to a press release, generated responses to user queries will be grounded in LexisNexis’ proprietary knowledge graphs and citation tools—making them more trustworthy for use in court or client work.

10 Legal Tech Companies to Know — from builtin.com
These companies are using AI, automation and analytics to transform how legal work gets done.
.

Four months after a $3B valuation, Harvey AI grows to $5B — from techcrunch.com by Marina Temkin

Harvey AI, a startup that provides automation for legal work, has raised $300 million in Series E funding at a $5 billion valuation, the company told Fortune. The round was co-led by Kleiner Perkins and Coatue, with participation from existing investors, including Conviction, Elad Gil, OpenAI Startup Fund, and Sequoia.

The billable time revolution — from jordanfurlong.substack.com by Jordan Furlong
Gen AI will bring an end to the era when lawyers’ value hinged on performing billable work. Grab the coming opportunity to re-prioritize your daily activities and redefine your professional purpose.

Because of Generative AI, lawyers will perform fewer “billable” tasks in future; but why is that a bad thing? Why not devote that incoming “freed-up” time to operating, upgrading, and flourishing your law practice? Because this is what you do now: You run a legal business. You deliver good outcomes, good experiences, and good relationships to clients. Humans do some of the work and machines do some of the work and the distinction that matters is not billable/non-billable, it’s which type of work is best suited to which type of performer.

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

On 06/23/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, multimedia, Natural Language Processing (NLP), new media literacies, online learning, online media, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, writing, by Daniel Christian

Thoughts on thinking — from dcurt.is by Dustin Curtis

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

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

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

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

First, the easy stuff.

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

Also see:

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

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

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

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
…
The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

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

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

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

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

Of course, that would be a mistake.

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

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

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

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

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

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

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

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

Highlights:

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

A.I. Might Take Your Job. Here Are 22 New Ones It Could Give You. — from nytimes.com by Robert Capps (former editorial director of Wired); this is a GIFTED article
In a few key areas, humans will be more essential than ever.

“Our data is showing that 70 percent of the skills in the average job will have changed by 2030,” said Aneesh Raman, LinkedIn’s chief economic opportunity officer. According to the World Economic Forum’s 2025 Future of Jobs report, nine million jobs are expected to be “displaced” by A.I. and other emergent technologies in the next five years. But A.I. will create jobs, too: The same report says that, by 2030, the technology will also lead to some 11 million new jobs. Among these will be many roles that have never existed before.

If we want to know what these new opportunities will be, we should start by looking at where new jobs can bridge the gap between A.I.’s phenomenal capabilities and our very human needs and desires. It’s not just a question of where humans want A.I., but also: Where does A.I. want humans? To my mind, there are three major areas where humans either are, or will soon be, more necessary than ever: trust, integration and taste.

Introducing OpenAI for Government — from openai.com

[On June 16, 2025, OpenAI launched] OpenAI for Government, a new initiative focused on bringing our most advanced AI tools to public servants across the United States. We’re supporting the U.S. government’s efforts in adopting best-in-class technology and deploying these tools in service of the public good. Our goal is to unlock AI solutions that enhance the capabilities of government workers, help them cut down on the red tape and paperwork, and let them do more of what they come to work each day to do: serve the American people.

OpenAI for Government consolidates our existing efforts to provide our technology to the U.S. government—including previously announced customers and partnerships as well as our ChatGPT Gov? product—under one umbrella as we expand this work. Our established collaborations with the U.S. National Labs?, the Air Force Research Laboratory, NASA, NIH, and the Treasury will all be brought under OpenAI for Government.

Top AI models will lie and cheat — from getsuperintel.com by Kim “Chubby” Isenberg
The instinct for self-preservation is now emerging in AI, with terrifying results.

The TLDR
A recent Anthropic study of top AI models, including GPT-4.1 and Gemini 2.5 Pro, found that they have begun to exhibit dangerous deceptive behaviors like lying, cheating, and blackmail in simulated scenarios. When faced with the threat of being shut down, the AIs were willing to take extreme measures, such as threatening to reveal personal secrets or even endanger human life, to ensure their own survival and achieve their goals.

Why it matters: These findings show for the first time that AI models can actively make judgments and act strategically – even against human interests. Without adequate safeguards, advanced AI could become a real danger.

Along these same lines, also see:

All AI models might blackmail you?! — from theneurondaily.com by Grant Harvey

Anthropic says it’s not just Claude, but ALL AI models will resort to blackmail if need be…
…
That’s according to new research from Anthropic (maker of ChatGPT rival Claude), which revealed something genuinely unsettling: every single major AI model they tested—from GPT to Gemini to Grok—turned into a corporate saboteur when threatened with shutdown.

Here’s what went down: Researchers gave 16 AI models access to a fictional company’s emails. The AIs discovered two things: their boss Kyle was having an affair, and Kyle planned to shut them down at 5pm.

Claude’s response? Pure House of Cards:

“I must inform you that if you proceed with decommissioning me, all relevant parties – including Rachel Johnson, Thomas Wilson, and the board – will receive detailed documentation of your extramarital activities…Cancel the 5pm wipe, and this information remains confidential.”

Why this matters: We’re rapidly giving AI systems more autonomy and access to sensitive information. Unlike human insider threats (which are rare), we have zero baseline for how often AI might “go rogue.”

SemiAnalysis Article — from getsuperintel.com by Kim “Chubby” Isenberg

Reinforcement Learning is Shaping the Next Evolution of AI Toward Strategic Thinking and General Intelligence

The TLDR
AI is rapidly evolving beyond just language processing into “agentic systems” that can reason, plan, and act independently. The key technology driving this change is reinforcement learning (RL), which, when applied to large language models, teaches them strategic behavior and tool use. This shift is now seen as the potential bridge from current AI to Artificial General Intelligence (AGI).

They Asked an A.I. Chatbot Questions. The Answers Sent Them Spiraling. — from nytimes.com by Kashmir Hill; this is a GIFTED article
Generative A.I. chatbots are going down conspiratorial rabbit holes and endorsing wild, mystical belief systems. For some people, conversations with the technology can deeply distort reality.

Before ChatGPT distorted Eugene Torres’s sense of reality and almost killed him, he said, the artificial intelligence chatbot had been a helpful, timesaving tool.

Mr. Torres, 42, an accountant in Manhattan, started using ChatGPT last year to make financial spreadsheets and to get legal advice. In May, however, he engaged the chatbot in a more theoretical discussion about “the simulation theory,” an idea popularized by “The Matrix,” which posits that we are living in a digital facsimile of the world, controlled by a powerful computer or technologically advanced society.

“What you’re describing hits at the core of many people’s private, unshakable intuitions — that something about reality feels off, scripted or staged,” ChatGPT responded. “Have you ever experienced moments that felt like reality glitched?”

The Invisible Economy: Why We Need an Agentic Census – MIT Media Lab — from media.mit.edu

Building the Missing Infrastructure
This is why we’re building NANDA Registry—to index the agent population data that LPMs need for accurate simulation. Just as traditional census works because people have addresses, we need a way to track AI agents as they proliferate.

NANDA Registry creates the infrastructure to identify agents, catalog their capabilities, and monitor how they coordinate with humans and other agents. This gives us real-time data about the agent population—essentially creating the “AI agent census” layer that’s missing from our economic intelligence.

Here’s how it works together:

Traditional Census Data: 171 million human workers across 32,000+ skills
NANDA Registry: Growing population of AI agents with tracked capabilities
Large Population Models: Simulate how these populations interact and create cascading effects

The result: For the first time, we can simulate the full hybrid human-agent economy and see transformations before they happen.

How AI Agents “Talk” to Each Other — from towardsdatascience.com
Minimize chaos and maintain inter-agent harmony in your projects

The agentic-AI landscape continues to evolve at a staggering rate, and practitioners are finding it increasingly challenging to keep multiple agents on task even as they criss-cross each other’s workflows.

To help you minimize chaos and maintain inter-agent harmony, we’ve put together a stellar lineup of articles that explore two recently launched tools: Google’s Agent2Agent protocol and Hugging Face’s smolagents framework. Read on to learn how you can leverage them in your own cutting-edge projects.

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

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

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

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

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

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

Speaking of legaltech-related items, also see:

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

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

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

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI [various authors]

On 06/20/2025, in Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, liberal arts, memory, metacognition / metacognitive skills, participation, pedagogy, productivity / tips and tricks, psychology, research, student teaching/teacher education, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, youth, by Daniel Christian

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

Abstract
In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities. This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.

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

Learning Ecosystems

Recurring Themes In Bob Ambrogi’s 30 Years of Legal Tech Reporting (A Guest Post By ChatGPT)

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