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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The AI Pilot is Over: Legal’s Moment to Move Beyond Experiments and Avoid the Innovator’s Dilemma — by Sabastian Niles, President & CLO Salesforce

We welcome back Sabastian Niles, President and Chief Legal Officer at Salesforce, to discuss his recent “Open Letter to Law Firms.” As the legal industry hits a critical inflection point, Sabastian argues that the era of “AI theater” and small-scale pilots is over.

The conversation dives deep into the Innovator’s Dilemma facing law firms, the shift toward agentic AI, and how firms must reimagine their business models to remain competitive. Sabastian highlights that legal professionals are uniquely positioned to lead the charge in trusted AI transformation, provided they embrace transparency, data integration, and shared efficiency gains with their clients.


How Law Firms Can Lead the Agentic AI Era — And What Clients Now Expect — from salesforce.com by Sabastian Niles

  1. Competition is intensifying:
  2. Client expectations will reshape the market: Clients are no longer asking whether firms use AI. Rather, they’re expecting to see the benefits of that transformation passed directly to them. They expect more for less but are not simply seeking lower costs – they want more insight, more speed, and more value for every dollar of their budget. And law firms, which operate at the center of data, ethics, and risk, have outsized influence over the structure and deployment of trusted AI across all industries. Some clients, like Salesforce, are even creating agentic tools to improve the law firm’s experience when working with clients. …
  3. Unified client intelligence is at the heart of legal strategy: …

Are AI First Firms a Threat To Biglaw? — from legallydisrupted.com by Zach Abramowitz and Logan Brown
Episode 49 features AI first law firm founder Logan Brown

Is Big Law about to become the Yellow Pages? Hey, I didn’t say it, but ex-Cooley lawyer turned AI first law firm Logan Brown did. The question is do I agree?

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Instead of the traditional billable hour, they charge flat fees like $100 for a contract review or $50 to ask a lawyer a quick question via chat. She’s already got over 40 attorneys on the platform. And in a departure from the traditional partnership track, she actually chose to raise venture capital so she could scale the firm like a tech company and tackle the access-to-justice gap.

From DSC:
LOVE to hear anything and everything regarding efforts to address the access-to-justice gap here in the United States!!! Along these lines, also see:

“Legal services are out of reach for many people and small businesses, and the gap is widening,” Anthropic said in its announcement. “We’re working with the Free Law Project, Justice Technology Association and other legal aid and public service organizations to help make legal services more affordable and available.”

That makes this the first time that a leading AI company is explicitly naming access to justice as a foundational pillar, JTA says, with Anthropic positioning the initiative as “investing in the premise that AI should expand access to justice — making legal services more affordable and available.”


AI Hallucinations in Legal Filings: How to Avoid Them and What to Do When You Find Them — from legaltechdaily.com by Ed Walters

What AI hallucinations in law actually are
In a legal context, AI hallucinations are one of two things. They’re either citations to cases or statutes that don’t exist, or citations to real authorities for propositions those authorities don’t actually support.

The first kind is the one making headlines. A lawyer or pro se litigant uses a general-purpose chatbot like ChatGPT, Claude, Gemini, Copilot, or Grok to help draft a brief. The model, predicting the statistically likely next word, decides a citation belongs in a particular spot, and produces one. The reporter might be real. The volume number might fall within the right range. The Bluebook formatting is often better than what most associates produce. The case itself just doesn’t exist.

The second kind is older than AI. Lawyers have always occasionally cited a case for a proposition that the case doesn’t stand for. AI has made this kind of error easier to commit and easier to catch.


A dangerous mind — from by Jordan Furlong
Generative AI is a tireless genius with no boundaries. Use it carelessly, and it can usurp your voice, overwrite your ideas, and steal your originality. Make sure you safeguard your capacity to think.

Don’t let the genius do the hard work for you. The more incisive and unique your own thinking — the more you battle and struggle and eventually succeed in getting your ideas and insights out — the more you can benefit from the AI’s complementary improvements. The great irony of Gen AI is that it actually makes your own cognitive processes your most valuable asset.

So safeguard your mind. Defend your right to think as only you can. And if you don’t want AI to replace you, then don’t send it a written invitation.


Ten AI Predictions for 2026: What Leading Analysts Say Legal Teams Should Expect — from natlawreview.com by Andrew R. Lee, Jason M. Loring, Graham H. Ryan

The pilot phase is over. After two years of experimentation for legal departments, 2026 will be the year AI moves from “interesting tool” to “operational infrastructure,” whether they’re ready or not. We surveyed predictions from Gartner, Forrester, McKinsey, and other leading legal tech analysts to identify where expert consensus is forming. The implications for AI governance, outside counsel relationships, and regulatory compliance are significant.

 

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.


 

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.

 

FutureFit AI Announces Strategic Investment to Help Governments and Industries Navigate AI’s Impact on People & Jobs — from prnewswire.com; via Ryan Craig

NEW YORKApril 13, 2026 /PRNewswire/ — FutureFit AI, a global leader in AI-powered workforce development technology, today announced an investment from Achieve Partners, led by investor and author Ryan Craig,  to accelerate its mission of helping more people navigate to better jobs faster and cheaper at scale.

“For too long, the U.S. workforce system has relied on disparate and disconnected systems to try to bridge the gap between the skills workers bring to the table, and the jobs available in a fast-changing labor market. In the age of AI, the need for a better approach has only become more urgent,” said Ryan Craig, co-founder and managing director of Achieve and author of Apprentice NationA New U, and College Disrupted. “FutureFit AI is solving that problem by helping workforce organizations create clearer paths to career opportunity for workers and solve pressing talent gaps that hinder economic growth. Their work around the country has already demonstrated the ability to help more people get good jobs faster.”

“A mission that began with a simple question of ‘What if everyone had a GPS for their career’ has turned into years of working closely with government and industry leaders to respond to – and solve for – the impacts of digital transformation and AI on jobs and people,” added Ekhtiari. “Our partnership with Achieve will accelerate our work to build and scale the missing workforce transition infrastructure that our country and the world so badly need at this moment.”

 

AI for Your Next Career Move — from wondertools.substack.com by Jeremy Caplan
Free tools to explore, research, and interview better

AI tools can serve as patient assistants when you’re looking for a job. Use them to organize your search. Or to challenge your assumptions about potential jobs. They can also help you present your strengths more persuasively. When you’re changing fields, or trying to move up, AI can help you stand out.

1. Visualize Your Career Options
Try: Google’s
Career Dreamer

What it is: A free tool for exploring jobs adjacent to yours. See a map of professional fields related to your interests.

How to use it: Start by typing in a current or previous role. Or name a job that interests you. Use up to five words. You can also name a specific organization or industry, if you have one in mind.

Career Dreamer asks what work activities interest you, then maps related career paths. Pick one at a time to explore.

You can then browse actual job openings. Refine the search based on location, company size, or other factors you care about.

 

This Is a Hard Time to Start a Career. These Two Words Can Help. — a gifted article from nytimes.com by Jodi Kantor
Advice on building a rewarding work life, even amid employment gloom.

If you’re sweating about what field to enter, here are a few things you can do now. Buy a cheap, thin notebook. Keep it on you. Every week, make a practice of writing down which actions you enjoy and which ones you hate, whom you like being around and whom you can’t stand. Keep running lists of what you’re good at and what ideas move you. Notice yourself.

Look to your friends instead. Think about what roles you take on with them: math tutor, party planner, psychologist, workout coach. These answers often reveal truths that our résumés do not. In social relationships, we aren’t bound by suffocating expectations about our future. Our friends have needs, and by noticing how we respond to them, we can learn who we are.

There is a wiser way to seize the future, which is to think about need. What is your own assessment of what society will need most during your working years, the next four or five decades? What kind of care; what kind of products; what kind of information?

The people I see thriving at work are the ones who chased some bigger need — not imposed by hollow conventional wisdom, but articulated through independent observation. Craft gives their work authority. Need gives it propulsion.

 

From DSC:
It’s great to see this type of good news for a change!


Tiny Traverse City restaurant sells more than 3,000 burgers in one day – all to help a competitor — this is a gifted article (which lasts for 7 days) out at mlive.com, by Tanda Gmiter

TRAVERSE CITY, MI – The long line out the door and down the street of the little Oakwood Proper Burgers shop was a head-turner Saturday as the restaurant invited people to its 1,000 Burger Challenge event.

But the swift sales being rung up inside weren’t benefitting their own business. Instead, they were a heartfelt helping hand to a competitor across town.

The team behind Oakwood Proper – as well as several other restaurant friends from the area – joined together to raise money for “Chef Tim” Bergstrom, the man behind his namesake Bergstrom’s Burgers. He’s been undergoing cancer treatment for some time now, and medical bills are mounting.
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Which Jobs Are Most at Risk From AI? New Anthropic Data Offers Clues. — from builtin.com by Matthew Urwin
Anthropic set out in its latest study to predict how artificial intelligence could impact the labor market. Instead, its findings raise more questions than answers for tech workers as the U.S. government refuses to regulate the AI industry.

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


Matthew links to:

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

Key findings

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

 

What the Future of Learning Looks Like in the Era of AI — from the Center for Academic Innovation at the University of Michigan, by Sean Corp

AI & the Future of Learning Summit brings industry, education leaders together to discuss higher education’s opportunity to lead, what students need, and what partnerships are possible

As artificial intelligence rapidly reshapes the nature of work and learning, speakers at the University of Michigan’s AI & the Future of Learning Summit delivered a clear message: higher education must take a leading role in defining what comes next.

One CEO of a leading educational technology company put it like this: “The only bad thing would be universities standing still.”

Universities must embrace their roles as providers of continuous, lifelong learning that evolves alongside technological change. 


This shift is already affecting early-career pathways. Employers are placing greater emphasis on experience, while traditional entry-level roles are becoming less accessible. There is often a gap between what a credential represents and the expectations of employers.

That gap is particularly evident in access to internships. Chris Parrish, co-founder and president of Podium, noted that millions of students compete for a limited number of internships each year, making it increasingly difficult to gain the experience employers demand.

“If you miss out on an internship, you’re twice as likely to be unemployed,” Parrish said. 

 

You Can’t Future-Proof Your Career From AI, But You Can Do This — from builtin.com by Liz Tran
Agility has become the most important skill to cultivate in today’s job market. Here’s how to get started.

Summary: Job seekers facing future panic should prioritize agility over information consumption. Build it by focusing on 30-day action experiments, reframing resumes around durable skills like problem-solving and embracing uncertainty through stretch applications and real-world feedback.

The antidote is what I call AQ — the agility quotient — which is your capacity to face change, disappointment and uncertainty without losing your footing. Unlike IQ, which measures what you know, AQ measures how fast you adapt when the rules change. Right now, it’s the most important career asset you have. Here’s how to build it.

What Is Agility Quotient (AQ)?
AQ is a measure of an individual’s capacity to adapt quickly when rules, industries or circumstances change. Unlike IQ, which focuses on existing knowledge, AQ emphasizes the ability to face uncertainty and disappointment without losing one’s footing, prioritizing action and iteration over exhaustive planning.

 

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

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

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

 

The Most Obvious Fix in Education — from michelleweise.substack.com by Michelle Weise
The No-Brainer Nobody’s Doing 

We know what better learning looks like. We have known for a while.

Real problems. Real roles. Built-in conflict. Conditions that simulate the messiness of actual work. Reflection that asks not just what did you do but who are you becoming? These are not radical ideas. They are not untested theories. The research is clear, employers are asking for exactly this, and students consistently report that the closest they got to real work was the most valuable part of their education.

So why aren’t universities doing more of it?

That is the question worth sitting with — because the gap between what we know and what we do is not a knowledge problem. It is a design problem, an incentive problem, and if we’re being candid, a courage problem.

Because in the meantime, learners are paying the price. They graduate credentialed but untested. They enter labor markets that want proof of performance and experience, not transcripts. They lack the networks, the exposure, and the scar tissue that comes from navigating real work.


Also relevant, see:

The Apprenticeship (R)Evolution — from insidehighered.com by Sara Weissman and Colleen Flaherty
Once synonymous with hard hats and tool belts, apprenticeships are branching into health care, artificial intelligence, business services, advanced manufacturing and more.

Such programs also challenge stereotypes about apprenticeships—namely that they’re only in construction, an earn-and-learn catchall for traditionally apprenticeable occupations such as bricklayer, plumber, carpenter and electrician. In integrating robotics, automation, machining and logistics, the manufacturing development program is a bridge to understanding how apprenticeships are evolving to support some of the nation’s fastest-growing industries. These include advanced manufacturing, but also health care, information technology and other business services.

 

Building a Thriving Organizational Culture: Strategies for Success — from learningguild.com by Genevieve Caplette

Characteristics of Strong Culture
Although each organization’s culture is unique, strong cultures share several common traits. They communicate openly, maintain trust across all levels, and reinforce their values through daily actions rather than slogans. Recognition is frequent and meaningful. Collaboration is encouraged over competition, and employees feel psychologically safe expressing ideas or concerns. These cultures evolve as the organization grows, ensuring alignment between stated values and lived behavior.

How to Strengthen Culture
A thriving environment is built through everyday habits: transparent communication, active listening, constructive feedback, and ensuring employees have the resources to grow. Embedding values into hiring, onboarding, recognition, and decision-making reinforces culture at every level. Sustaining culture requires ongoing attention—listening regularly, adjusting to evolving needs, and ensuring leaders continue to model the behaviors the organization expects.

 

From DSC:
I have been proposing that the AI-based learning platform of the future will be constantly doing this — every single day. It will know what the in-demand skills are — at any given moment in time. It will then be able to direct you to resources that will help you gain those skills. Though in my vision, the system is querying actual/open job descriptions, not analyzing learning data from enterprise learners. Perhaps I should add that to the vision.


Coursera’s Job Skills Report 2026: Top skills for your students — from coursera.org

The Job Skills Report 2026 analyzes learning data from more than 6 million enterprise learners to identify the future job skills organizations need most. It’s designed for HR and L&D leaders; data, IT, and software & product development leaders; higher education administrators; and government agencies seeking actionable insights on workforce skills trends and AI-driven transformation.

Drawing on data from 6 million enterprise learners across nearly 7,000 organizations, the Job Skills Report 2026 guides you through the skills reshaping the global economy. This year’s analysis spans Data, IT, and Software & Product Development—and the Generative AI skills becoming essential for every role.

 
© 2025 | Daniel Christian