May Brought Deep Cuts at Multiple Colleges — from insidehighered.com by Josh Moody Colleges laid off well over 800 employees last month due to a mix of enrollment challenges and state funding issues. Ivy Tech saw the deepest cuts with more than 200 jobs axed.
With the academic year coming to an end, multiple universities announced deep cuts in May, shedding dozens of jobs amid financial pressures often linked to enrollment shortfalls.
…
But the cuts below, for the most part, are not directly tied to the rapid-fire actions of the Trump administration but rather stem from other financial pressures weighing on the sector. Many of the institutions listed are contending with declining enrollment and, for public universities, shrinking state support, which has necessitated fiscal changes.
From DSC: I survived several job reductions at one of my former workplaces. But I didn’t survive the one that laid off 12 staff members after the Spring 2017 Semester. So, more and more, faculty and staff have been starting to dread the end of the academic year — as they may not survive another round of cuts.
She recognized their desperation and felt called to return and use what she had learned to help them realize a different future. So she set up an organization, HeartSmiles, to do just that — one young person at a time.
Holifield’s experience is one that city officials and public health workers can learn from. If they want to disrupt the generational cycle of poverty, trauma and hopelessness that afflicts so many communities, a good place to focus their efforts is children.
… How can communities overcome inertia and resignation? Holifield’s organization starts with two core interventions. The first is career and leadership development. Children as young as 8 go to the HeartSmiles center to participate in facilitated sessions on youth entrepreneurship, budgeting and conflict resolution. Those who want to explore certain career paths are matched with professionals in these fields.
… The second part of her vision is youth-led mentorship, which involves pairing young people with those not much older than they are.
This week, we’re publishing Part 2 of a Q&A with Erik Maloney, a lifer in Arizona, and Kevin Wright, a criminal justice professor at Arizona State University. They co-authored Imprisoned Minds, a book about trauma and healing published in December 2024, over the course of seven years. Check out Part 1 of the Q&A.
West: The fact that you created your own curriculum to accompany the book makes me think about the role of lifers in creating educational opportunities in prisons. What do you see as the role of lifers in filling some of these gaps?
Maloney: I’ve said for years that lifers are so underutilized in prison. It’s all about punishment for what you’re in for, and [the prison system] overlooks us as a resource. We are people who, if allowed to be educated properly, can teach courses indefinitely while also being a role model for those with shorter sentences. This gives the lifer meaning and purpose to do good again. He serves as a mentor, whether he likes it or not, to [those] people coming into the prisons. When they see him doing well, it inspires others to want to do well.
But if it’s all about punishment, and a person has no meaning and no purpose in life, then all they have is hopelessness. With hopelessness comes despair, and with despair, you have rampant drug and alcohol abuse in prison, and violence stems from that.
How do we reconcile the first three points with the final one? The answer is that AI use that boosts individual performance does not naturally translate to improving organizational performance. To get organizational gains requires organizational innovation, rethinking incentives, processes, and even the nature of work. But the muscles for organizational innovation inside companies have atrophied. For decades, companies have outsourced this to consultants or enterprise software vendors who develop generalized approaches that address the issues of many companies at once. That won’t work here, at least for a while. Nobody has special information about how to best use AI at your company, or a playbook for how to integrate it into your organization. .
Today we are excited to launch Galileo Learn™, a revolutionary new platform for corporate learning and professional development.
…
How do we leverage AI to revolutionize this model, doing away with the dated “publishing” model of training?
The answer is Galileo Learn, a radically new and different approach to corporate training and professional development.
…
What Exactly is Galileo Learn™? Galileo Learn is an AI-native learning platform which is tightly integrated into the Galileo agent. It takes content in any form (PDF, word, audio, video, SCORM courses, and more) and automatically (with your guidance) builds courses, assessments, learning programs, polls, exercises, simulations, and a variety of other instructional formats.
Centering Public Understanding in AI Education
In a recent talk titled “Designing an Ecosystem of Resources to Foster AI Literacy,” Duri Long, Assistant Professor at Northwestern University, highlighted the growing need for accessible, engaging learning experiences that empower the public to make informed decisions about artificial intelligence. Long emphasized that as AI technologies increasingly influence everyday life, fostering public understanding is not just beneficial—it’s essential. Her work seeks to develop a framework for AI literacy across varying audiences, from middle school students to adult learners and journalists.
A Design-Driven, Multi-Context Approach
Drawing from design research, cognitive science, and the learning sciences, Long presented a range of educational tools aimed at demystifying AI. Her team has created hands-on museum exhibits, such as Data Bites, where learners build physical datasets to explore how computers learn. These interactive experiences, along with web-based tools and support resources, are part of a broader initiative to bridge AI knowledge gaps using the 4As framework: Ask, Adapt, Author, and Analyze. Central to her approach is the belief that familiar, tangible interactions and interfaces reduce intimidation and promote deeper engagement with complex AI concepts.
There are growing signs that artificial intelligence poses a real threat to a substantial number of the jobs that normally serve as the first step for each new generation of young workers. Uncertainty around tariffs and global trade is likely to only accelerate that pressure, just as millions of 2025 graduates enter the work force.
…
Breaking first is the bottom rung of the career ladder. In tech, advanced coding tools are creeping into the tasks of writing simple code and debugging — the ways junior developers gain experience. In law firms, junior paralegals and first-year associates who once cut their teeth on document review are handing weeks of work over to A.I. tools to complete in a matter of hours. And across retailers, A.I. chatbots and automated customer service tools are taking on duties once assigned to young associates.
Anthropic’s “Prompt Engineering Overview” is a free masterclass that’s worth its weight in gold. Their “constitutional AI prompting” section helped us create a content filter that actually works—unlike the one that kept flagging our coffee bean reviews as “inappropriate.” Apparently “rich body” triggered something…
OpenAI’s “Cookbook” is like having a Michelin-star chef explain cooking—simple for beginners, but packed with pro techniques. Their JSON formatting examples saved us 3 hours of debugging last week…
Google’s “Prompt Design Strategies” breaks down complex concepts with clear examples. Their before/after gallery showing how slight prompt tweaks improve results made us rethink everything we knew about getting quality outputs.
Pro tip: Save these guides as PDFs before they disappear behind paywalls. The best AI users keep libraries of these resources for quick reference. .
“To address this, organizations should consider building a sustainable AI governance model, prioritizing transparency, and tackling the complex challenge of AI-fueled imposter syndrome through reinvention. Employers who fail to approach innovation with empathy and provide employees with autonomy run the risk of losing valuable staff and negatively impacting employee productivity.”
Key findings from the report include the following:
Employees are keeping their productivity gains a secret from their employers. …
In-office employees may still log in remotely after hours. …
Younger workers are more likely to switch jobs to gain more flexibility.
AI discovers new math algorithms— from by Zach Mink & Rowan Cheung PLUS: Anthropic reportedly set to launch new Sonnet, Opus models
The Rundown: Google just debuted AlphaEvolve, a coding agent that harnesses Gemini and evolutionary strategies to craft algorithms for scientific and computational challenges — driving efficiency inside Google and solving historic math problems.
… Why it matters: Yesterday, we had OpenAI’s Jakub Pachocki saying AI has shown “significant evidence” of being capable of novel insights, and today Google has taken that a step further. Math plays a role in nearly every aspect of life, and AI’s pattern and algorithmic strengths look ready to uncover a whole new world of scientific discovery.
At the recent HR Executive and Future Talent Council event at Bentley University near Boston, I talked with Top 100 HR Tech Influencer Joey Price about what he’s hearing from HR leaders. Price is president and CEO of Jumpstart HR and executive analyst at Aspect43, Jumpstart HR’s HR?tech research division, and author of a valuable new book, The Power of HR: How to Make an Organizational Impact as a People?Professional.
This puts him solidly at the center of HR’s most relevant conversations. Price described the curiosity he’s hearing from many HR leaders about AI agents, which have become increasingly prominent in recent months.
Global leader brings its trusted brand and powerful network to enable payments with new technologies
Launches new innovations and partnerships to drive flexibility, security and acceptance
SAN FRANCISCO–(BUSINESS WIRE)–The future of commerce is on display at the Visa Global Product Drop with powerful AI-enabled advancements allowing consumers to find and buy with AI plus the introduction of new strategic partnerships and product innovations.
Collaborates with Anthropic, IBM, Microsoft, Mistral AI, OpenAI, Perplexity, Samsung, Stripe and more
Will make shopping experiences more personal, more secure and more convenient as they become powered by AI
Introduced [on April 30th] at the Visa Global Product Drop, Visa Intelligent Commerce enables AI to find and buy. It is a groundbreaking new initiative that opens Visa’s payment network to the developers and engineers building the foundational AI agents transforming commerce.
In today’s newsletter, I’m unpacking why your next major buyers won’t be people at all. They’ll be AI agents, and your brand might already be invisible to them. We’ll dig into why traditional marketing strategies are breaking down in the age of autonomous AI shoppers, what “AI optimization” (AIO) really means, and the practical steps you can take right now to make sure your business stays visible and competitive as the new digital gatekeepers take over more digital tasks.
AI platforms and AI agents—the digital assistants that browse and actually do things powered by models like GPT-4o, Claude 3.7 Sonnet, and Gemini 2.5 Pro—are increasingly becoming the gatekeepers between your business and potential customers.
…
“AI is the new front door to your business for millions of consumers.”
The 40-Point (ish) AI Agent Marketing Playbook
Here’s the longer list. I went ahead and broke these into four categories so you can more easily assign owners: Content, Structure & Design, Technical & Dev, and AI Strategy & Testing. I look forward to seeing how this space, and by extension my advice, changes in the coming months.
During a fireside chat with Meta CEO Mark Zuckerberg at Meta’s LlamaCon conference on Tuesday, Microsoft CEO Satya Nadella said that 20% to 30% of code inside the company’s repositories was “written by software” — meaning AI.
In just six months, the consumer AI landscape has been redrawn. Some products surged, others stalled, and a few unexpected players rewrote the leaderboard overnight. Deepseek rocketed from obscurity to a leading ChatGPT challenger. AI video models advanced from experimental to fairly dependable (at least for short clips!). And so-called “vibe coding” is changing who can create with AI, not just who can use it. The competition is tighter, the stakes are higher, and the winners aren’t just launching, they’re sticking.
We turned to the data to answer: Which AI apps are people actively using? What’s actually making money, beyond being popular? And which tools are moving beyond curiosity-driven dabbling to become daily staples?
This is the fourth installment of the Top 100 Gen AI Consumer Apps, our bi-annual ranking of the top 50 AI-first web products (by unique monthly visits, per Similarweb) and top 50 AI-first mobile apps (by monthly active users, per Sensor Tower). Since our last report in August 2024, 17 new companies have entered the rankings of top AI-first web products.
The AI search landscape is transforming at breakneck speed. New “Deep Research” tools from ChatGPT, Gemini and Perplexity autonomously search and gather information from dozens — even hundreds — of sites, then analyze and synthesize it to produce comprehensive reports. While a human might take days or weeks to produce these 30-page citation-backed reports, AI Deep Research reports are ready in minutes.
What’s in this post
Examples of each report type I generated for my research, so you can form your own impressions.
Tips on why & how to use Deep Research and how to craft effective queries.
Comparison of key features and strengths/limitations of the top platforms
As AI agents transition from experimental systems to production-scale applications, their growing autonomy introduces novel security challenges. In a comprehensive new report, “AI Agents Are Here. So Are the Threats,” Palo Alto Networks’ Unit 42 reveals how today’s agentic architectures—despite their innovation—are vulnerable to a wide range of attacks, most of which stem not from the frameworks themselves, but from the way agents are designed, deployed, and connected to external tools.
To evaluate the breadth of these risks, Unit 42 researchers constructed two functionally identical AI agents—one built using CrewAI and the other with AutoGen. Despite architectural differences, both systems exhibited the same vulnerabilities, confirming that the underlying issues are not framework-specific. Instead, the threats arise from misconfigurations, insecure prompt design, and insufficiently hardened tool integrations—issues that transcend implementation choices.
LLMs Can Learn Complex Math from Just One Example: Researchers from University of Washington, Microsoft, and USC Unlock the Power of 1-Shot Reinforcement Learning with Verifiable Reward — from marktechpost.com by Sana Hassan
DC: THIS could unfortunately be the ROI companies will get from large investments in #AI — reduced headcount/employees/contract workers. https://t.co/zEWlqCSWzI
Duolingo will “gradually stop using contractors to do work that AI can handle,” according to an all-hands email sent by cofounder and CEO Luis von Ahn announcing that the company will be “AI-first.” The email was posted on Duolingo’s LinkedIn account.
According to von Ahn, being “AI-first” means the company will “need to rethink much of how we work” and that “making minor tweaks to systems designed for humans won’t get us there.” As part of the shift, the company will roll out “a few constructive constraints,” including the changes to how it works with contractors, looking for AI use in hiring and in performance reviews, and that “headcount will only be given if a team cannot automate more of their work.”
Something strange, and potentially alarming, is happening to the job market for young, educated workers.
According to the New York Federal Reserve, labor conditions for recent college graduates have “deteriorated noticeably” in the past few months, and the unemployment rate now stands at an unusually high 5.8 percent. Even newly minted M.B.A.s from elite programs are struggling to find work. Meanwhile, law-school applications are surging—an ominous echo of when young people used graduate school to bunker down during the great financial crisis.
What’s going on? I see three plausible explanations, and each might be a little bit true.
The new workplace trend is not employee friendly. Artificial intelligence and automation technologies are advancing at blazing speed. A growing number of companies are using AI to streamline operations, cut costs, and boost productivity. Consequently, human workers are facing facing layoffs, replaced by AI. Like it or not, companies need to make tough decisions, including layoffs to remain competitive.
Corporations including Klarna, UPS, Duolingo, Intuit and Cisco are replacing laid-off workers with AI and automation. While these technologies enhance productivity, they raise serious concerns about future job security. For many workers, there is a big concern over whether or not their jobs will be impacted.
Key takeaway: Career navigation has remained largely unchanged for decades, relying on personal networks and static job boards. The advent of AI is changing this, offering personalised career pathways, better job matching, democratised job application support, democratised access to career advice/coaching, and tailored skill development to help you get to where you need to be.Hundreds of millions of people start new jobs every year, this transformation opens up a multi-billion dollar opportunity for innovation in the global career navigation market.
…
A.4 How will AI disrupt this segment? Personalised recommendations: AI can consume a vast amount of information (skills, education, career history, even youtube history, and x/twitter feeds), standardise this data at scale, and then use data models to match candidate characteristics to relevant careers and jobs. In theory, solutions could then go layers deeper, helping you position yourself for those future roles. Currently based in Amsterdam, and working in Strategy at Uber and want to work in a Product role in the future? Here are X,Y,Z specific things YOU can do in your role today to align yourself perfectly. E.g. find opportunities to manage cross functional projects in your current remit, reach out to Joe Bloggs also at Uber in Amsterdam who did Strategy and moved to Product, etc.
No matter the school, no matter the location, when I deliver an AI workshop to a group of teachers, there are always at least a few colleagues thinking (and sometimes voicing), “Do I really need to use AI?”
Nearly three years after ChatGPT 3.5 landed in our lives and disrupted workflows in ways we’re still unpacking, most schools are swiftly catching up. Training sessions, like the ones I lead, are springing up everywhere, with principals and administrators trying to answer the same questions: Which tools should we use? How do we use them responsibly? How do we design learning in this new landscape?
But here’s what surprises me most: despite all the advances in AI technology, the questions and concerns from teachers remain strikingly consistent.
…
In this article, I want to pull back the curtain on those conversations. These concerns aren’t signs of reluctance – they reflect sincere feelings. And they deserve thoughtful, honest answers.
This week, in advance of major announcements from us and other vendors, I give you a good overview of the AI Agent market, and discuss the new role of AI governance platforms, AI agent development tools, AI agent vendors, and how AI agents will actually manifest and redefine what we call an “application.”
I discuss ServiceNow, Microsoft, SAP, Workday, Paradox, Maki People, and other vendors. My goal today is to “demystify” this space and explain the market, the trends, and why and how your IT department is going to be building a lot of the agents you need. And prepare for our announcements next week!
DeepSeek has quietly launched Prover V2, an open-source model built to solve math problems using Lean 4 assistant, which ensures every step of a proof is rigorously verified.
What’s impressive about it?
Massive scale: Based on DeepSeek-V3 with 671B parameters using a mixture-of-experts (MoE) architecture, which activates only parts of the model at a time to reduce compute costs.
Theorem solving: Uses long context windows (32K+ tokens) to generate detailed, step-by-step formal proofs for a wide range of math problems — from basic algebra to advanced calculus theorems.
Research grade: Assists mathematicians in testing new theorems automatically and helps students understand formal logic by generating both Lean 4 code and readable explanations.
New benchmark: Introduces ProverBench, a new 325-question benchmark set featuring problems from recent AIME exams and curated academic sources to evaluate mathematical reasoning.
The need for deep student engagement became clear at Dartmouth Geisel School of Medicine when a potential academic-integrity issue revealed gaps in its initial approach to artificial intelligence use in the classroom, leading to significant revisions to ensure equitable learning and assessment.
From George Siemens “SAIL: Transmutation, Assessment, Robots e-newsletter on 5/2/25
All indications are that AI, even if it stops advancing, has the capacity to dramatically change knowledge work. Knowing things matters less than being able to navigate and make sense of complex environments. Put another way, sensemaking, meaningmaking, and wayfinding (with their yet to be defined subelements) will be the foundation for being knowledgeable going forward.
That will require being able to personalize learning to each individual learner so that who they are (not what our content is) forms the pedagogical entry point to learning.(DSC: And I would add WHAT THEY WANT to ACHIEVE.)LLMs are particularly good and transmutation. Want to explain AI to a farmer? A sentence or two in a system prompt achieves that. Know that a learner has ADHD? A few small prompt changes and it’s reflected in the way the LLM engages with learning. Talk like a pirate. Speak in the language of Shakespeare. Language changes. All a matter of a small meta comment send to the LLM. I’m convinced that this capability to change, transmute, information will become a central part of how LLMS and AI are adopted in education.
… Speaking of Duolingo– it took them 12 years to develop 100 courses. In the last year, they developed an additional 148. AI is an accelerant with an impact in education that is hard to overstate. “Instead of taking years to build a single course with humans the company now builds a base course and uses AI to quickly customize it for dozens of different languages.”
FutureHouse is launching our platform, bringing the first publicly available superintelligent scientific agents to scientists everywhere via a web interface and API. Try it out for free at https://platform.futurehouse.org.
MOOC-Style Skills Training— from the-job.beehiiv.com by Paul Fain WGU and tech companies use Open edX for flexible online learning. Could community colleges be next?
Open Source for Affordable Online Reach
The online titan Western Governors University is experimenting with an open-source learning platform. So are Verizon and the Indian government. And the platform’s leaders want to help community colleges take the plunge on competency-based education.
…
The Open edX platform inherently supports self-paced learning and offers several features that make it a good fit for competency-based education and skills-forward learning, says Stephanie Khurana, Axim’s CEO.
“Flexible modalities and a focus on competence instead of time spent learning improves access and affordability for learners who balance work and life responsibilities alongside their education,” she says.
“Plus, being open source means institutions and organizations can collaborate to build and share CBE-specific tools and features,” she says, “which could lower costs and speed up innovation across the field.”
Axim thinks Open edX’s ability to scale affordably can support community colleges in reaching working learners across an underserved market.
We are entering a new reality—one in which AI can reason and solve problems in remarkable ways. This intelligence on tap will rewrite the rules of business and transform knowledge work as we know it. Organizations today must navigate the challenge of preparing for an AI-enhanced future, where AI agents will gain increasing levels of capability over time that humans will need to harness as they redesign their business. Human ambition, creativity, and ingenuity will continue to create new economic value and opportunity as we redefine work and workflows.
As a result, a new organizational blueprint is emerging, one that blends machine intelligence with human judgment, building systems that are AI-operated but human-led. Like the Industrial Revolution and the internet era, this transformation will take decades to reach its full promise and involve broad technological, societal, and economic change.
To help leaders understand how knowledge work will evolve, Microsoft analyzed survey data from 31,000 workers across 31 countries, LinkedIn labor market trends, and trillions of Microsoft 365 productivity signals. We also spoke with AI-native startups, academics, economists, scientists, and thought leaders to explore what work could become. The data and insights point to the emergence of an entirely new organization, a Frontier Firm that looks markedly different from those we know today. Structured around on-demand intelligence and powered by “hybrid” teams of humans + agents, these companies scale rapidly, operate with agility, and generate value faster.
Frontier Firms are already taking shape, and within the next 2–5 years we expect that every organization will be on their journey to becoming one. 82% of leaders say this is a pivotal year to rethink key aspects of strategy and operations, and 81% say they expect agents to be moderately or extensively integrated into their company’s AI strategy in the next 12–18 months. Adoption is accelerating: 24% of leaders say their companies have already deployed AI organization-wide, while just 12% remain in pilot mode.
The time to act is now. The question for every leader and employee is: how will you adapt?
Anthropic expects AI-powered virtual employees to begin roaming corporate networks in the next year, the company’s top security leader told Axios in an interview this week.
Why it matters: Managing those AI identities will require companies to reassess their cybersecurity strategies or risk exposing their networks to major security breaches.
The big picture: Virtual employees could be the next AI innovation hotbed, Jason Clinton, the company’s chief information security officer, told Axios.
A market report from Validated Insights released this month notes that fewer colleges and universities hire external online program management (OPM) companies to develop their courses.
For 2024, higher education institutions launched only 81 new partnerships with OPMs — a drop of 42% and the lowest number since 2016.
The report showed that institutions increasingly pay OPMs a fee-for-service instead of following a revenue-sharing model with big service bundles and profit splits.
Experts say revenue-sharing models, which critics denounce as predatory arrangements, incentivize service providers to use aggressive recruiting tactics to increase enrollments and maximize tuition revenue.
According to the report, fee-for-service has become the dominant business model for OPMs.
While school-led professional development can be helpful, there are online professional learning communities on various edtech websites that can be leveraged. Also, some of these community spaces offer the chance to monetize your work.
Here is a summary of six online edtech professional learning spaces.
Public schools do not work for everyone. But options have increased since 1922, when Oregon tried to ban private education. The Supreme Court shut down that scheme fast. But now, after more than 100 years, political insiders are rallying again to stop a new source of choice.
The target this time is microschooling, a Covid-era alternative that has outlasted the pandemic. Key players in the movement will gather May 8–9, 2025, at the International Microschools Conference in Washington, D.C. I will join them.
Most likely, I will meet educators running all kinds of programs in all kinds of community spaces. Microschools blur the lines between home, public, and private schooling—combining elements from all three models.
The result is a fourth category of schooling that hinges on flexibility. Some parents pool their resources and hire outside instructors. Other groups rotate teaching duties among themselves, gathering daily or perhaps only once or twice per week. These are the do-it-yourselfers. Professionals also get involved with standalone enterprises and national networks.
4 ways community colleges can boost workforce development — from highereddive.com by Natalie Schwartz Higher education leaders at this week’s ASU+GSV Summit gave advice for how two-year institutions can boost the economic mobility of their students.
SAN DIEGO — How can community colleges deliver economic mobility to their students?
College leaders at this week’s ASU+GSV Summit, an annual education and technology conference, got a glimpse into that answer as they heard how community colleges are building support from business and industry and strengthening workforce development.
These types of initiatives may be helping to boost public perception of the value of community colleges vs. four-year institutions.
Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
…
What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
…
Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
…
In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.
Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.
From DSC: I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.
Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.
There are a few places where Scott and I differ.
The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:
To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”
Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”
— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY .
By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.
Also, I would use the term learning preferences where Scott uses the term learning styles.
Scott also mentions:
“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”
It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).
That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.
So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!
Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.
The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.
The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.
So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.
Just keep two big things in mind:
Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.
So, use the tools, find what helps you, but don’t trust them completely.
We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.
This year, two startups ended up with an equal number of votes for the top spot:
Case Crafter, a company from Norway that helps legal professionals build compelling visual timelines based on case files and evidence.
Querious, a product that provides attorneys with real-time insights during client conversations into legal issues, relevant content, and suggested questions and follow-ups. .
DC: If https://t.co/c3Io6EqFds can do this with legal-related conversations, what about with lectures & learning-related applications of this?
Querious transforms client conversations with real-time legal insights while reducing non-billable administrative tasks.#legaltech#AIpic.twitter.com/s0r9o4N89q
The Ontario Bar Association has recently launched a hands-on AI learning platform tailored for lawyers. Called the AI Academy, the initiative is designed to help legal professionals explore, experiment with, and adopt AI tools relevant to their practice.
Colin Lachance, OBA’s innovator-in-residence and the lead designer of the platform, says that although the AI Academy was built for practising lawyers, it is also well-suited for law students.
