“The Value of Doing Things: What AI Agents Mean for Teachers” — from nickpotkalitsky.substack.com by guest author Jason Gulya, Professor of English and Applied Media at Berkeley College in New York City

AI Agents make me nervous. Really nervous.

I wish they didn’t.

I wish I could write that the last two years have made me more confident, more self-assured that AI is here to augment workers rather than replace them.

But I can’t.

I wish I could write that I know where schools and colleges will end up. I wish I could say that AI Agents will help us get where we need to be.

But I can’t.

At this point, today, I’m at a loss. I’m not sure where the rise of AI agents will take us, in terms of how we work and learn. I’m in the question-asking part of my journey. I have few answers.

So, let’s talk about where (I think) AI Agents will take education. And who knows? Maybe as I write I’ll come up with something more concrete.

It’s worth a shot, right?

From DSC: 
I completely agree with Jason’s following assertion:

A good portion of AI advancement will come down to employee replacement. And AI Agents push companies towards that. 

THAT’s where/what the ROI will be for corporations. They will make their investments up in the headcount area, and likely in other areas as well (product design, marketing campaigns, engineering-related items, and more). But how much time it takes to get there is a big question mark.

One last quote here…it’s too good not to include:

Behind these questions lies a more abstract, more philosophical one: what is the relationship between thinking and doing in a world of AI Agents and other kinds of automation?


How Good are Claude, ChatGPT & Gemini at Instructional Design? — from drphilippahardman.substack.com by Dr Philippa Hardman
A test of AI’s Instruction Design skills in theory & in practice

By examining models across three AI families—Claude, ChatGPT, and Gemini—I’ve started to identify each model’s strengths, limitations, and typical pitfalls.

Spoiler: my findings underscore that until we have specialised, fine-tuned AI copilots for instructional design, we should be cautious about relying on general-purpose models and ensure expert oversight in all ID tasks.


From DSC — I’m going to (have Nick) say this again:
I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing.

Students began mapping out research directions I’d never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns. 


The Digital Literacy Quest: Become an AI Hero — from gamma.app

From DSC:
I have not gone through all of these online-based materials, but I like what they are trying to get at:

  • Confidence with AI
    Students gain practical skills and confidence in using AI tools effectively.
  • Ethical Navigation
    Learn to navigate the ethical landscape of AI with integrity and responsibility. Make informed decisions about AI usage.
  • Mastering Essential Skills
    Develop critical thinking and problem-solving skills in the context of AI.

 


Expanding access to the Gemini app for teen students in education — from workspaceupdates.googleblog.com

Google Workspace for Education admins can now turn on the Gemini app with added data protection as an additional service for their teen users (ages 13+ or the applicable age in your country) in the following languages and countries. With added data protection, chats are not reviewed by human reviewers or otherwise used to improve AI models. The Gemini app will be a core service in the coming weeks for Education Standard and Plus users, including teens,


5 Essential Questions Educators Have About AI  — from edsurge.com by Annie Ning

Recently, I spoke with several teachers regarding their primary questions and reflections on using AI in teaching and learning. Their thought-provoking responses challenge us to consider not only what AI can do but what it means for meaningful and equitable learning environments. Keeping in mind these reflections, we can better understand how we move forward toward meaningful AI integration in education.


FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI — from epoch.ai
FrontierMath presents hundreds of unpublished, expert-level mathematics problems that specialists spend days solving. It offers an ongoing measure of AI complex mathematical reasoning progress.

We’re introducing FrontierMath, a benchmark of hundreds of original, expert-crafted mathematics problems designed to evaluate advanced reasoning capabilities in AI systems. These problems span major branches of modern mathematics—from computational number theory to abstract algebraic geometry—and typically require hours or days for expert mathematicians to solve.


Rising demand for AI courses in UK universities shows 453% growth as students adapt to an AI-driven job market — from edtechinnovationhub.com

The demand for artificial intelligence courses in UK universities has surged dramatically over the past five years, with enrollments increasing by 453%, according to a recent study by Currys, a UK tech retailer.

The study, which analyzed UK university admissions data and surveyed current students and recent graduates, reveals how the growing influence of AI is shaping students’ educational choices and career paths.

This growth reflects the broader trend of AI integration across industries, creating new opportunities while transforming traditional roles. With AI’s influence on career prospects rising, students and graduates are increasingly drawn to AI-related courses to stay competitive in a rapidly changing job market.

 

Is Generative AI and ChatGPT healthy for Students? — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky
Beyond Text Generation: How AI Ignites Student Discovery and Deep Thinking, according to firsthand experiences of Teachers and AI researchers like Nick Potkalitsky.

After two years of intensive experimentation with AI in education, I am witnessing something amazing unfolding before my eyes. While much of the world fixates on AI’s generative capabilities—its ability to create essays, stories, and code—my students have discovered something far more powerful: exploratory AI, a dynamic partner in investigation and critique that’s transforming how they think.

They’ve moved beyond the initial fascination with AI-generated content to something far more sophisticated: using AI as an exploratory tool for investigation, interrogation, and intellectual discovery.

Instead of the much-feared “shutdown” of critical thinking, we’re witnessing something extraordinary: the emergence of what I call “generative thinking”—a dynamic process where students learn to expand, reshape, and evolve their ideas through meaningful exploration with AI tools. Here I consciously reposition the term “generative” as a process of human origination, although one ultimately spurred on by machine input.


A Road Map for Leveraging AI at a Smaller Institution — from er.educause.edu by Dave Weil and Jill Forrester
Smaller institutions and others may not have the staffing and resources needed to explore and take advantage of developments in artificial intelligence (AI) on their campuses. This article provides a roadmap to help institutions with more limited resources advance AI use on their campuses.

The following activities can help smaller institutions better understand AI and lay a solid foundation that will allow them to benefit from it.

  1. Understand the impact…
  2. Understand the different types of AI tools…
  3. Focus on institutional data and knowledge repositories…

Smaller institutions do not need to fear being left behind in the wake of rapid advancements in AI technologies and tools. By thinking intentionally about how AI will impact the institution, becoming familiar with the different types of AI tools, and establishing a strong data and analytics infrastructure, institutions can establish the groundwork for AI success. The five fundamental activities of coordinating, learning, planning and governing, implementing, and reviewing and refining can help smaller institutions make progress on their journey to use AI tools to gain efficiencies and improve students’ experiences and outcomes while keeping true to their institutional missions and values.

Also from Educause, see:


AI school opens – learners are not good or bad but fast and slow — from donaldclarkplanb.blogspot.com by Donald Clark

That is what they are doing here. Lesson plans focus on learners rather than the traditional teacher-centric model. Assessing prior strengths and weaknesses, personalising to focus more on weaknesses and less on things known or mastered. It’s adaptive, personalised learning. The idea that everyone should learn at the exactly same pace, within the same timescale is slightly ridiculous, ruled by the need for timetabling a one to many, classroom model.

For the first time in the history of our species we have technology that performs some of the tasks of teaching. We have reached a pivot point where this can be tried and tested. My feeling is that we’ll see a lot more of this, as parents and general teachers can delegate a lot of the exposition and teaching of the subject to the technology. We may just see a breakthrough that transforms education.


Agentic AI Named Top Tech Trend for 2025 — from campustechnology.com by David Ramel

Agentic AI will be the top tech trend for 2025, according to research firm Gartner. The term describes autonomous machine “agents” that move beyond query-and-response generative chatbots to do enterprise-related tasks without human guidance.

More realistic challenges that the firm has listed elsewhere include:

    • Agentic AI proliferating without governance or tracking;
    • Agentic AI making decisions that are not trustworthy;
    • Agentic AI relying on low-quality data;
    • Employee resistance; and
    • Agentic-AI-driven cyberattacks enabling “smart malware.”

Also from campustechnology.com, see:


Three items from edcircuit.com:


All or nothing at Educause24 — from onedtech.philhillaa.com by Kevin Kelly
Looking for specific solutions at the conference exhibit hall, with an educator focus

Here are some notable trends:

  • Alignment with campus policies: …
  • Choose your own AI adventure: …
  • Integrate AI throughout a workflow: …
  • Moving from prompt engineering to bot building: …
  • More complex problem-solving: …


Not all AI news is good news. In particular, AI has exacerbated the problem of fraudulent enrollment–i.e., rogue actors who use fake or stolen identities with the intent of stealing financial aid funding with no intention of completing coursework.

The consequences are very real, including financial aid funding going to criminal enterprises, enrollment estimates getting dramatically skewed, and legitimate students being blocked from registering for classes that appear “full” due to large numbers of fraudulent enrollments.


 

 

How Legal Education Must Evolve In The Age Of AI: Insights From An In-House Legal Innovator — from by abovethelaw.com Olga Mack
Traditional legal education has remained largely unchanged for decades, focusing heavily on theoretical knowledge and case law analysis.

As we stand on the brink of a new era defined by artificial intelligence (AI) and data-driven decision-making, the question arises: How should legal education adapt to prepare the next generation of lawyers for the challenges ahead?

Here are three unconventional, actionable insights from our conversation that highlight the need for a radical rethinking of legal education.

  1. Integrate AI Education Into Every Aspect Of Legal Training…
  2. Adopt A ‘Technology-Agnostic’ Approach To AI Training…
  3. Redefine Success In Legal Education To Include Technological Proficiency…
 

Boosting Student Engagement with Interactive and Practical Teaching Methods — from campustechnology.com by Dr. Lucas Long

One of my biggest goals as an educator is to show students how the material they learn in class can be applied to real-world situations. In my finance courses, this often means taking what we’re learning about financial calculations and connecting it to decisions they’ll have to make as adults. For example, I’ve used real-life scenarios like buying a car with a loan, paying off student debt, saving for a wedding, or calculating mortgage payments for a future home purchase. I even use salary data to show students what they could realistically afford given average salaries after graduation, helping them relate to the financial decisions they will face after college.

These practical examples don’t just keep students engaged; they also demonstrate the immediate value of learning financial principles. I often hear students express frustration when they feel like they’re learning concepts that won’t apply to their lives. But when I use real scenarios and provide tools like financial calculators to show them exactly how they’ll use this knowledge in their future, their attitude changes. They become more motivated to engage with the material because they see its relevance beyond the classroom.

 

Undergraduate enrollment rises 3% despite drop in first-year students, early data shows — from highereddive.com by Laura Spitalniak
Headcounts declined among students attending college directly after high school, the National Student Clearinghouse Research Center found.

Dive Brief:

  • Undergraduate enrollment rose this fall for the second year in a row, up 3% compared to similar early data from fall 2023, according to preliminary figures released Wednesday by the National Student Clearinghouse Research Center.
  • Enrollment jumped 1.9% in bachelor’s degree programs and 4.3% in those for associate degrees. While all credential types saw gains, the number of undergraduate certificate seekers increased the most, at 7.3%.
  • However, enrollment among first-year students shrank 5%, the first dip since the decline seen at the start of the pandemic. Declining enrollment among 18-year-olds — a proxy for students who attend college directly after high school — accounted for most of that drop, the clearinghouse said.

What preliminary enrollment data from fall 2024 tells us — from highereddive.com by Laura Spitalniak
Higher education experts broke down some trends in the early data and what may have prompted the decline in first-year students.

Higher education news tends to be a mixed bag, and the most recent enrollment report from the National Student Clearinghouse Research Center is no exception.

Last week, the clearinghouse released preliminary findings for fall 2024 and found that undergraduate enrollment rose 3% compared with early data from last year. On the other hand, it showed enrollment among first-year students dropped 5% compared with the year before, the first decline since the drop at the start of the pandemic.

The youngest adults, 18-year-olds, drove a majority of the decrease, according to the clearinghouse. Its researchers used this group as a proxy for students who enroll in postsecondary education directly after they graduate high school, it said.

 

AI Tutors Double Rates of Learning in Less Learning Time — by drphilippahardman.substack.com Dr. Philippa Hardman
Inside Harvard’s new groundbreaking study

Conclusion
This Harvard study provides robust evidence that AI tutoring, when thoughtfully designed, can significantly enhance learning outcomes. The combination of doubled learning gains, increased engagement, and reduced time to competency suggests we’re seeing just the beginning of AI’s potential in education and that its potential is significant.

If this data is anything to go by, and if we – as humans – are open and willing to acting on it, it’s possible AI will have a significant and for some deeply positive impact on how we design and deliver learning experiences.

That said, as we look forward, the question shouldn’t just be, “how AI can enhance current educational methods?”, but also “how it might AI transform the very nature of learning itself?”. With continued research and careful implementation, we could be moving toward an era of education that’s more effective but also more accessible than ever before.


Three Quick Examples of Teaching with and about Generative AI — from derekbruff.org Derek Bruff

  • Text-to-Podcast.
  • Assigning Students to Groups.
  • AI Acceptable Use Scale.

Also from Derek’s blog, see:


From Mike Sharples on LinkedIn: 


ChatGPT’s free voice wizard — from wondertools.substack.com by Jeremy Caplan
How and why to try the new Advanced Voice Mode

7 surprisingly practical ways to use voice AI
Opening up ChatGPT’s Advanced Voice Mode (AVM) is like conjuring a tutor eager to help with whatever simple — or crazy — query you throw at it. Talking is more fluid and engaging than typing, especially if you’re out and about. It’s not a substitute for human expertise, but AVM provides valuable machine intelligence.

  • Get a virtual museum tour. …
  • Chat with historical figures….
  • Practice languages. …
  • Explore books. …
  • Others…


Though not AI-related, this is along the lines of edtech:


…which links to:

 

2025 EDUCAUSE Top 10: Restoring Trust — from educause.edu

Higher education has a trust problem. In the past ten years, the share of Americans who are confident in higher education has dropped from 57 percent to 36 percent.

Colleges and universities need to show that they understand and care about students, faculty, staff, and community members, AND they need to work efficiently and effectively.

Technology leaders can help. The 2025 EDUCAUSE Top 10 describes how higher education technology and data leaders and professionals can help to restore trust in the sector by building competent and caring institutions and, through radical collaboration, leverage the fulcrum of leadership to maintain balance between the two.

.

 

The Uberfication of Higher Ed — from evolllution.com by Robert Ubell | Vice Dean Emeritus of Online Learning in the School of Engineering, New York University
As the world of work increasingly relies on the gig economy, higher ed is no different. Many institutions seek to drive down labor costs by hiring contingent works, thereby leaving many faculty in a precarious position and driving down the quality of education.

While some of us are aware that higher ed has been steadily moving away from employing mostly full-time, tenured and tenure-track faculty, replacing them with a part-time, contingent academic workforce, the latest AAUP report issued this summer shows the trend is accelerating. Precarious college teachers have increased by nearly 300,000 over the last decade, as conventional faculty employment stays pretty much flat. It’s part of a national trend in the wider economy that replaces permanent workers with lower paid, contingent staff—members of what we now call the gig economy.

The wide disparity is among the most glaring dysfunctions—along with vast student debt, falling enrollment, rising tuition and other dangers afflicting higher education—but it’s the least acknowledged. Rarely, if ever, does it take its place among the most troubling ails of academic life. It’s a silent disease, its symptoms largely ignored for over half a century.

Do families who send their kids to college, paying increasingly stiff tuition, realize that most of the faculty at our universities are as precarious as Uber drivers?

Everyone at the table was taken aback, totally surprised, a sign—even if anecdotal—that this dirty secret is pretty safe. Mass participation of contingent faculty at our universities remains largely obscure, wrapped in a climate of silence, with adjunct faculty perpetuating the quiet by leaving their students mostly uninformed about their working conditions.  

 

From DSC:
The following reflections were catalyzed by Jeff Selingo’s Next posting from 10/22, specifically the item:

  • Student fees for athletics, dark money in college sports, and why this all matters to every student, every college.

All of this has big risks for institutions. But whenever I talk to faculty and administrators on campuses about this, many will wave me away and say, “Well, I’m not a college sports fan” or “We’re a Division III school, so that all this doesn’t impact us.”

Nothing is further from the truth, as we explored on a recent episode of the Future U. podcast, where we welcomed in Matt Brown, editor of the Extra Points newsletter, which looks at academic and financial issues in college sports.

As we learned, despite the siloed nature of higher ed, everything is connected to athletics: research, academics, market position. Institutions can rise and fall on the backs of their athletics programs – and we’re not talking about wins and losses, but real budget dollars.

And if you want to know about the impact on students, look no further than the news out of Clemson this week. It is following several other universities in adopting an “athletics fee”: $300 a year. It won’t be the last.  

Give a listen to this episode of Future U. if you want to catch up quick on this complicated subject, and while you’re at it, subscribe wherever you get your podcasts.


Clemson approves new athletics fee for students. Here’s what we know — from sports.yahoo.com by Chapel Fowler
How much are student fees at other schools?

That’s true in the state of South Carolina, when comparing the annual fees of Clemson ($300) and USC ($172) to Coastal Carolina ($2,090). And it holds up nationally, too.



From DSC:
The Bible talks a lot about idols….and I can’t help but wonder, have sports become an idol in our nation?

Don’t get me wrong. Sports can and should be fun for us to play. I played many an hour of sports in my youth and I occasionally play some sports these days. Plus, sports are excellent for helping us keep in shape and take care of our bodies. Sports can help us connect with others and make some fun/good memories with our friends.

So there’s much good to playing sports. But have we elevated sports to places they were never meant to be? To roles they were never meant to play?

 

Micro-Credentials Impact Report 2024: US Edition — from coursera.org

Perspectives from higher education leaders in the United States

97% of US leaders offering micro-credentials say they strengthen students’ long-term career outcomes. Discover micro-credentials’ positive impact on students and institutions, and how they:

  • Equip students for today’s and tomorrow’s job markets
  • Augment degree value with for-credit credentials
  • Boost student engagement and retention rates
  • Elevate institutional brand in the educational landscape

Ninety-seven percent of US campus leaders offering micro-credentials say these credentials strengthen students’ long-term career outcomes. Additionally, 95% say they will be an important part of higher education in the near future.1

Over half (58%) of US leaders say their institutions are complementing their curriculum with micro-credentials, allowing students to develop applicable, job-ready skills while earning their degree.

 

Half of Higher Ed Institutions Now Use AI for Outcomes Tracking, But Most Lag in Implementing Comprehensive Learner Records — from prnewswire.com; via GSV

SALT LAKE CITY, Oct. 22, 2024 /PRNewswire/ — Instructure, the leading learning ecosystem and UPCEA, the online and professional education association, announced the results of a survey on whether institutions are leveraging AI to improve learner outcomes and manage records, along with the specific ways these tools are being utilized. Overall, the study revealed interest in the potential of these technologies is far outpacing adoption. Most respondents are heavily involved in developing learner experiences and tracking outcomes, though nearly half report their institutions have yet to adopt AI-driven tools for these purposes. The research also found that only three percent of institutions have implemented Comprehensive Learner Records (CLRs), which provide a complete overview of an individual’s lifelong learning experiences.


New Survey Says U.S. Teachers Colleges Lag on AI Training. Here are 4 Takeaways — from the74million.org by ; via GSV
Most preservice teachers’ programs lack policies on using AI, CRPE finds, and are likely unready to teach future educators about the field.

In the nearly two years since generative artificial intelligence burst into public consciousness, U.S. schools of education have not kept pace with the rapid changes in the field, a new report suggests.

Only a handful of teacher training programs are moving quickly enough to equip new K-12 teachers with a grasp of AI fundamentals — and fewer still are helping future teachers grapple with larger issues of ethics and what students need to know to thrive in an economy dominated by the technology.

The report, from the Center on Reinventing Public Education, a think tank at Arizona State University, tapped leaders at more than 500 U.S. education schools, asking how their faculty and preservice teachers are learning about AI. Through surveys and interviews, researchers found that just one in four institutions now incorporates training on innovative teaching methods that use AI. Most lack policies on using AI tools, suggesting that they probably won’t be ready to teach future educators about the intricacies of the field anytime soon.



The 5 Secret Hats Teachers are Wearing Right Now (Thanks to AI!) — from aliciabankhofer.substack.com by Alicia Bankhofer
New, unanticipated roles for educators sitting in the same boat

As beta testers, we’re shaping the tools of tomorrow. As researchers, we’re pioneering new pedagogical approaches. As ethical guardians, we’re ensuring that AI enhances rather than compromises the educational experience. As curators, we’re guiding students through the wealth of information AI provides. And as learners ourselves, we’re staying at the forefront of educational innovation.


 

 

Freshman Enrollment Appears to Decline for the First Time Since 2020 — from nytimes.com by Zach Montague (behind paywall)
A projected 5 percent drop in this year’s freshman class follows a number of disruptions last year, including persistent failures with the FAFSA form.

Freshman enrollment dropped more than 5 percent from last year at American colleges and universities, the largest decline since 2020 when Covid-19 and distance learning upended higher education, according to preliminary data released on Wednesday by the National Student Clearinghouse Research Center, a nonprofit education group.

The finding comes roughly a year after the federal student aid system was dragged down by problems with the Free Application for Federal Student Aid form, commonly known as FAFSA, which led to maddening delays this year in processing families’ financial data to send to school administrators. That in turn held up the rollout of financial aid offers well into the summer, leaving many families struggling to determine how much college would cost.


Re: the business of higher ed, also see:

Tracking college closures— from hechingerreport.org by Marina Villeneuve and Olivia Sanchez
More colleges are shutting down as enrollment drops

College enrollment has been declining for more than a decade, and that means that many institutions are struggling to pay their bills. A growing number of them are making the difficult decision to close.

In the first nine months of 2024, 28 degree-granting institutions closed, compared with 15 in all of 2023, according to an analysis of federal data provided to The Hechinger Report by the State Higher Education Executive Officers Association or SHEEO.

And when colleges close, it hurts the students who are enrolled. At the minimum, colleges that are shutting down should notify students at least three months in advance, retain their records and refund tuition, experts say. Ideally, it should form an agreement with a nearby school and make it easy for students to continue their education.

 


Are ChatGPT, Claude & NotebookLM *Really* Disrupting Education? — from drphilippahardman.substack.com
Evaluating Gen AI’s *real* impact on human learning

The TLDR here is that, as useful as popular AI tools are for learners, as things stand they only enable us to take the very first steps on what is a long and complex journey of learning.

AI tools like ChatGPT 4o, Claude 3.5 & NotebookLM can help to give us access to information but (for now at least) the real work of learning remains in our – the humans’ – hands.


To which Anna Mills had a solid comment:

It might make a lot of sense to regulate generated audio to require some kind of watermark and/or metadata. Instructors who teach online and assign voice recordings, we need to recognize that these are now very easy and free to auto-generate. In some cases we are assigning this to discourage students from using AI to just autogenerate text responses, but audio is not immune.




 

New Study Reveals Keys to Re-Engaging the 41.9 Million Americans with Some College, but No Credential — from globenewswire.com by StraighterLine
Students’ Perception of the Value of a Degree Drops 50% After Stopping Out

Key Findings Included:

  • Financial Barriers Remain Significant. 58% of respondents note their current financial situation would not allow them to afford college tuition and related expenses. 72% cite affordable tuition or cost of the program as a necessary factor for re-enrollment.
  • Shifting Perceptions of Degree Value. While 84% of respondents believed they needed a degree to achieve their professional goals before first enrolling, only 34% still hold that belief.
  • Trust Deficit in Higher Education. Only 42% of respondents agree that colleges and universities are trustworthy, underscoring a trust deficit that institutions must address.
  • Key Motivators for Re-enrollment. Salary improvement (53%), personal goals (44%), and career change (38%) are the top motivators for potential re-enrollment.
  • Predicting Readiness to Re-enroll. The top three factors predicting adult learners’ readiness to re-enroll are mental resilience and routine readiness, positive opinions on institutional trustworthiness and communication, and belief in the value of a degree.
  • Communication Preferences. 86% of respondents prefer email communication when inquiring about programs, with minimal interest in chatbots (6%).
 


Articulate AI & the “Buttonification” of Instructional Design — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new trend in AI-UX, and its implications for Instructional Design

1. Using AI to Scale Exceptional Instructional Design Practice
Imagine a bonification system that doesn’t just automate tasks, but scales best practices in instructional design:

  • Evidence-Based Design Button…
  • Learner-Centered Objectives Generator…
    Engagement Optimiser…

2. Surfacing AI’s Instructional Design Thinking
Instead of hiding AI’s decision-making process, what if we built an AI system which invites instructional designers to probe, question, and learn from an expert trained AI?

  • Explain This Design…
  • Show Me Alternatives…
  • Challenge My Assumptions…
  • Learning Science Insights…

By reimagining the role of AI in this way, we would…


Recapping OpenAI’s Education Forum — from marcwatkins.substack.com by Marc Watkins

OpenAI’s Education Forum was eye-opening for a number of reasons, but the one that stood out the most was Leah Belsky acknowledging what many of us in education had known for nearly two years—the majority of the active weekly users of ChatGPT are students. OpenAI has internal analytics that track upticks in usage during the fall and then drops off in the spring. Later that evening, OpenAI’s new CFO, Sarah Friar, further drove the point home with an anecdote about usage in the Philippines jumping nearly 90% at the start of the school year.

I had hoped to gain greater insight into OpenAI’s business model and how it related to education, but the Forum left me with more questions than answers. What app has the majority of users active 8 to 9 months out of the year and dormant for the holidays and summer breaks? What business model gives away free access and only converts 1 out of every 20-25 users to paid users? These were the initial thoughts that I hoped the Forum would address. But those questions, along with some deeper and arguably more critical ones, were skimmed over to drive home the main message of the Forum—Universities have to rapidly adopt AI and become AI-enabled institutions.


Off-Loading in the Age of Generative AI — from insidehighered.com by James DeVaney

As we embrace these technologies, we must also consider the experiences we need to discover and maintain our connections—and our humanity. In a world increasingly shaped by AI, I find myself asking: What are the experiences that define us, and how do they influence the relationships we build, both professionally and personally?

This concept of “off-loading” has become central to my thinking. In simple terms, off-loading is the act of delegating tasks to AI that we would otherwise do ourselves. As AI systems advance, we’re increasingly confronted with a question: Which tasks should we off-load to AI?

 
© 2024 | Daniel Christian