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Interview: What Does the ‘I’ in AI Really Mean?
Sara Talpos, Undark, 2026/09/30

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This is a set of interviews with five experts about whether AI can ever match human intelligence. The interviews are relatively short and easy to read, and the content is well-informed. The experts mostly default to the view that 'machine intelligence and human intelligence are fundamentally different' and while they offer explanations of how they differ (eg., as Emily Bender says, in attaching meaning to words) we don't really get any insights on what makes them difference. I suspect that this is because they don't know (eg., how do humans actually attach meaning to words?). My own thought is that human and machine intelligence are fundamentally the same, with limited differences based on the nature of their physical composition.

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Clocks and Watches with AI
Dan McCreary, 2026/09/29

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Here we have what I think is a great example of a course where it doesn't matter whether you're using AI. It's based on building your own clocks with microelectronics, and as such, hands-on in a way the AI cannot substitute (not, at least, until we get very capable robots). An advantage of this course it that it depends on stock low-cost components easily shipped to your home from the internet. "For under $15 in parts — a Raspberry Pi Pico 2 W, a 2.1" round color display, three buttons, and a breadboard — students build a real, ultra-smart clock from scratch. No soldering required."  Via Dan McCreary.

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Finding friction
Tomcw.xyz, 2026/09/29

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Tom Watson argues in favour of seeking out productive friction. "The often quoted Thinking and Fast and Slow talks of two types of thinking System 1: fast, intuitive, automatic thinking and System 2: slower, effortful, deliberate thinking. The removal of friction from much of our thinking work means we need to be very deliberate in leaning into System 2 as a practice." My own preference is to use the word 'resistance' rather than 'friction', and in slogan form, it's "Do hard things."

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AI Tutors Are Changing Education - But Are Students Actually Learning?
Alex Kennedy, Next Horizon, 2026/09/30

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According to this article, "the race is shifting from 'Who has the smartest chatbot?' to 'Who can build an AI that helps a person learn without doing the learning for them?'" It's a good question, because it's not exactly clear what the answer would look like (and indeed, it might be different for each student). "The problem is timing. If a beginner uses AI to bypass the exact mental operation they are trying to learn, they may become efficient before they become competent." This would have been a stronger article had it stuck to this question, but the AI-assisted text wanders as it goes on, talking more about the role of the teacher and that the AI can, and cannot, replace. "The winning model is unlikely to be 'AI teaches, humans watch.' It is more likely to be a deliberately designed triangle: the student does the learning, the AI supplies adaptive support, and the teacher decides what the learning is for."

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Compass for Governance of AI & Digital Transformation in Education
2026/09/28

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According to this article, "The Compass provides a method for thinking about governance and implementation of technologies holistically to help education systems navigate technological change while keeping human rights, democracy and the rule of law at the centre." The 'compass' has two major axes: "the governance of people and the governance of processes"; and "education with AI and education about AI." There are four layers: exploration, integration, implementation, and transformation. Around the outside are eight interconnected systems. The intent is fir the compass to be a guide, not a destination, and it's a nice metaphor, but I'm not sure it advances discourse in any particular way.

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What Happens When No One Owns Online Learning - Online Learning Consortium
Natalya Hierholzer, Online Learning Consortium, 2026/09/28

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This article takes a problem of coordination, translates it into a problem of ownership, and recommends a centralized solution in the form of a Chief Online Learning Officer (COLO). It sounds great, but it seems to me that it just pushes the problem deeper (and more intractably) into the different departments. Jeremiah Grabowski references decisions about online learning being made in academic affairs, instructional design, admissions, and marketing, among others. Is the COLO now going to tell marketing how to market? Admissions who to admit? This simply creates contradictions in each of those departments, where they no longer have the mandate to manage what they have the putative mandate to manage. 

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Manifesto for Generative AI in Higher Education – The Book Project
Hazel Farrell, Ken McCarthy, PressBooks, 2026/09/25

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This is the book-length version of the much briefer manifesto (64 page PDF) released last year. It's available in Pressbooks format or 197 page PDF. It is composed of 30 essays from various authors organized around the three major themes: rethinking teaching and learning; responsibility, ethics and power; and imagination, humanity and the future. I have mixed feelings about both the messaging and the purplish prose, but I do like the structure. And we don't have to fret silently if we disagree; there's an interactive website where you can respond to each of the essays (and it's nice to see people actually interacting on it). My favourite comment so far, on the section called "Curiosity surpasses completion": "I interpret this as learning is in the process, not in the product. In which case I agree. Could be made plainer English." The same (?) anonymous poster reaction to another chapter: "This is a bit abstracty as it stands."

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Designing Self-Paced Modules for Learners Who Can’t Attend Every Session
Tessa Dodson, ALTC Blog, 2026/09/25

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At first, based on the title, I thought this was a great new way to help people attending a conference to experience different sessions virtually, so they didn't miss out on multiple simultaneous sessions that are the norm for a conference experience. Alas, no, it's just a standard presentation on how do design a self-paced module for a course, and looks at such standards as chunking, flexible resources, and keeping the cohort connected. But it would be a good idea to convert conference sessions into virtual experiences - not just a video recording of someone talking and showing slides, but something engaging and interactive. 

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The Origin and Meaning of Land Acknowledgements
Robert Jago, BC Humanist Association, 2026/09/25

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This paper (28 page PDF) is not only fascinating, it is well worth reading for those charged with expressing land acknowledgements. The paper serves three objectives: to describe the history of land acknowledgements in the Coast Salish region of British Columbia, specifically, the ch'ech'itsul code; to identify how traditional acknowledgements are being "culturally misappropriated" to contain references to "stolen land", to express personal feelings, and to describe remorse or regret; and to describe the correct form of a land acknowledgement for the region, consisting of three parts: to introduce and situate the speaker, to acknowledge the stewards of the territory, and to explain the intent behind the event. Where I live, some 3500 kilometres away, my home sits on land where the traditional territories of four distinct nations overlap: the Omàmìwininìwag (Algonquin), Wendake-Nionwentsïo, Ho-de-no-sau-nee-ga (Haudenosaunee), and Anishinabewaki, and is acknowledged in a treaty called the Crawford Purchase (1783). 

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The AI Tools that L&D Teams Are Building (Rather than Buying)
Philippa Hardman, Dr Phil's Newsletter, 2026/09/25

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Good article on the emerging practice of learning and development (L&D) building their own tools, using AI, rather than buying from vendors. There are good reasons for this: it's fast, it's cheap, and you can get exactly the tool you want instead of settling for whatever the vendor has available The bulk of the article lists types of tools L&D teams are building, and the variety tells the story, everything from problem statement bots to job aid bots. 

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Copyright Infringement Still Isn’t Theft, Even When A Microsoft Employee Says It Is
Mike Masnick, TechDirt, 2026/09/25

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You've probably seen the headline of a Microsoft employee calling AI scraping "the largest theft of labor in human history." Case closed, right. No. As Mike Masnick says, "An exec's statement doesn't change the underlying facts: fair use isn't copyright infringement, and even when something is infringement, it still isn't theft." I know that a lot of people disagree with this, on both counts. But it is well established that, for example, "the use of the books at issue to train Claude and its precursors was exceedingly transformative and was a fair use under Section 107 of the Copyright Act." There may be an argument for changing the law, or creating new law, though I don't think so. But training AI on legally acquired text is perfectly legal under current law, and it should stay that way, not for the sake of Anthropic and OpenAI, but for the rest of us.

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Moral Learning
Stanford Encyclopedia of Philosophy, 2026/09/24

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This article discusses how we learn morals (and not some type of learning that is ethically good, though that may be a subject for another day). It tries to approach the subject analytically, without actually taking sides in any of the cross-cultural disagreements on what morals there are, how they're arrived at, and who is subject to the morality in question (for example: " There is a difference between representing 'this is something people shouldn't do' and representing 'this is something I'm required to stop people from doing'."). It just touches the surface of interesting issues such as innateness, statistical descriptions of morality, emotional resonance, and universalizability.

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The Gap Between Me and the Machine
Nick Potkalitsky, Educating AI, 2026/09/24

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Nick Potkalitsky reports "beginning to feel a strange distance between me and the work. My critical theory professor Brian McHale describes parallel experiences in literature as an "ontological" flicker. We have known since the 1970s that we are living in a world of mirrors and simulacra that challenged our ability to determine what actually is. But my experiences with AI translated that analytical insight into an intimate and embodied truth in a way no other engagement with technology has had up to this point." 

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Tiny-neural-network
con-dog, GitHub, 2026/09/24

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"Can a 14 Byte Neural Network Solve a Maze? Can it transfer across tasks?" This is a fun little demonstration of what even a simple neural network can do, with some interesting summary about the trial and error that led to its current configuration, including 'split weights' and a narrowing of what the input senses report.

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GPUs: Rent vs Buy
Cloud GPUs, 2026/09/24

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Everything discussed in this post is way beyond my budget, though I suppose if I splurged I could rent a GPU for maybe an hour once in a while. Buying is out of the question with costs ranging from $3,000 to more than $10K. Institutions and departments with budgets, though, are looking at exactly this problem. Everyone knows the prince for GPUs is inflated right now. The question is, what will prices look like in the future. The best advice in the article is that, if you're considering buying, be sure to rent what you plan to buy to test how it actually performs under your planned load. The article also has numerous tables and examples of different loads, giving you a good guide on the subject.

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Red Blob Games: English: a vs an
Amit Patel, Red Blob Games's Blog, 2026/09/24

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This has long been a fascination of mind, ever since a colleague at the student newspaper titled a column 'An Historical Perspective'. Why would he use 'an' instead of 'a'. Well - it's a rule. But isn't the rule to use 'an' in front of a word beginning with a vowel? Not exactly - as this article notes, "The actual rule is not whether the written word starts with a vowel letter, but whether the spoken word starts with a vowel sound." Fair enough. That explains why we would say 'a unicorn' and not 'an unicorn'. But that doesn't solve the historical problem. We do pronounce the 'h' in 'historical'. Well - we do in Canada. In the UK and regions with similar accents, the 'h' sound is often dropped, learning an ungainly pronunciation, 'istorical'. And so you need the 'an'. But not in Canada. Next week: why Americans drop the 'h' on 'herb'.

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Meta says its Muse AI agent can do things for you. I put it to the test
Lisa Eadicicco, CNN, 2026/09/24

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Today's AI fad is Meta's Muse, which was the subject of a number of feature announcements (including a wrist bracelet) in Meta's Connect conference, which concludes today. Muse has built-in agents, which means, for example, that it can run applications on your computer and do things like shop online. Amazon has blocked Muse. People find it useful, but note that this comes at the price of giving it access to your personal information (Meta also owns Facebook, Instagram and WhatsApp). The focus on agents suggests a shift in educational applications, moving from prompts to loops. 

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Jev introduces a new shape of LLM—System One, aka Decision Models
Simon Willison, Simon Willison's Weblog, 2026/09/23

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Simon Willison discusses the latest AI fad, Jev, also known as "System One" models. "I'm with Maggie Appleton," he writes, "I think 'decision models' is a better name for these." Is basically black box AI. "Jev is an interesting variant on the usual LLM format: it still accepts text inputs, but instead of text output it returns floating point numbers corresponding to categories, yes/no questions, ratings, and associated confidence scores." As Willison notes, "It's great for anything that can be expressed as a classification task—think spam detection, suggesting labels, prioritization and ranking." Ah, that describes (sadly) so much educational activity (people have been going gaga over it in LinkedIn).

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Embedding non-placement, community-engaged work-integrated learning in the first year: A curriculum model for vocational identity and belonging
Brooke Harris-Reeves, Andrew Pearson, 2026/09/23

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We typically think of work integrated learning (WIL) as similar to an apprenticeship where the student is effectively employed by some company while also completing their studies. That's fine if define your identity as 'employee', but what if you're thinking more broadly than that? There's still a value in WIL even if it doesn't mean "working for someone else". This paper (15 page PDF), I think, addresses that "by positioning first-year, non-placement, community-engaged WIL as an identity-forming process rather than solely a late-stage employability intervention." As the authors write, "earlier, curriculum-embedded engagement with community and professional contexts may play a formative role in shaping how students begin to understand, relate to, and envision future professional identities from the outset of university study."

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Classroom-Friendly, Browser-Based Alternative Tools to Proprietary Software
Miguel Guhlin, Another Think Coming, 2026/09/23

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Miguel Guhlin presents "a project I'd been working on since May as a side-project. It started as a way to capture the idea of "instructional rasquachismo" (see a 15-minute version of my preso). The work wasn't my main focus at the time, a weekend and evening project, but as I worked to make tools I could and would use in a classroom, I realized that I'd gone a long way past the idea of having an interactive whiteboard tool that works in your browser." Two things of note here. The first is that you could just start using these tools - the data saves locally and it "does NOT collect any personal data and students/staff do NOT need an account." Second (and probably more importantly), you could create your own version of this if you were willing to spend a little on AI and some time deciding what you want. 

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Trump administration attacks Australia's 'opt-out' algorithm law in rare intervention
Cam Wilson, 2026/09/23

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The U.S. government "wants US social media companies excluded from digital duty of care laws, which would give Australians the option to opt out of algorithmic feeds." Why would this matter? The algorithm is the difference between a social networking service that connects users with people and resources they want and a social networking service that is a channel for advertising and political messaging. Obviously there's a lot more money to be made by the latter, but it also causes a lot of harm. The public interest and social education are fulfilled much better by the former. At some point, instead of simply banning social media for children, people need to have the right to define and build their own algorithms, serving their own interests, without corporate and political interests intervening in the process.

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Ecosystems for the Future of Learning
Education Reimagined, History Co:Lab, 2026/09/23

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This report (72 page PDF) is a few years old, and it's the end point of a series of links I traced from Sam Chaltain to the ecosystem lab page to this intro. It speaks to "a growing movement among school leaders to reimagine learning in ways that center the child, prioritize equity, and recognize the integrated nature of community," According to the authors, learner-centered ecosystems "are networked systems that support children and young people to find, build, and navigate their individual learning journeys while tapping into the connections, community, and resources that have widely been left out of the conventional public education experience." This has all the words that appeal to me. In addition, the ecosystems in question are place-based and teacher and community led. 

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a16z is challenging Silicon Valley's love for drop-outs by launching a school
Julie Bort, TechCrunch, 2026/09/23

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As this story reports, "Venture capital firm Andreessen Horowitz is launching a school called The Horowitz Andreessen Academy aimed at aspiring founders who have just graduated high school and have not yet attended college." I like this description: " this is like if Y Combinator (the most famed startup school) and Peter Thiel's Fellowship Program (a famed program for young people who opt to build companies instead of attend college) had a baby." They've raised $42 million to fund it and are starting with a cohort of 50 students wealthy enough to pay elite-level tuition and looking for an inside track to connections and job opportunities. See also: the a16z newsletter announcement.

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A Principled Approach as the Sands Shift
Anna Tumadóttir, Creative Commons, 2026/09/22

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I appreciate that Creative Commons is undertaking a good-faith effort to wrestle with some of the contradictions the emergence of AI has created around open licenses and open content. They conclude, "We believe in a thriving commons above all else. We believe that for a thriving commons to exist, reciprocity is required to sustain it. We believe that to encourage people to continue a full and sincere embrace of open sharing practices in this new world order, they have to have some agency. We continue to believe that copyright is not the hammer for every nail, and that new tools are needed. And we continue to believe that none of the experiments should come at the expense of public-interest uses, which must be strongly protected." I don't agree with the idea of reciprocity - as I've said before, openness and sharing are not transactions. And I don't want the model of a knowledge commons to be a transactional one.

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Renaissance AI and Education Resource Hub
Joon Suh Choi, 2026/09/22

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According to the website, "We are piloting a knowledge-building library for AI agents in learning engineering. This hub curates evidence-based research, tools, datasets, and policy resources from trusted sources like What Works Clearinghouse, Evidence for ESSA, Mathematica, and the Learning Policy Institute - structured so AI agents can search, filter, and cite them directly." I can seethe usefulness of this, but once again a quick look at the literature raises more questions than answers. Why are there 169 frameworks, for example? This strikes me as a discipline less like engineering and more like creative arts. Here's the GitHub version.

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What It Takes to Build an AI Teacher
Allison Dulin Salisbury, The Humanist, 2026/09/22

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This is an interview with Tom Sayer from Ello about their effort to build what he calls an AI teacher.The premise of the article is that since teaching requires mastering many little things, all of which go into the overall task of personalizing instruction, it follows that an AI teacher won't be the product of a frontier model, but rather an assemblage of more specialist models. I don't know about that, and in the end the difference probably doesn't matter anyway. I do think from reading this article that Ello is informed by very traditionalist pedagogy. For example: "At Ello, we focus more on core skills in reading, math, and language learning. We'd love to nurture creativity alongside these core skills, but right now, we just want to teach a kid to read. That involves drilling phonics, but it also means engaging a readers' comprehension too, and developing their vocabulary; all the parts of the reading rope."

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The Agentic Professor: Exploring GenAI-Supported Futures in Higher Education
Peter Cornillon, Xavier Prochaska, EDUCAUSE Review, 2026/09/22

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This is a long article with the challenging idea that an 'agentic professor' is something that can and maybe should exist. What I like is that the authors offer a test of the concept in the middle of the article; you can copy their prompt into an AI of your choice and see what it does. "What distinguishes the Agentic Professor envisioned here from such present-day interactions is not any single function but the combination of capabilities sustained over time: agency, longitudinal memory, pedagogical plurality, cross-disciplinary synthesis, and continuous refinement. Its significance lies not simply in providing individualized support but in creating continuity across a student's educational experience, connecting ideas, skills, and feedback across courses, disciplines, and years of study." I don't think they're wrong in the sense that something like the agentic professor is probably achievable. But I wonder if an agentic professor is what learners and people generally are actually looking for.

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The Synthesis Is Here
Frederick M. Lawrence, Alfred Spector, The American Scholar, 2026/09/21

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According to this article, technologists need to study more of the liberal arts, while those in the liberal arts need to embrace technology. "By suggesting that we need to fuse technology and the liberal arts, we are explicitly affirming the need to balance topics like economic growth, political expediency, and human desires with the humanistic insights developed over the centuries." Otherwise, "technology's effects could well be harmful." Even assuming anyone has the time to study all that (and over my lifetime I have genuinely tried) it's not clear that any genuinely deep civilization-saving insight results. We already know that systems devoted to the single-minded pursuit of anything - whether paperclips or money - lead to undesirable consequences, but we build them anyway. But more, I just don't see this argument as particularly deep. Sure, we should pool out knowledge. But then what? Do we even know what we want and what we reasonably fear? I don't get a sense of that here. Via Mark Oehlert.

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What Happens When Grading Costs Almost Nothing?
Marc Watkins, Rhetorica, 2026/09/21

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This article follows a well-established pattern for this sort of writing: a new capability is described, we get some examples of it at work, then we read some cautionary remarks about misusing the capability. In this case, the capability is very low cost automated assessment, courtesy System One + Jev. It uses a grading rubric and natural language student text as input, and saves money by avoiding costly next-token text generation in its output. The caution: "When you write to please a machine, you enter into a feedback loop that may not benefit your learning. While some writing tasks are straightforward and don't necessarily require much process work, the type of long-form and engaged writing many college courses call upon asks students to develop their responses via close reading of primary and secondary sources, multiple drafts, peer review, instructor feedback, and above all, time." 

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More Degrees But Not Higher Earnings: Puzzling Data from CUNY’s Famed ASAP program
Jill Barshay, KQED, 2026/09/21

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The City University of New York (CUNY) Accelerated Study in Associate Programs (ASAP) has helped many more students earn degrees, but according to this article, "a recent 14-year study finds that those additional degrees haven't translated into higher earnings." The rest of the article considers possible explanations: associate degrees aren't valued, maybe, or too many of them are in the humanities. I thought that maybe the economy in general was a pretty good reason. Or it could just be that the study is fatally flawed: "the averages include people who are unemployed or working outside of New York state (counted as earning zero)." This seems like a study determined to undermine the program. For though "CUNY says ASAP's mission isn't simply to maximize earnings, and there may be other personal and societal benefits to finishing a degree that wages cannot measure" Jill Barshay nonetheless writes "if taxpayers are spending tens of millions of dollars on an intensive intervention, earnings are one legitimate outcome to examine." 

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Defining collectivism as duties in relationships rather than generalized warmth improves predictive validity in 100 cultures
Thomas Talhelm, et al., Nature, 2026/09/21

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This is an odd article. On the one hand, it points to what may be a genuine mischaracterization of collectivism. On the other hand, it uses loaded terminology and feels like it may be an attempt to mislead readers. Your call. Here's the gist: our traditional view of East versus West is that the former is more collectivist while the latter is more individualist. However, the authors assert, studies fail to find that distincction in practice. They propose splitting the defition of collectivism into 'warm fuzzies' and 'responsibilism'. These are distinct in the the former favours general affirmations of obligations to wider groups and strangers, while the latter emphasizes responsibilities to close knit groups like families and communities. Reapples, the scale predicts differences in Eastern cultures (deemed 'responsibilist') and Western cultures ('warm fuzzies'). "Although warm fuzzy collectivism is not the same concept as individualism, it is paradoxically more common in individualistic cultures... Warm fuzzy collectivism and responsibilism are different ways of prioritizing social relationships, not a walling off from relationships."

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