Stephen Downes

Knowledge, Learning, Community

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Stephen Downes spent 25 years as an expert researcher at the National Research Council of Canada, specializing in new instructional media and personal learning technology. With degrees in Philosophy and a background in journalism and media, he is one of the originators of the first Massive Open Online Course, has published frequently about online and networked learning, and is the author of the widely read e-learning newsletter OLDaily. He is a popular keynote speaker and has presented at conferences around the world. [More]

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Here's what's in the latest edition of OLDaily

Mark Zuckerberg's new toy is a parasite. Please don't fall into his latest trap.
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This is a column from SFGate warning people about MUSE, Meta's personal agent AI. "In addition to storing logins and passwords and linking your bank account information, it wants to see your messages, personal calendar and contacts, requesting more sensitive information than virtually any other AI app, according to ZDNET." The concern isn't so much that it has this information as what it wants to do with it. "The true end users of Facebook are the marketers who want to reach and influence us," media theorist and CNN columnist Douglas Rushkoff wrote in 2013. "They are Facebook's paying customers; we are the product. And we are its workers."

Today: Total: Ariana Bindman, Sfgate, 2026/10/19 [Direct Link]
Designing for Kindness
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"The single most important strategy we can use to help our students succeed in our courses is to care about them as learners and as human beings," says Kona Jones from Richland Community College. What I like about this article is that it contains not just the platitude in the introduction, but a detailed description of how exactly to design for kindness, using her own mathematics course as an example, with concrete steps taken to make sure people feel looked after and cared for in the course. This includes things like a "checklist of all the important things that students should be doing", "videos that students are able to download", asking "what are your preferred names and pronouns, what's your preferred name and preferred pronoun", "backup plan for completing assignments if you experience internet or computer issues", and more. 

Today: Total: Kona Jones, Instructure, 2026/10/22 [Direct Link]
8 types of web applications and examples
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This article describes "8 main types of web applications, how they work, and real examples to help you choose the right solution for your project." It's an introductory article, useful for people who aren't familiar with the different types of web pages they may encounter, and helpful for people thinking about something they may want to build (this sort of conceptual clarity is really useful if building with AI).

Today: Total: Hostinger Tutorials, 2026/10/21 [Direct Link]
Sovereignty isn't a place
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People typically associate sovereignty with a nation or place, but as micro-nations like Sealand demonstrate, sovereignty isn't about place, it's about what you can do. In this post, Tom Watson argues, "sovereignty is about meaningful choice and the ability to act on it. Having alternatives, yes, but also having the knowledge, money, rights and practical means to actually pick one." That means the sovereignty of nations, communities, businesses, organizations and individuals are different. Each has different needs and priorities. Governments are concerned with security while individuals are concerned about their data, for example. 

Today: Total: Tom Watson, Tomcw.xyz, 2026/10/20 [Direct Link]
Mechanistic Indicators of Understanding in Large Language Models
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This is a really interesting paper that considers the question of whether large language models (LLM) understand. As the authors write, this depends a lot on what we mean by 'understand'. To clarify, they identify three types of understanding: conceptual understanding, which "involves the model developing internal representations ('features') that are functionally analogous to human concepts; state-of-the-world understanding, which "involves forming an internal representation of the state of the world by grasping contingent empirical connections between features"; and principled understanding, which is "the ability to grasp the underlying principles or rules that unify a diverse array of facts." Through various examples, they show that LLMs can attain all three forms of understanding, however, they do it very differently from how a human would. They employ a variety of mechanisms running in parallel to do so, and hence don't demonstrate the same preference for parsimony - that is, for a single over-riding principle - that humans do. Great paper. Via Pierre-Yves Oudeyer.

Today: Total: Pierre Beckmann, Matthieu Queloz, arXiv, 2026/10/19 [Direct Link]
How AI replaced me
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This is "an edtech worker's account of what got left behind." I spent most of the article what company it was she was laid off from (it's probably Kiddom, though she never says). "We're automating the humanity out of our jobs and leaving the annoying parts," she writes. "We're using technological band aids instead of meeting our issues at the source. Tech CEOs love to make sure their employees are grinding away generating AI slop. They also love to watch their employees suffer. 'Let's bring everyone back into the office. Who cares if we don't have enough desk space? Who cares if they have to commute hours at a time? Who cares if they were hired as remote employees (and paid less for it?) We have lunch and happy hours! Why aren't they more grateful?'" Via Audrey Watters.

Today: Total: Oakland Review of Books, 2026/10/16 [Direct Link]

Stephen Downes Stephen Downes, Casselman, Canada
stephen@downes.ca

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Last Updated: Oct 18, 2026 4:37 p.m.

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