Stephen Downes

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Vision Statement

Stephen Downes works with the Digital Technologies Research Centre at the National Research Council of Canada specializing in new instructional media and personal learning technology. His degrees are in Philosophy, specializing in epistemology, philosophy of mind, and philosophy of science. He has taught for the University of Alberta, Athabasca University, Grand Prairie Regional College and Assiniboine Community College. His background includes expertise in journalism and media, both as a prominent blogger and as founder of the Moncton Free Press online news cooperative. He is one of the originators of the first Massive Open Online Course, has published frequently about online and networked learning, has authored learning management and content syndication software, and is the author of the widely read e-learning newsletter OLDaily. Downes is a member of NRC's Research Ethics Board. He is a popular keynote speaker and has spoken at conferences around the world.

Stephen Downes Photo
Stephen Downes,, Casselman Canada

Alignment Assembly on AI and the Commons — Outcomes and Learnings
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I'm pretty sure I took part in this, at least at the earlier stages. There's a lot here, so I'll focus on the consensus: "This Alignment Assembly revealed three key areas of consensus. First, the prioritization of values beyond openness in considering the open movement's policies towards AI (related to principle no. 3). Second, the need for public investment in AI (related to principle no. 7). And third, the call for the open movement to make education about AI and its impact, and public-facing communication on AI a priority." What interested me even more than the outcome was the decision-making process.

Today: 59 Total: 314 Open Future, 2024/06/14 [Direct Link]
Why Getty Images and Picsart are partnering to train a new AI image model
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The argument that AI is violating copyright is being used mostly to eliminate it as competition; the question of whether it actually copies content (it doesn't) is moot. This is clear in this article, which describes an agreement whereby Picsart trains an AI model using Getty licensed images, creating a new image platform for both companies. The play is that this is legally safe - a clause risk-averse lawyers will embrace with enthusiasm. "the deal aims to provide "commercially safe AI-generated imagery" for creators, marketers and small businesses (and) it will offer customers commercial rights and indemnity for the images they create." It feels more like a protection racket than a service, even as it makes the hollow promise to develop "new ways to compensate the creators of the images used to train the AI model." See also this deal between Business Insider and OpenAI. The common foe shared by all, of course, is genuinely open access AI, which they would like to prevent as soon as possible.

Today: 58 Total: 290 Marty Swant, Digiday, 2024/06/14 [Direct Link]
Firefox tips and tricks for creatives
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While most people in the world use Chrome, people who understand the web, I think, use Firefox (and of course I count myself among those). It's more secure, properly blocks advertising (with extensions like UBlock Origin) and won't let Google or Microsoft track you - important if you're working in what you would like to be a secure environment (it's funny how many people complain about surveillance culture but won't even take the basic step of using a more private browser). This post points to a few nifty features - including some new one for me: editing PDF files, screen capture

Today: 65 Total: 299 Steve Flavin, 2024/06/14 [Direct Link]
Tim Crane on AI and Agency
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Agency is key to understanding learning. Agency here is thought of as "deliberation, choosing between options, and bringing reasons to bear on what we do." This video interview (no transcript, sorry) asks the core question, can AI exhibit genuine agency? Humans, thought of as machines, certainly can, but what about 'artificial' machines? We can't rule it out without evidence or a good argument. But can a computing machine exhibit agency? Here, the need for evidence is on the other side: there's no good reason to assume such a machine would achieve agency. "Understanding is not producing a string of symbols," which is what we have today. There are questions of, for example, consciousness. And nobody has been able to say with any clarity what the endpoint of an artificial intelligency with agency would look like. It has to act in order to pursue some goal. But what would a system-generated goal look like?

Today: 64 Total: 297 Tim Crane, Majid D. Beni, The Brains Blog, 2024/06/14 [Direct Link]
Team support
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Very short post with the following message: "If you want to know how good a team is, watch them when things are tough. See how they support one another." But I'm here for the image, which though it's probably AI-generated, really works for me.

Today: 66 Total: 380 David Truss, Daily-Ink by David Truss, 2024/06/14 [Direct Link]
Competency model development: The backbone of successful stealth assessments
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You might not like this, but this, I think, is the future of assessment: "Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning." According to the authors, the success of this approach depends on four sets of models: "Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning.' The central question is whether these models can be developed algorithmically, that is, by using AI. The full version is behind a paywall, but don't bother - you get the sense from the outline and most of the relevant work was already openly published here. Image: Rahimi.

Today: 14 Total: 512 JCAL, 2024/06/13 [Direct Link]

Stephen Downes Stephen Downes, Casselman, Canada

Copyright 2024
Last Updated: Jun 15, 2024 10:37 a.m.

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