Stephen Downes

As Lee Gaines writes, "More than three years after ChatGPT debuted, AI has become a part of everyday life — and professors and students are still figuring out how or if they should use it." I think the question revolves around means to an end. "What we need is students to go through the process of writing research papers so they can become better thinkers, so they can put together a cogent argument, so they can differentiate between a good source and a bad source," Cryer says. Well, yeah, I can see that. But is writing research papers the only way to become a better thinker? It seems very limited to me. In an AI-enabled would we should be a lot more hands-on, solving problems, testing solutions, that sort of thing. What is the actual work we want to be able to do? Focus on that.

I have spent my entire life resisting the idea of the narrative and storytelling (which is a hard place to be in for a writer). For Keith Hamon, though, the narrative is the core. He cites Pria Anand's The Confabulations of Oliver Sacks, where a 'confabulation' is "a neurological repair where the brain fills memory gaps with stories that the teller believes to be true." Well there's no doubt there are these gaps that are filled, but are they filled with stories? Hamon thinks so. "Narrative is the biological software that converts raw, chaotic data into a liveable reality. It's an instinctive search for order that slips beneath consciousness to insure that we always have a coherent sense of ourselves and our worlds." It strikes me as wrong, though, that the only sort of coherent sense we can have is a text-based linear structure. At the very least, it's a fabric - "it's all a rich tapestry," as Andrea likes to say. And for me, at least, it's thickly woven, multi-modal, and generally non-linguistic. I can, if I really try, represent it with a narrative, but it doesn't come naturally at all. I think we do people a disservice if we tell them all they can imagine is stories.

The term 'open education' has a variety of meanings, most being based on the idea of creating access to learning opportunities and resources. The term 'fair dealing' is a legal term providing reader rights to use copyright material under certain conditions, analogous to 'fair use' in the U.S. This article finds a lot on common between them and argues "they're rooted in the same values: fairness, accessibility, and a commitment to the public good." I mostly agree with the authors' vision: "Imagine an educational landscape where learners have rich, meaningful choices: open textbooks they can customize and adapt, fair dealing excerpts for highly specialized knowledge, collaborative assignments that contribute to shared knowledge, and community-created resources that reflect the world students live in." Also available: the Open Education Workbook (content is in the menu that runs across the top of the page in hard-to-see dark grey).

There's more to this than meets, the eye, but I've added Updates from GOV.UK AI Studio to my RSS reader and will likely track further developments. Here's the gist: Kay Dale writes, "We've identified 8 different types of government service to help us see where agentic AI can add most value." These topologies, as they're called, underlie the existing list of 75 digital services they've identified across government. Of course this sort of analysis could be undertaken for any sort of service, including learning services. I think this sort of this is going to matter, and will watch how it plays out. If you're wondering, the eight types (illustrated) are: informational hub, task list, portal, application, register, license, appointment, and payment. Via Doug Belshaw, Tom Loosemore.

I think it's worth spending the time it takes to have a nice leisurely read through this article from Jakob Nielsen, one of the world's most notable experts on usability and user experience design, as he reflects on how AI has upended the last 40 years of his work. "AI will likely completely invalidate the manual UX design process I spent four decades evangelizing, from 1983 to 2023," he writes. "My error was in assuming that what had worked for forty years would continue to define the standard. A reasonable assumption, perhaps, but one I have now been proven wrong in holding." Stunning. And yet, still beautifully designed and written.

I'm sure a lot of the articles I've been reviewing for OLDaily are AI-authored, though it is getting increasingly difficult to tell. In a certain sense, it doesn't matter, because what I'm always interested in is whether the content is accurate, clearly expressed, and in some sense novel (by that, I mean 'novel to me', which leaves a lot of room for both humans and AIs). This article passes the test, though many readers won't like the message: "AI can already do social science research better than most professors... (and) The academic paper is a dead format walking." It's the same thing for academic papers as it is for software: we can produce a high-quality paper in a few minutes with AI. So why on earth would we pay any money for one? Now there's still a bit of a supply-chain issue: if the AI is to stay current it needs input from somewhere. But probably not from academic papers. Via Paul Prinsloo, who I can just envision walking around muttering to himself after reading this.