OLDaily

Welcome to Online Learning Daily, your best source for news and commentary about learning technology, new media, and related topics.

Generative AI and Open Access Publishing: A New Economic Paradigm
Leo S. Lo, Library Trends, 2025/06/30

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This paper (18 page PDF) is a balanced and conservative look at how AI impacts open access publishing. A lot of the paper is exposition; if you're familiar with the field you really only need to read the introduction and perhaps the nondescript call to action at the end. But the paper works well with an audience not familiar with the nuances of open access publishing and the potential offered by AI. "AI technologies promise to streamline workflows, potentially reducing the costs associated with manuscript preparation, peer review, and publication. Generative AI tools can assist in drafting papers, performing literature reviews, managing peer review, and generating data-driven insights," writes Leo Lo. "However, the economic implications extend beyond mere cost savings. Generative AI also opens up new avenues for value creation and monetization in publishing. AI-driven analytics, personalized content recommendations, and advanced search capabilities could become premium services, potentially creating a new tiered system of access to knowledge. This raises questions about the future of truly 'open' access in an AI-enhanced publishing landscape."

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We Still Have Time to Protect the Last Frontier of Privacy
Alexandra Frye, Blog of the APA, 2025/06/30

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If you aren't thinking of these things, you aren't thinking ahead: "brain-computer interfaces (BCIs), neuroimaging, neural recording devices, neural decoding." We're talking maybe decades here, not centuries. And when the time comes, there will be a lot of reaction along the lines of "we should ban these completely", but they'll be too useful. Alexandra Frye says, "the potential of this technology for ethical compromise seems clear to me. Issues like privacy, consent, cognitive liberty, inequality, mental autonomy, and the risk of exploitation by bad actors are all deeply implicated." It's not clear to me that we'll have a better understanding of any of these than we have today, but that won't be for lack of opportunity. We can't just go into these debates with a list of (supposedly unassailable) ethical principles. We should be thinking about not just what we want and don't want, but how we as a society make and enact such decisions. 

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Some dog content to temporarily distract you
Michelle, Bluesky, 2025/06/30

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I am not distracted. I mean, using 'it' as a pronoun for a dog? But mostly, this video reminds me to say, once again, that knowledge is pattern recognition. You don't need words or language, you don't need models and semantics, you just need to associate a pattern of experience with what happens next, and you know, even if you're a dog.

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Beyond AI and Copyright
Paul Keller, Open Future, 2025/06/30

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What bothers me, I think, about some of the schemes responding to the idea that AI is "appropriating" public knowledge and information is that writers are tying themselves in knots trying to avoid the one approach we have always used and which we know actually works: taxation. The basic idea is that if somebody makes money while benefiting off the common wealth - whether it be intellectual property, physical infrastructure, security services, whatever - then they are taxed a reasonable portion of that money that goes back in to support those services. All the other contortions - ranging from 'preference signals' to 'user pay' to the "market-deployment levy framework" - are simply attempts to curtail that democratic process, for example by stipulating, as this article (17 page PDF) does, that our tax dollars should be paid specifically to "creators and rightholders", "public service media organizations", "open access information providers", and "public AI models and services". That's better than most, but why privilege these groups? What's left for the people who sweep the floors where these creators ply their craft?

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Ethics Is the Edge: The Future of AI in Higher Education
Maya Georgieva, John Stuart, EDUCAUSE Review, 2025/06/30

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Short and not very insightful article about ethics and AI in higher education. We are told "a new framework outlines eight ethical principles to guide higher education's implementation of artificial intelligence" but it's really just the same old framework with no depth or insight added.

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We publish six to eight or so short posts every weekday linking to the best, most interesting and most important pieces of content in the field. Read more about what we cover. We also list papers and articles by Stephen Downes and his presentations from around the world.

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