Stephen Downes

This article laments the 'ludic loops' that define us in the algorithmic age, that is, the design of the internet stops us from ever switching it off, "It moves at the speed of light, with constantly changing metrics, fuelled by ... repeated cycles of uncertainty, anticipation and feedback" - in other words, it works exactly like a Jackpot 6000 slot machine." But instead of tokens or dollars, what we're playing for is "your sense of self". But external validation is as old as the concept of 'self-worth' itself. Michelangelo didn't paint for free. Da Vinci had to earn a living. Any time we depend on such externalized criteria, whether an author waiting for the reviews or the big price shortlist, or the Reddit reply guy playing for 'likes', we run this risk. The cure, though, is to get over ourselves. Am I another Descartes? As popular as Wittgenstein? Why would it matter? If we want, we can play the game, but the only way to win is to stop playing.

This item is the latest in a series of posts that didn't really catch my attention until now. It's based on the idea of "Horizon Three" or "H3", which is the name for the "future-ready" educational system that follows in sort of a third wave that follows after 'traditional' (H1) and 'efficiency' (H2) learning. The concept is described more fully in this Google Drive PDF document (24 pages). What is it, exactly? It's a lot of stuff we've seen elsewhere, a mix of good and bad, including learner-driven school models, business and community partnerships, national competition for models, publicly funded supplemental and enrichment programs, mastery-based and embedded assessments, student ownership of credentials data, and more (see specifically pages 18 and 19 of the document). This approach is framed in terms of defining philanthropic support for education initiatives (which is why it flew beneath my radar; I usually just think of these as policy advocacy initiatives to find ways to support privatized education systems). Anyhow, worth knowing about.

From Alan Levine comes this link: "At 12.4 million image-caption pairs, PD12M is the largest public domain image-text dataset to date, with sufficient size to train foundation models while minimizing copyright concerns. Through the Source.Plus platform, we also introduce novel, community-driven dataset governance mechanisms that reduce harm and support reproducibility over time." Search could be better, but the images are great.

In case you thought Amazon was being left out of the AI boom, this article offers an antidote. Here's Amazon's plan: "They're offering their own models (Nova). They're investing in the current leader (Anthropic). They're building the chips (Trainium). They're creating the infrastructure (Project Rainier)." See also: Amazon's easy 17 step process to gain access to its Nova pro model.

The reviewer shortage isn't, as Ingrid Robeyns claims, "a collective action problem." I have stopped refereeing papers entirely (though the requests keep pouring in). It's not just that it's unpaid labour for (often) commercial entities. It's that I think the pre-publication peer review system is broken and needs to be replaced with a system for open and post-publication peer review. No more 'mystery reviewer #2'. No more secret requirements that 'the literature' (ie., other papers in the same journal) be cited. No more inner cicles of people positively reviewing each others' stuff. And also, by making reviewing open and post-publication, we have a strong case for open access publishing, of for no other reason we have eliminated much of the expense of publishing a journal. Image: UAB Libraries.

When Dow Jones sued Perplexity for failing to properly license its content, Perplexity replied, "[Dow Jones] prefers to live in a world where publicly reported facts are owned by corporations, and no one can do anything with those publicly reported facts without paying a toll." Now let's suppose that what Perplexity said is true, that is, that the content under question really consists of "publicly reported facts". What does that say now that Dow Jones has its own AI engine, Factiva, and has negotiated licenses with news publishers? To me, it says precisely that Dow Jones thinks that it now owns exclusive rights (or, at least, rights) to publicly reported facts. But that's now how it's supposed to work, right? Nobody owns (say) the fact that there was an earthquake off California today, no matter how someone (or some thing) learned of that fact. Can you imagine a university having to license the facts it teaches in its classes?