Stephen Downes

It always interests me to know when people talk of concept-formation in learning and intelligence just what sort of account of 'concept' they are using. Consider, for example, a 'cat'. Suppose we encounter one that is 25 feet tall. Is it still a cat? Is it a new type of cat? Or just an existing cat (a tiger, say) with extraordinary properties. Anyhow. This article (24 page PDF) takes these questions seriously, and in particular, examines Waismann's notion of open texture through the paradigm of the prototype theory of concepts, a theory that in turn evolved out of cognitive linguistics and can be contrasted with empirical and formal theories of concepts. In particular, it involves the idea that concepts can be open ended and vague, similar to Wittgenstein's 'family resemblances', such that (say) different entities can be more or less instances of a given concept (that is, being an instance of a concept is not an 'all or nothing' proposition). This paper is accessible and clearly written, and a good starting point for a serious inquiry into these ideas, if you're so inclined.

This is an interesting set of reflections on what it means to use AI to develop software. There's the good and there's the bad. "AI is the most powerful tool I've ever used. It's also the most draining. Both things are true... If you're tired, it's not because you're doing it wrong. It's because this is genuinely hard. The tool is new, the patterns are still forming, and the industry is pretending that more output equals more value. It doesn't. Sustainable output does." And AI fundamentally changes the job from being a creator using deterministic tools to being a code reviewer using (untrustworthy) non-deterministic tools. Again, this all points to the idea that AI is not eliminating the need for skills, but changing the skills we need. Via Martin Fowler, who credits Tim Bray.

It's that old question: do fish know they're wet? This article considers nature of the paradigms we swim within without even realizing what they are. For example, write authors Zac Hill and Ben Marshall, many non-profits facing challenges focus on "rigorous, well-established ways of working... hiring staff and volunteers to deliver products or services to beneficiaries... emblematic of a way of working we call the institutional paradigm." But it's not the only paradigm. There is the 'democratic paradigm' - where "people are elected or appointed rather than hired", or the 'legal paradigm', or the 'social movement paradigm'. Here, the authors suggest organizations look at what they call 'the creative paradigm', which is "generally more flexible, output-oriented, and driven by expert discernment." There are opportunities, they write, such as a more flexible talent model, different time horizons, and different ways of evaluating work.

I like this article because it carefully steps through the question it addresses. Readers of this newsletter will know that AI-scoring has been available for a number of years now, and easily predates the recent generative AI boom. As Nick Potkalitsky notes, "Ohio uses discriminative AI. Its job is to classify and score existing text. You give it an essay, it returns a number: 1, 2, 3, or 4 points." It is trained on human-graded essays and after training does nothing but classify essays into separate categories. By contrast, "The AI teachers worry about, tools like ChatGPT, is generative AI. Its job is to create new text.? It's completely different, shouldn't be used for grading, and probably wouldn't be very good at it (by contrast, discriminative AI is often fairer and more consistent than human graders).

Creative Commons has offered the next argument in what it describes here as a process of redefining 'open'. "CC licenses are often viewed as neutral tools, but in practice they can amplify existing power imbalances (as we know, infrastructure is not neutral!). For example, marginalized language and data communities may lack the leverage to negotiate how open resources are reused." This is not new and not unique to marginalized language and data communities - anyone not wealthy enough to hire lawyers has no effective rights in a law- and lawyer-based system. But this isn't the issue being flagged by Creative Commons. "We know that openness is much more than a set of legal tools; it is a set of values, a way of belonging, a wish for a better future." The specific value CC seems to be promoting, though, is transactionalism. "Communities are responding by asking for openness that also accounts for agency, consent, reciprocity, and governance." Who speaks for 'communities'? Creative Commons? Related: Google backs African push to reclaim AI language data. Also: Microsoft Research releases PazaBench and Paza automatic speech recognition models, advancing speech technology for low resource languages.

This article begins with an observation: "The same person who cannot get through a novel can watch a three-hour video essay on the decline of the Ottoman Empire. The same teenager who supposedly lacks attention span can maintain game focus for hours." The point is that what some people are calling a cognitive decline is actually a transition to multi-modality, and if sustained attention is a problem, it's more a problem of design and architecture, not modality. Then, as if to prove the point, this essay essentially repeats the same three or four points over and over through more than 3,000 words (yes, I counted). They're good points, sure, but they don't bear repeating that much.