Sketches, visualizations and other forms of externalizing cognition play a prominent role in the work of just about any scientist. It’s why we love using blackboards, whiteboards, notebooks and scraps of paper. Many folks who had the privilege of working the late Pieter Muysken fondly remember his habit of grabbing any old piece of paper that came to hand, scribbling while talking, then handing it over to you.

Over two years ago I wrote about the unstoppable tide of uninformation that follows the rise of large language models. With ChatGPT and other models bringing large-scale text generation to the masses, I want to register a dystopian prediction: this enables a whole new form of monetization.

The construction of gothic cathedrals like Chartres was governed not by blueprints but by “talk, tradition, and templates” — at least that is what Turnbull has compellingly argued. When you come across such a neatly alliterative triad, there are two ways you can go. You can adopt the terms in an unexamined way and rely on their alliterative power.

DALL-E, a new image generation system by OpenAI, does impressive visualizations of biased datasets. A widely circulated PR animation features meme-like koala dunking a baseball leading into an array of old white men — representing at one blow the past and future of representation and generation. This post jumps from reflections on techbros to the erasure of human labour in Cosmopolitan’s rushed “first AI magazine cover”.

Few historical maps of Ghana’s Volta and Oti regions have been invested with so much political and sociohistorical meaning as Hans Gruner’s 1913 map of the Togo Plateau. Gruner, stationed for over twenty years at Misahöhe in present-day Togo, was a long-time colonial administrator known for his ethnographical and historical knowledge of the area.

There is a considerable halo-effect attached to JIFs, whereby an article that ends up in a high IF journal (whether by sheer brilliance or simply knowing the right editor, or both) is treated, unread, with a level of veneration normally reserved for Wunderkinder. Usually this is done by people totally oblivious to network effects, gatekeeping and institutional biases.

Lezenswaardig: een groep jonge medici ageert tegen de marketing-wedstrijd waarin volgens hen narratieve CVs in kunnen ontaarden — de nieuwste bijdrage aan het Erkennen & Waarderen-debat. Maar niets is wat het lijkt. Over evidence-based CVs, kwaliteit & kwantificatie. Eerst dit: de brief benoemt het risico dat je met narratieve CVs een soort competitie krijgt tussen verhalen.

A preprint claims that “ideas from theoretical linguistics have played no role in [NLP]”. Outside the confines of Chomskyan linguistics folks have long been working on incorporating storage, retrieval, gating and attention in theories of language, with direct relevance to computational models. The only way to give any content to the claim is by giving the notion “theoretical linguistics” the narrowest conceivable reading.

I have other things to do but one day I’ll enlarge on the insidious effects of elevating this cursed little histogram of “Research output per year” as the single most important bit of information about academics at thousands of universities that use Elsevier Pure. Consider this mini-rant my notes for that occasion. Most importantly, we DO NOT write per year. Our careers are too diverse and precarious to measure output that way.

With Times Higher Education writing about citation gaming and hyperprolific authors (surely not unrelated) I hope we can save some of our attention for what Uta Frith and others have called slow science. On that note, consider this: Team science is (often) slow science.

Large language models make it entirely trivial to generate endless amounts of seemingly plausible text. The web is about to be engulfed in unending waves of algorithmically tuned AI-generated uninformation. This builds a feedback loop of uninformation feeding on uninformation. Counterintuitively, there was never a better time to be a scholar.