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.

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.

Reading Suchman’s classic Human-machine reconfigurations: plans and situated actions , I am impressed by her description David Turnbull’s work on the construction of gothic cathedrals. In brief, the intriguing point is that no blueprints or technical drawings or even sketches are known to have existed for any of the early modern gothic cathedrals, like that of Chartres.

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 as much for his ethnographical and historical knowledge of the area as for being a petty tyrant with a powerful grip on ‘his’ district.

I’ve been caught up in a few debates recently about Recognition and Rewards , a series of initiatives in the Netherlands to diversify the ways in which we recognize and reward talent in academia. One flashpoint was the publication of an open letter signed by ~170 senior scientists (mostly from medical and engineering professions), itself written in response to two developments.

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.

This Lingbuzz preprint by Baroni is a nice read if you’re interested in linguistically oriented deep net analysis. I did feel it’s a bit hampered by the near-exclusive equation of linguistic theory with generative/Chomskyan aps.

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 rant my notes for that occasion.

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.