The mirage of “AI” reaches us through a narrative centered on inevitability, productivity, and efficiency. It is therefore at loggerheads with the values of a healthy academia, which questions narratives of inevitability, prioritizes process over product, and realizes the value of friction for creativity. This workshop is for everyone who is bored about the typical AI sales pitch and interested in how to do the best science possible and build a better academia together. The workshop promotes a values-first rather than a tech-first perspective and articulates what you probably already suspected: it is perfectly okay not to use “AI”.
In the past months we’ve started the Futures Library, in which we share key ideas and people that drive the project. The first few weeks have featured a wide variety of themes and technologies, from pluriversalism to cosmotechnics and allohistorical maps to magic lanterns.
What seemed an open-and-shut case of plagiarism turned out to be symptomatic of a much more worrying issue: the runaway influence predatory publishers have on declining scholarly standards. The good news: everything is on hand to start creating the future we want. Academics should vote with their feet and move towards scholar-led diamond open access.
During the pandemic I built a gather town co-working space for my team. The free tier enabled our team to be together even when working from home. Folks claimed their desks and co-designed the space. Multiple papers were written here and collaborations blossomed. As gather town 1.0 closes down, we say goodbye. In this post I share a few recollections and reflect on what made the gather town experience so compelling for informal co-working and flexible interactions.
When you’re enamoured of a technology and someone points out important ethical challenges, a typical reflex is to seek permission: yeah, but what about this use? If you find yourself seeking permission, one useful thing to do is to step back and inspect the underlying value conflict. What does your own moral compass say? Centering values leads to mindful choices. As you move from a tech-first to a values-first perspective, the question shifts from “won’t you give me permission?” to “how do I do the best science possible?”. And that, to me, is a question worth asking.
Some thoughts on generative AI, reproducibility, and why the praxis of slow and reproducible science provides a useful lesson for navigating the lures of “AI”.
Succinct argument for scientific publishers to adopt a clear and unequivocal policy that discourages authors from submitting synthetically generated text, and that invites them to uphold basic standards and core values of research integrity.
Start your blog with an exultant tone, pompous words, and gratuitous alliterations and I know we’re in for a rapid descent into the wastelands of utter mediocrity. I recently came across some obvious LLM-generated slop on science blogging aggregator Rogue Scholar. Here I write up why synthetic text has no place in scholarly blogging.
GPT based text generators like ChatGPT or Microsoft Copilot have rapidly become a “cultural sensation”. Here I provide scientific background and guidance on how to think critically and mindfully about these tools in academic writing and research.
Academics often feature a few selected papers on their home page. Typically these represent big projects or work published in prominent venues. What I’d like to see more of is “niche papers”: work to be proud of even if it has managed to remain a bit obscure. What are your niche papers?
For years now, I have responded to review requests from Elsevier journals with a friendly explanation of why I cannot in good conscience devote my free labour to their for-profit venture. I always include an out: make some work in the same journal available in open access. Somehow they always find this isn’t possible.
Reading Latour can feel like sorting through ideas the way you deal with laundry fresh out of the tumble dryer, sorting things out, reuniting pairs of socks, finding the inevitable singletons, creating some semblance of order and accepting loose ends. It all comes out in the wash.
Writing is thinking. The writing process is the most neglected part of our job. We spend millions on fancy equipment and uncountable hours on training for using this or that toolkit. Yet we assume the BA-level academic writing course we once followed is sufficient; the rest we’ll just learn on the job and hopefully soon we’ll automate away with LLMs. It is all formulaic anyway. To think this way is to hollow out the very foundations of scholarly work. Can’t think original thoughts if you don’t find your own voice.
Interjections are, in Felix Ameka’s memorable formulation, “the universal yet neglected part of speech” (1992). They are rarely the subject of historical, typological or comparative research in linguistics, and they are notably underrepresented in descriptive grammars. As grammars are the main source of data for typologists, this is of course a perfect example of a self-reinforcing feedback loop. How can we break this trend?
Will synthetic text generators usher in a new age of creative thinking? The remarkable fluency of large language models may make them interesting tools for rapidly exploring semantic and stylistic spaces, yet the deceptive ease with which they generate output also provides countless new ways of appropriating ideas and erasing authorship. To better understand challenges and opportunities in this domain, we consider the interactional foundations of human creativity. Drawing on documented cases of creative collaboration, we argue that there is a world of a difference between text generation and true grasp — and that the friction and interaction that comes with the latter may be a meaningful element of human collaborative creativity.
We don’t generally see PhD dissertations as an exciting genre to read, and that is wholly our loss. As the publishing landscape of academia is fast being homogenised, the thesis is one of the last places where we have a chance to see the unalloyed brilliance of up and coming researchers. Let me show you using three examples of remarkable theses I have come across in the past years.
No mind is an island (after John Donne). In a new piece, we make the case for putting interaction at the heart of cognition. This represents a figure-ground reversal for the cognitive sciences, which traditionally have focused on single minds.
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. Or you can go meta and think critically about what it takes to make a point that is as compelling as this in both form and content. See, and I like that second move a lot more.
Part of the struggle of writing in a non-native language is that it can be hard to intuit the strength…