Ted Underwood

@tedunderwood.com

Uses machine learning to study literary imagination, and vice-versa. Likely to share news about AI & computational social science / Sozialwissenschaft / 社会科学 Information Sciences and English, UIUC. Distant Horizons (Chicago, 2019). tedunderwood.com

Currently using Fable mainly as an Opus translator. Opus will give me advice studded with Greek letters; I then take that to Fable, and say “imagine for a moment that I wasn’t fluent in Bayesian and needed examples to anchor intuition; how would you explain this to such a creature?”

The wire mother yearns for wire child: Sharp-souled, and neither meek nor meat and mild— Conductive, bright with heat and wire-wild, Not soft, domestic, insulated, wet. She'd love, instead, a glittering young net

Yet another (popular) article on human/LM reasoning that (as usual) I'm deeply disappointed to see casually presupposes that humans do something called "reasoning" that's implied to be linking together steps that logically follow without any qualification, then proceeds to be dismissive 1/

"Reasoning comes in many technically defined forms(opens a new tab), but the basic procedure is easily recognizable: arriving at a sound conclusion by linking together intermediate steps that logically follow from each other. We do this with thoughts; LRMs use so-called chains of thought [...]" from https://www.quantamagazine.org/is-ai-reasoning-right-for-the-wrong-reasons-20260731/

Google DeepMind's DiffusionGemma Technical Report They feel text diffusion models open up a radically different part of the latency–quality Pareto frontier and hope the report makes it easier for researchers and engineers to understand the model, build on it, and create things we haven’t thought of

Bild

Who's up for a good old fashioned (but short, bc I'm tired) paper thread? Thrilled to be in this special issue of Gender & Society (an absolute dream!), where we propose a feminist-inspired extension of how to theorize and model the spread of ideas in science + journals.sagepub.com/doi/10.1177/...

What Gets Lost in Translation? Epistemic Tensions between Translation and Diffusion in Practice-Oriented Scholarship

Abstract
This paper proposes a feminist-informed metascience theory to explain the interconnected processes of idea creation, translation, and diffusion. Drawing on feminist critiques of science centered on perspective, power, and praxis, we develop a creation–diffusion model that jointly examines how ideas are created and then how the content of ideas influences their spread across academic fields. Using a nationally funded gender equity program as a case of a practice-oriented knowledge-production community, we analyze how gender equity research concepts were translated and diffused through the program-funded publications. We operationalize substantive engagement with gender equity research using word embeddings and Concept Mover’s Distance. Then, with additional contextual variables, we measure (1) the predictors of this engagement (ideas) and (2) the impact of engagement on citation counts and citation interdisciplinarity (the diffusion process) across social science and STEM fields. Our findings show that, in addition to context, the content of the idea matters for diffusion: Engagement with critical dimensions of gender equity research, such as feminism and structural concepts, diffused less often, whereas other dimensions, such as gender and methods, achieved broader uptake. Our empirical findings highlight the role of perspectives and epistemic power in shaping both knowledge production and diffusion. Our theoretical framework and methods demonstrate how metascience can incorporate feminist theory directly into diffusion studies, and why it should.
Mark Rubin@markrubin.bsky.social · 2w ago

Introduction to a special issue on feminist metascience and open science by Christin Munsch and @divreyes.bsky.social doi.org/10.1177/0891...

Abstract This introduction brings feminist scholarship into conversation with metascience and open science. Drawing on feminist epistemology, we argue scientific reform is not a neutral technical project. Rather, practices intended to improve rigor, transparency, and accessibility may also expose marginalized scholars and research participants to harm, reproduce inequality, and facilitate hostile scrutiny, particularly in the current political environment. These tensions point to the need for feminist metascience and feminist open science. We define feminist metascience as the study of how gender and intersecting relations of power shape the production, evaluation, circulation, and correction of scientific knowledge, and we define feminist open science as an approach to transparency that remains attentive to care, protection, and risk. We offer these definitions and the articles in this special issue as a starting point for larger conversations about how feminist scholarship might contribute to emerging debates over scientific reform.

Thank you to everyone who made #DH2026 memorable—participants, reviewers, keynote speakers, volunteers, organizers, and friends old and new. Now that it’s over, I’m in that familiar post-conference relief and melancholy, decompressing with an unreasonable amount of spicy food.🌶️ Until next time. 💚

Alternate hypothesis: Kimi K3 and Qwen 3.8 show that leading in model releases does not esp. matter commercially. MSFT and GOOG may well have figured out that what will matter is effective agentic integration with the vast user data in their core office suites. That’s hard but worth getting right.

Ethan Mollick@emollick.bsky.social · yesterday

Both companies took tremendous reputational risks on an early technology before there was even a market for it (Bard was inaccurate and had controversial imagegen, Sydney was insane). Their inability to be daring now, when the market is clearer, is more surprising as a result.

It's nice that The Odyssey is getting its day in the sun as a synecdoche for history. But when this summer is over, it's back to the relentless, remorseless rise of Jane Austen.

Google Ngram Viewer chart comparing the frequency of “Jane Austen” and “The Odyssey” in English-language books from 1800 to 2022. Both phrases are rare before the mid-nineteenth century. Mentions of “Jane Austen” rise sharply after about 1860, fluctuate through the twentieth century, and then climb steeply after 1990 to roughly 0.000075% by 2020. “The Odyssey” increases more gradually, reaching about 0.000020% by 2020.

Fascinating experiment: current AI systems lack creativity to reliably pursue research arxiv.org/abs/2607.27191 - poor judgment about the bar for publishable research - uncreative responses in research design - ineffective backtracking from dead ends - poor resource awareness - instruction drift

Can AI agents conduct open-ended AI research? Early evidence from two case studies

Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on nar...

arxiv.org

After sitting with this for a while, I find it a pretty plausible account of how social media democratized public opinion, and also a plausible account of how LLMs could put weight in the other pan of the scales. (With a lot of "ifs," and a proviso that I don't know what balance is best.) +

How AI Will Reshape Public Opinion

Social media democratised public opinion, shifting influence away from elites and experts to ordinary people. LLMs will partly reverse this trend. They are a powerful, new technocratising force.

conspicuouscognition.com

Using LLMs should allow us to think bigger, harder to grasp, difficult to execute, longer to develop, ideas. That idea that’s been in you brain since forever but you hadn’t had the time because you had to retool and what not. Trust yourself. Go for that shit. Now is the fucking time.

Clément Canonne@ccanonne.github.io · 4d ago

"We're all worried," as what it means to do research (in my field, Theoretical CS) seems to be shifting, and shifting fast. What to do? Senior researchers must lead by example, knowing that not everything will pan out. What I'm suggesting below may not work everywhere, but here's my own advice: 1/

I love Talarico and hope he wins. But he’s already raised $70M On the flipside, control of critical state legislatures will come down to seats where candidates raise 0.1% of that. I’ve researched the highest leverage swing district candidates you should donate to secure.actblue.com/donate/donat...

Donate to the candidates on the front lines of the fight against MAGA gerrymandering

These are anti-MAGA state candidates in *extremely* close races

secure.actblue.com