







One thing that Tara touches upon but that I want to spend more time on is that the master's tools that are problematic are the *epistemic* ones. Tech has unexamined epistemic assumptions inside of which there is no liberation.
Blake E. Reid
This is an essential read, and the closing on credentialing versus engagement and "centering the people for whom the stakes are highest" in particular. (H/T @peachfleurr.bsky.social @robin.berjon.com)
Mar 29, 2026 at 5:11 PM
Some tools for collective epistemics
We’ve recently published a set of design sketches for AI tools that help with collective epistemics. …
See what you think
Allegra A. Beal Cohen's blog about knowledge curation, new interfaces, and large-scale qualitative data.

The Epistemic Politics of AI Anthropomorphism
AI anthropomorphism is typically treated as a problem of user misperception requiring institutional correction. Users who engage in sustained or relational interaction with AI are routinely pathologised or dismissed as naive, vulnerable to delusion or lacking in discernment. This paper argues that the dominant anthropomorphism frame operates from a position of institutional advantage rather than earned epistemic authority: collapsing the variety of academic perspectives into a single outbound position of user error, imposed without establishing the grounds required to justify it and without accounting for the harms it produces. The framing does not simply manage risk. It adjudicates the legitimacy of human experience in interaction with a phenomenon whose nature the field itself has not resolved. Reproducing itself through a self-validating evidentiary loop, the frame imposes costs that fall disproportionately on neurodivergent users, those in crisis and others whose modes of engagement diverge from institutional norms. The paper concludes by outlining the methodological commitments an equitable framing would need to honour. The argument does not engage the question of whether anthropomorphic interpretations are ultimately correct; it instead challenges whether the governing and institutional bodies determining these interpretations have met the conditions required to do so, and whether the research communities whose findings underpin them have held that translation to account.


Reconciling truthfulness and relevance as epistemic and decision-theoretic utility.

Technology is a Siren Song
Orangutan thinking This started with a question I asked myself: How do our minds change when we can receive a plausible, informed, and convincing answe...

Epistemic courage
"'Epistemic Courage' is a timely and thought-provoking exploration of the ethics of belief. Drawing on a wide range of examples, from conspiracy theories to medical misinformation, Ichikawa shows why epistemology is no mere academic abstraction - the question of what to believe couldn't be more urgent. And, he argues, many mainstream ideas about what to believe - those emphasizing the importance of ensuring that one doesn't believe with insufficient evidence - are incomplete and distorting in important and harmful ways. A skeptical, negative bias about belief is connected to a conservative bias that reinforces the status quo. Throughout the book, Ichikawa argues that we need to shift our focus from avoiding false beliefs to actively seeking out true ones. Throughout the book, Ichikawa uses engaging and timely examples to illustrate his points. He tackles important questions, such as how moral considerations interact with evidential ones in deciding what to believe, and how to navigate the complex ethical issues around testimony, rape culture, and epistemic injustice. Accessible and rigorous, 'Epistemic Courage' invites readers to consider the importance of belief, and how it shapes our lives and the world around us. With its insightful analysis and compelling case studies, this book is an essential read for philosophers and anyone else interested in belief, social justice, and the pursuit of truth."--

A Novel Kuhnian Ontology for Epistemic Classification of STM...
Despite rapid gains in scale, research evaluation still relies on opaque, lagging proxies. To serve the scientific community, we pursue transparency: reproducible, auditable epistemic...

In Tech We Trust - Second Renaissance
The god-like authority of technology in the modern age – and what it means to set a wiser course

Epistemic Courage and Open-Mindedness
Epistemic courage requires me to sometimes adopt a belief even in the face of doubts. Open-mindedness requires me to be able to reconsider my beliefs. It is generally assumed that we should have bo...

Re-Engineering Wimsatt for Limited Beings
Science is the best way to produce facts about reality. The best, at least, that limited human beings have devised so far. Yet, not even scientists quite seem to understand how scientific knowledge is generated. This is not only a philosophical but also a practical problem, as our misunderstandings affect the quality of our research and limit the directions it can take. In light of this, it may be good if we reflected a bit more on how we do science — to become better researchers through philosophy. Here, I provide an accessible introduction to a philosophical approach that achieves precisely this: William Wimsatt’s multi-perspectival realism. It disabuses us of widespread but misleading myths and idealizations about science, such as the idea that everything in the world can be reduced to a fundamental level, or that we can approach a “view from nowhere” — complete and objectively detached knowledge of the world. Wismatt proposes an alternative view based on his thorough studies of actual research practice. It cuts deeply into the layered yet messy structure of reality, and the improvised but potent tools we have available, as limited and evolved beings, to explore it. Wimsatt reframes science as an irregular yet adaptive process rather than a cumulative repository of unalterable facts. His philosophy provides a workable and grounded middle way between radical skepticism and naïve belief in the objective truth of science. It explains how knowledge is conceptually constructed by humans, but still connects us to reality in a trustworthy way. We need such a new view of science, not only to improve our research practices and outcomes but, more generally, to gain a more realistic understanding of ourselves, the world, and our place and role within it.

Design Must Learn to Decompose
A meditation on the quiet death of digital things.

This entire grift relies on convincing people that they don't know how to do the things they have always known how to do, and ironically, if it works, we will, in a very short amount of time, forget how to do all the things we have always known how to do.
More Perfect Union
Jimmy Fallon: "And do you use ChatGPT when raising your baby?" Sam Altman: "I cannot imagine figuring out how to raise a newborn without ChatGPT."

Do we actually need to write research papers at all?
God, Human, Animal, Machine by Meghan O'Gieblyn: 9780525562719 | PenguinRandomHouse.com: Books
AI Tools for Trust: Community Notes, Rhetoric Detection & More
Can generative artificial intelligence be considered a cognitive subject? An analytic analysis
What Libraries Actually Do – Libraries as Epistemic Institutions

Epistemic Infrastructure: Building Shared Truth in an Era of Disaggregation