In cultural heritage projects and artistic documentation, motion capture has emerged as a key archival strategy that is promised to be a “next stage” solution in preserving and accessing the past. However, motion capture is not an objective recording; it transposes a technological bodily imaginary onto the bodies whose movements it documents. This essay is situated at the intersection of current critical discourses on archives, dance and AI, bringing domain-specific knowledge to reimagine biased algorithmic systems. Although there is substantial risk for representational harms in how current AI motion models are used to render dancing bodies as data, recent projects show that retaining the entanglement of expert practitioners can refine data processing. We argue that incorporating the specificity of dance-based knowledge can support more meaningful historical research practices, in particular when understanding how bodies are themselves also archives. This contributes to identifying and countering the harms that arise from the mismatch between what automated motion extraction systems purport to accomplish and what they actually represent. The article outlines questions and guidelines that reimagine motion data through a visceral approach for an era of AI.

This article examines the collecting that occurred after the 2018 referendum to repeal the Eighth Amendment to the Irish Constitution, using the collections database as a lens for understanding how this recent period of Irish history is currently being narrativized. The Eighth Amendment prohibited abortion in almost all circumstances by equating the life of a pregnant person to that of the unborn child; its repeal was a result of four decades of grassroots, feminist campaigning. The collections now being preserved depict this activism, and are made up of campaign documents, photographs, and first-person stories archived from Facebook. Through a close analysis of the database of the Digital Repository of Ireland, where most of these materials are held, this article argues for an interpretation of the database as a political infrastructure, which refracts existing tensions surrounding the future of Irish feminisms and the activist archive. It also examines the database’s politics of visibility in relation to the shame and silence that defined women’s position in Ireland prior to the referendum and advances a theorisation of the archival database as a historiographical technology, which plays an active role in the production of Irish identity in the wake of the Eighth.

Foundation models are many things and encompass several modalities; they use text, images, sound, and more recently, action or inference units. But all of these forms share one thing in common: the (massive) scale. The “large” in large language models has been well studied by scholars in critical data, AI and archive studies, with several experts pointing at how these models are environmentally harmful, technically opaque and corporationally monopolistic primarily because of their scale. This piece discusses questions of technical and cultural scale – in the material, archival and procedural senses – within the contemporary technical and discursive landscape. At stake here is the role of critical and design studies within academic, artistic and para-academic worlds. It suggests that instead of corporate chatbots that aspire to pass the Turing test through multipurpose, encyclopedic service, we may be better served by playing with local models and reaching for small-scale AI development. This epistemological shift, in fact, may also provide some creative and critical potential that more effectively gets at the strangeness of machine learning systems while consciously and carefully handling the scalar environmental and social impacts of big AI.