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Agathe Balayn

@amabalayn.bsky.social

166 followers 241 following 7 posts

Postdoc researcher @MicrosoftResearch, previously @TUDelft. Interested in the intricacies of AI production and their social and political economical impacts; gap policies-practices (AI fairness, explainability, transparency, assessments)

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Agathe Balayn @amabalayn.bsky.social · 08/04/2026

🧑‍🎨🤖 HCI x AI supply chains ⛓️ Join us at our CHI'26 meetup! If you design AI-powered applications, we can start asking together which parts of the supply chains (e.g., APIs, data pipelines, hardware infra) behind these applications we should account for as HCI practitioners and researchers.

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Reposted by Agathe Balayn

Alexandra Olteanu @aolteanu.bsky.social · 18/06/2025

We have to talk about rigor in AI work and what it should entail. The reality is that impoverished notions of rigor do not only lead to some one-off undesirable outcomes but can have a deeply formative impact on the scientific integrity and quality of both AI research and practice 1/

Print screen of the first page of a paper pre-print titled "Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor" by Olteanu et al. Paper abstract: "In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI community, including overblown claims about AI capabilities. Our position is that a broader conception of what rigorous AI research and practice should entail is needed. We believe such a conception -- in addition to a more expansive understanding of (1) methodological rigor -- should include aspects related to (2) what background knowledge informs what to work on (epistemic rigor); (3) how disciplinary, community, or personal norms, standards, or beliefs influence the work (normative rigor); (4) how clearly articulated the theoretical constructs under use are (conceptual rigor); (5) what is reported and how (reporting rigor); and (6) how well-supported the inferences from existing evidence are (interpretative rigor). In doing so, we also aim to provide useful language and a framework for much-needed dialogue about the AI community's work by researchers, policymakers, journalists, and other stakeholders."

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Agathe Balayn @amabalayn.bsky.social · 25/04/2025

I will be at #CHI25 in person this week 🇯🇵 I'm looking forward to chat about **AI supply chains** from socio-technical & organizational / regulatory & governance / political economic lenses. I'll present my work at the main conference (honorable mention), and attend the #HEAL and #STAIG workshops.

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