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    <abstract>Researchers claim to measure large language models. Measurement and evaluation differ epistemically: evaluation asks whether outputs are fit for use; measurement requires a pre-existing quantitative attribute. LLM variability is designed, not discovered; evaluate models, measure people. Critical AI literacy proves, in simulation, most measurable where AI is least capable.</abstract>
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%0 Conference Proceedings
%T Measuring the User, Not the Model: Critical AI Literacy
%A Briggs, Derek
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-0-0
%F briggs-2026-measuring
%X Researchers claim to measure large language models. Measurement and evaluation differ epistemically: evaluation asks whether outputs are fit for use; measurement requires a pre-existing quantitative attribute. LLM variability is designed, not discovered; evaluate models, measure people. Critical AI literacy proves, in simulation, most measurable where AI is least capable.
%U https://aclanthology.org/2026.aimecon-main.45/
%P 407-412

Markdown (Informal)

[Measuring the User, Not the Model: Critical AI Literacy](https://aclanthology.org/2026.aimecon-main.45/) (Briggs, AIME-Con 2026)

• Measuring the User, Not the Model: Critical AI Literacy (Briggs, AIME-Con 2026)

ACL

• Derek Briggs. 2026. Measuring the User, Not the Model: Critical AI Literacy. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 407–412, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).