C
Standardization
6 plates
- C.12 Cognitive Standardization When everyone consults tools trained on the same dominant data, ways of writing, thinking, and noticing converge — quietly, and at scale.
- C.13 Homogenization of Style and Language The Doshi 2024 study, the classroom literature, and the central case of cognitive standardization — how AI quietly tightens the distribution of how things get written.
- C.14 Filter Bubbles and Algorithmic Bias Pariser's 2011 phrase, Sunstein's variations, and the question fifteen years later — how strong is the filter-bubble effect actually, and what do we know now that we did not know then?
- C.15 Cultural Bias in Generative Models WEIRD-AI — why model outputs default to Western, English-language, urban-industrial assumptions, and what one can and cannot do about it.
- C.16 Creativity Under AI Assistance The paradox the recent literature has surfaced — individuals using AI score higher on creativity measures while groups using AI score lower. What that pattern means and where it leaves us.
- C.17 Preserving Cognitive Diversity Education, technology, and policy responses to cognitive standardization — what each one can and cannot do, and why none alone is sufficient.