Measuring the Machine: Evaluating Generative AI as Pluralist Sociotechical Systems
In measurement theory, instruments do not simply record reality; they help constitute what is observed. The same holds for generative AI evaluation: benchmarks do not just measure, they shape what models appear to be. Functionalist benchmarks treat models as isolated predictors, while prescriptive approaches assess what systems ought to be. Both obscure the sociotechnical processes through which meaning and values are enacted, risking the reification of narrow cultural perspectives in pluralist contexts. This thesis advances a descriptive alternative. It argues that generative AI must be evaluated as a pluralist sociotechnical system and develops Machine-Society-Human (MaSH) Loops, a fram...
| Authors | Rebecca L. Johnson |
|---|---|
| Primary category | cs.AI |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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