CONCEPT
Epistemic Commons
A shared knowledge base about the effects of AI on professional practice — <em>produced by and for</em> the affected population, governed collectively, and independent of technology companies' research infrastructure.
The epistemic commons is the institutional response to epistemic capture: a shared knowledge base about AI's effects on professional practice, produced by and for the affected population rather than by the companies whose systems they use. The commons would include empirical studies of AI's effects on professional quality, longitudinal tracking of AI-augmented career trajectories, comparative analyses of different deployment approaches, and case studies documenting both successes and failures from perspectives the incumbent research infrastructure systematically under-represents. Its construction addresses the knowledge asymmetry that currently ensures AI policy discussion is shaped by industry-aligned frameworks and metrics. Its governance, following Ostrom's design principles for commons institutions, requires deliberate mechanisms for preventing capture by any particular constituency.
In The You On AI Field Guide
The need for epistemic commons arises from a specific structural problem: the technology companies currently control the bulk of the data generated by the use of their products, the funding for most research about their effects, the venues where that research is published, and the professional networks
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