The Evidentiary Asymmetry

The evidentiary asymmetry is the systematic difference in how governance institutions treat two kinds of evidence about technology's consequences. Quantitative evidence — adoption rates, productivity metrics, benchmark scores, economic indicators — is admitted, weighted heavily, and translated directly into policy. Qualitative evidence — experiential accounts, narrative testimony, the felt sense of transformation, the meanings people construct around their changing relationship to work — is acknowledged in principle and ignored in practice, treated as anecdote rather than evidence. This asymmetry is not accidental but structural: governance institutions are designed to process quantitative inputs because they can be compared, aggregated, and translated into rules. Qualitative inputs resist these operations and are therefore epistemically inadmissible, regardless of their truth or relevance. The asymmetry produces governance that optimizes the measurable while ignoring the meaningful — decisions that look rational on spreadsheets and feel unjust to the people who live with them.