CONCEPT
The Cognitive Intensity Metric
Coyle's proposed supplementary metric to distinguish efficiency gains from intensity gains — adapting time-use surveys to capture self-reported cognitive load, stress, engagement quality, and perceived sustainability of working patterns.
The first feasible measurement reform Coyle proposes for the AI era is the adaptation of time-use surveys to capture cognitive intensity. Time-use surveys already exist in most OECD countries. They ask respondents to record activities in fine-grained intervals across representative days. The surveys capture what people do with time. They do not currently capture how intensely they do it. Adding intensity measures — self-reported cognitive load, stress, engagement quality, and perceived sustainability — to existing survey instruments would provide, for the first time, a national-level dataset on the cognitive composition of working time.
In The You On AI Field Guide
The data would not be perfect. Self-reported intensity is subject to recall bias, social desirability effects, and the fundamental difficulty of introspection about cognitive states. But approximate data on a critical variable is infinitely more useful than no data at all, and the marginal cost of adding intensity questions to existing surveys is modest relative to the value of the information.
The metric would operationalize the
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