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The AI Dose-Response Curve

The pharmacological principle — too little produces no effect, too much produces harm — applied to AI exposure, structuring the clinical question that prohibition-vs-endorsement debates obscure.
The dose-response framework Christakis applied to television in 2004 is the template for evaluating AI's developmental impact. Before his study, the screen-time conversation was binary: screens were good or bad, depending on camp. His work transformed it into a pharmacological question: at what dose, at what developmental stage, does the effect transition from benefit to harm? The 2004 paper demonstrated a continuous dose-response relationship for television with ten-percent increments in attentional problems per daily hour of early exposure. The AI version of the question is structurally identical but empirically harder: the measurement unit ('AI time') collapses qualitatively distinct interactions; the relationship is almost certainly non-linear; and — critically — the longitudinal data does not yet exist. The framework nonetheless structures the right question even where it cannot yet provide the answer.

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The measurement problem is severe. Television exposure was simple: the child was watching or not watching, and duration could be estimated by parental report. AI exposure is categorically more complex. A

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