CONCEPT
Intelligence Overload
The condition in which available <em>cognitive processing capacity</em> exceeds the organism's capacity to direct it — a throughput problem no filter can govern, because the overload is in what can now be done, not in what is received.
Information overload, the classical pathology, described paralysis when incoming data exceeded processing capacity — an input problem that sophisticated filtration (libraries, indexes, peer review, editorial standards) could manage. Intelligence overload, the pathology the AI transition produces, is structurally different: the volume of available cognitive throughput exceeds the organism's capacity to meaningfully deploy it. No filter can govern capability itself. The tool builds anything the user can describe; the capacity to discriminate between the possible and the worthwhile has not expanded correspondingly, and the gap between execution and choice produces a specific form of disorientation that information-overload theory cannot explain.
In The You On AI Field Guide
The Berkeley study by Xingqi Maggie Ye and Aruna Ranganathan, published in Harvard Business Review in February 2026, documented intelligence overload in its early stages through eight months of ethnographic embedding in a 200-person technology company. Three findings map directly onto the framework: AI does not reduce work but intensifies it; work seeps
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