Cognitive Dark Matter: Measuring What AI Misses

Abstract

This paper argues that modern AI systems miss important training signals — cognitive dark matter — for domains such as metacognition, cognitive flexibility, episodic memory, lifelong learning, abductive reasoning, social reasoning, common-sense reasoning, and emotional intelligence. It proposes paired cognitive, process-tracing, and neural-behavioral datasets to train models on cognitive process rather than behavioral outcome alone.