Why AI systems don't learn – On autonomous learning from cognitive science

This paper critically examines why current AI models fail at autonomous learning and proposes a cognitively inspired architecture. The framework combines learning from observation (System A) and active behavior (System B), governed by meta-control signals (System M), drawing on how organisms adapt across evolutionary and developmental timescales.