Why AI systems don't learn and what to do about it: Lessons on autonomous learning from cognitive science
Summary
A cognitive science–inspired critique of current AI learning limits, proposing a two-system autonomous learning architecture (observational learning and active behavior learning) with a meta-control mechanism to switch between them. The article argues for integrating biological principles to enable AI to adapt to dynamic real-world environments, with implications for the design of future AI tools and automation systems.