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Summary

The paper presents Human–AI collaboration as “joint cognitive development,” arguing that the way tasks are shared between humans and AI can influence what both learn and how their capabilities develop over time. It brings together work on bounded rationality, Human–Automation/HCI, and AI-agent memory to propose a framework linking task allocation, experience, learning, and future collaboration. The paper concludes with six directions for future research.

Major Issues

The main issue is that the “joint cognitive development loop” is presented somewhat more confidently than the available evidence supports. The paper itself acknowledges that the complete loop has not yet been empirically demonstrated. It would therefore be helpful to distinguish more clearly between what is supported by existing research and what is being proposed as a conceptual framework.

Some of the six research questions also overlap with gaps already discussed in the continual-learning and agent-memory literature. The paper could strengthen its contribution by showing more explicitly how these questions emerge from the proposed framework itself.

Minor Issues

No significant minor issues at this stage.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.