Imagine developing a research project through repeated conversations with an AI assistant. The assistant retrieves an earlier hypothesis, connects it to a new question, and identifies a tension between your previous assumptions and your current argument. You challenge its interpretation, revise the record, and reconsider your position. In a later conversation, that revision shapes both your reasoning and the assistant’s responses.

How should we understand the cognitive relationship taking shape here?

In my recent article, From evolutionary individuality to cognitive integration: a cross-modular perspective on human–AI coevolution, I distinguish evolutionary individuality from cognitive individuality. The former concerns the emergence of higher-level evolutionary units; the latter concerns the organization through which a system maintains, accesses, and revises cognitive content. Increasing cooperation between humans and AI leaves the relationship between these forms of individuality open.

The cross-modular perspective offers one way to investigate this relationship. It considers interactions among partially specialized systems, including language, event memory, perception, affect, and social evaluation. Stronger cognitive integration would involve persistent, reciprocal exchanges through which content remains available across domains and open to correction.

Shared memory provides a concrete starting point. In the research scenario above, the important question is how a recorded discussion becomes part of subsequent inquiry. Does an earlier correction change later interpretations? Can an idea developed during writing inform planning or evaluation? Can the user identify where a remembered claim originated and challenge the interpretation attached to it?

A useful experiment might compare a jointly revisable event record with an equally informative, one-way retrieval aid. Across repeated sessions, researchers could examine whether reciprocal updating supports transfer between remembering, reasoning, and planning. They could also test whether corrections carry forward consistently when the same event is encountered in a different task. If the apparent advantages disappear once information access is matched, that would weaken the case for the proposed form of integration. Positive findings would support particular criteria while leaving the stronger claim of cognitive individuality open.

There is also a conceptual question: must integration involve a shared representational architecture, or could coordinated, complementary representations be sufficient? Requiring too much unity might overlook the value of differences between human and artificial processes. Requiring too little might make almost any reliable assistance count as integration. Where should the threshold lie?

Human agency belongs within this discussion. Consider an AI record that gradually turns an exploratory suggestion into an apparent statement of the user’s settled beliefs. Who can recognize the change, contest it, and ensure that the correction affects future interactions? The ability to inspect and revise an interaction history could become an important dimension of how we evaluate these relationships.

My article treats constitutive cognitive integration as an unestablished possibility. I would welcome perspectives on the following questions:

• What evidence would distinguish jointly maintaining an event representation from accurately retrieving someone’s history?

• Which forms of cross-task transfer would support a stronger claim of cognitive integration?

• Could complementary representations be sufficient without a unified model?

• How should human control over interpretation and revision shape our criteria for integration?

Examples from research, education, creative work, and everyday AI use could help clarify where these boundaries belong.