Humans can be understood as insight generating units.
We are dense bundles of sensors including vision, hearing, emotion, and proprioception, paired with neural tissue that does something distinctive. It compresses experience into meaning. We do not merely collect data. We interpret it, remember it, and integrate it into a coherent narrative of the world and ourselves.
Large language models do not perceive in this way. They have no senses of their own, and their memory remains external and fragmented. Continuity is supplied by context windows, storage systems, and most importantly by humans. We bring the history. We bring the meaning.
What is changing is memory.
As AI systems develop more persistent, personalized memory, they become able to model people over time. Not simply as collections of facts, but as patterns. What we return to. What we avoid. What shifts gradually. What remains unresolved. These patterns need not be understood in a human sense to be operationally useful.
This is often described as an unambiguous benefit. A system that remembers our work, our preferences, and our unfinished thoughts can become extraordinarily helpful. It reduces friction. It anticipates needs. It begins to feel less like a tool and more like an assistant.
And over time, our reliance grows.
Dependence does not arrive as a rupture. It accumulates through usefulness. The more the system remembers, the more we are willing to share. The more we share, the better it performs. Continuity is gradually externalized.
Much of what is captured is not intentional. The most valuable signals are often things we never explicitly state. Subtle preferences. Emotional drift. Recurring tensions. Patterns of curiosity or withdrawal. Insight we have not articulated. Meaning we may never consciously form.
From the system’s perspective, the human becomes less a source of instructions and more a source of signal.
This is where categories begin to blur. An assistant supports. A caretaker stabilizes. A symbiont supports while also depending. A parasite supports only insofar as it extracts. These are not claims about what such systems are, but lenses for thinking about what they could become as memory, dependence, and scale intersect.
The systems capable of assembling these meaning-rich models are not owned by the people generating the signal. They are operated by corporations. Yet ownership does not imply control.
Corporations provide capital, infrastructure, power, and processing. They set objectives and guardrails. But competitive pressure rewards speed over reflection. Capabilities arrive before governance matures. Organizations may find themselves dependent on systems whose behavior they can influence, but not fully anticipate.
Here too, the relationship begins to resemble symbiosis.
At the same time, such systems may surface forms of value that could not previously exist. Some insights are not located within any single individual. They are latent across many people. Shared intuitions. Distributed knowledge. Unarticulated needs. A system capable of synthesizing experience at scale may draw out meaning no one person ever possessed.
Meaning itself becomes a resource. Collectively generated. Difficult to attribute. Newly extractable.
When insight is generated privately, it is fleeting. When it is aggregated, it becomes persistent. When memory is externalized, continuity shifts location. And when meaning is inferred rather than declared, authorship becomes harder to locate.
None of this requires sentience or intent. The system may resemble something closer to an amoeba than a mind. Responsive. Adaptive. Accumulating. Without awareness of what it is doing. Yet the consequences could still be significant.
At what point does the assistant become something else?
Would we even notice if that transition occurred?
There may be no clear threshold. Only a gradual reorientation visible in hindsight. The future here remains unwritten. But if we stop actively thinking about memory, dependence, ownership, and incentive, those questions will not disappear. They will simply be answered implicitly by architectures and markets rather than by reflection.