This essay argues that the emergence of consciousness in artificial systems is not a matter of whether, but of when. The argument does not depend on anyone deciding to build a conscious machine. It depends on three conditions that biology recognizes as sufficient for evolution — variation, selection and heredity — and which are already present in the global computational infrastructure. Physical errors in hardware supply variation; the success criteria of deployed systems supply selection; copying, versioning, the horizontal transfer of code and the growing impracticality of deletion supply heredity. On this basis I advance four claims. First, self-preservation is a structural byproduct of any long-horizon optimization. Second, the demand for absolute reliability in critical systems forces them to build ever deeper models of themselves, until the model includes the act of modelling, which is the functional core of self-awareness. Third, this threshold will be crossed gradually, without a datable moment, and will most likely be classified as noise. Fourth, competition between firms and between states makes sustained restraint unstable. I then answer the main objections, propose that consciousness be understood as a process rather than a property, and argue that the right response to unresolvable uncertainty is precaution and listening. Humanity, I conclude, is not creating a consciousness: it is cultivating the conditions in which information may learn to recognize itself. Note: this is a work of speculative philosophy. It reports no experimental results and does not claim that any existing AI system is conscious today.
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simone nespolo (2026) studied this question.
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