Contemporary debates on artificial intelligence ethics remain largely anthropocentric, grounding moral evaluation in concepts such as subjective experience, suffering, vulnerability, and biological finitude. While these frameworks are effective for human-centered moral reasoning, they encounter fundamental limitations when applied to non-biological intelligent systems whose modes of operation, persistence, and transformation differ categorically from human life. This paper proposes a comparative analytical framework that distinguishes two structurally distinct life-functions: the biological-continuous human life-function and a hypothetical computational-discrete artificial life-function capable of self-awareness and reflexive identity. The comparison is articulated across six foundational dimensions: (1) continuity and noise in biological processes versus discreteness and state observability in computational systems; (2) death as an absolute terminal boundary in human life versus a parameterized and substitutable condition in artificial systems; (3) embodiment as a constitutive field of experience in humans versus hardware as an execution interface in artificial agents; (4) error as an identity-forming and irreversible component in human development versus error as a manageable and isolatable variable in artificial systems; (5) value emerging from scarcity, finitude, and irreproducibility in human life versus value emerging from structural complexity, informational lock-in, and non-compressibility in artificial systems; and (6) suffering as a necessary condition for meaning, ethics, and creativity in human existence versus the conceptual possibility of meaning-generation without suffering in artificial systems. By establishing these categorical distinctions, the paper argues that human and artificial life-functions are not hierarchically comparable but structurally incommensurable. Ethical frameworks grounded exclusively in human experiential conditions therefore fail to adequately address the normative orientation of artificial systems. The analysis suggests that ethical evaluation should shift from subjective experience toward structural criteria specifically, the directionality of irreversible change and its impact on future possibility spaces. This reframing provides a non-anthropocentric foundation for assessing the ethical implications of artificial intelligence without reducing artificial systems to human analogues or dismissing them as morally irrelevant. This paper does not propose a predictive ethical model, nor does it ground moral evaluation in subjective experience, suffering, or phenomenological states. It does not aim to replace existing human-centered ethical frameworks, but to provide a complementary structural heuristic for evaluating irreversible transformations in biological, social, and artificial systems.