Cognitive Access Parity in AI Systems A Technical–Ethical Addendum to SUPREME-1 v3.0, OMNIA-1, and EROS-1

The deployment of artificial intelligence systems in low-connectivity and resource-constrained contexts introduces a structural risk of cognitive exclusion driven by non-neutral interaction channels. In many such settings, access to AI is mediated primarily through written, asynchronous text, rather than spoken or multimodal interfaces. This addendum examines the neurocognitive non-equivalence between written and spoken language, integrating evidence from functional neuroimaging and cognitive load theory to show that writing imposes systematically higher cognitive, motor, and environmental demands. Building on the ethical and technical architectures of SUPREME-1 v3.0, OMNIA-1, and EROS-1, the document formalizes new cross-framework requirements addressing channel-induced inequality. It introduces the concept of Cognitive Access Parity (CAP) as a metric for evaluating whether AI interaction modalities disproportionately disadvantage vulnerable populations. The addendum extends existing requirements with explicit provisions for cognitive channel equity, channel redundancy under degraded conditions, and assessment of induced cognitive load. By reframing access modality as a matter of computational justice rather than interface preference, this addendum provides a normative basis for preventing AI systems from amplifying pre-existing inequalities in low-connectivity environments.