Utility Without Trust: AI Adoption, Public Distrust, and the Sovereign AI Response (2017–2026)

Abstract

Abstract Between 2025 and 2026, empirical surveys across 47 countries document a structurally paradoxical condition in the AI adoption landscape: 66 percent of people use AI with intentional regularity, yet fewer than half - 46 percent - are willing to trust it, and only 18 percent in the United States would trust AI to take autonomous action on their behalf. This paper formalizes this divergence as the Utility-Trust Paradox and identifies four structural mechanisms producing it: (1) hallucination and epistemic unreliability; (2) cognitive enfeeblement and labor displacement; (3) deepfake-driven erosion of shared institutional reality; and (4) AI power concentration and governance deficit. The paper introduces a complementary geopolitical argument: the verified record of sovereign AI initiatives launched by six nations and two multilateral alliances between 2017 and 2026 constitutes institutional-level evidence of the same four distrust mechanisms operating at the state scale. Nations are building independent AI infrastructure not merely to compete, but because they do not trust the epistemic reliability, data sovereignty, cultural alignment, or long-term governance of foreign AI systems. Evidence is triangulated across three tiers: large-scale global survey data (n=48,000+; 47 countries), practitioner commentary on public discourse among verified and high-engagement X-platform accounts (January–May 2026; offered as contextual observation, not formal coded analysis), and a curated corpus of peer-reviewed and preprint academic literature. The paper proposes a Sovereign Trust Alignment (STA) framework - operationalized across four components with identified implementation actors, audit mechanisms, and priority deployment sectors. A corrected and verified sovereign AI timeline (2017–2026) is presented as a primary evidence table.

Ähnliche Arbeiten