Navigating the Architecture of Truth: Public Communication Strategies in the Era of Generative Engine Optimization
Keywords:
Generative Engine Optimization; Architecture of Truth; Public Communication; Algorithmic Mediation; Digital GovernanceAbstract
The rapid expansion of generative artificial intelligence (AI) has fundamentally transformed the architecture of truth in digital public spaces, shifting informational legitimacy from institution-based authority toward algorithmically synthesized representation. This study examines how Generative Engine Optimization (GEO) reshapes public communication strategies and explores how public institutions adapt within AI-mediated ecosystems. Drawing on a qualitative critical case study of Indonesian public institutions, data were collected through semi-structured interviews, digital content observations, and policy document analysis. The findings reveal that GEO reconfigures representational power by privileging structured data, semantic interoperability, and machine readability, thereby reducing institutional control over message framing. Public communication now operates within a dual mediation system symbolic and computational where algorithmic synthesis influences the visibility, coherence, and perceived legitimacy of information. In response, this study proposes the “Navigating the Architecture of Truth” model, integrating three strategic dimensions: normative transparency, technological standardization, and public algorithmic literacy. The study extends social construction of reality and public sphere theory by positioning algorithmic systems as non-human agents of objectivation in the construction of public meaning. These findings offer both theoretical refinement and practical guidance for strengthening informational integrity in increasingly algorithm-mediated governance environments.
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