Algorithmic Discipline: A Critical Assessment of Self-Regulatory Framework of Child-Friendly Content in Contemporary Indonesia’s Digital Media Landscape
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Abstract
Digital media consumption among children in Indonesia has surged, positioning video-on-demand (VoD) platforms as key mediators of content access. In the absence of responsive regulatory frameworks, these platforms increasingly rely on self-regulatory regimes, particularly age classification systems and algorithmic recommendation mechanisms, to manage what minors can access. This article critically examines how three VoD platforms operating in Indonesia define, implement and justify such strategies. Drawing on qualitative interviews with representatives from three platforms, this study employs thematic analysis to map divergent governance models shaped by platform type, from algorithmically driven global entities to value-focused local suppliers. Using media governance theory, the study argues that the regulation of children’s content is increasingly displaced from public oversight to proprietary, opaque and market-driven infrastructures. In this fragmented regime, normative power is unevenly allocated, with platforms disproportionately governing visibility and age classification. Child protection is thus rearticulated through proprietary computational logic rather than shared social norms, foregrounding urgent questions of accountability, sovereignty and algorithmic power. The article calls for a hybrid governance model grounded in child rights and institutional auditability.
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