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Managing sexually explicit user uploads presents a immensely challenging challenge for platforms that rely on peer-generated media. Unlike traditional paywalls that simply restrict access in exchange for payment, emerging income streams such as virtual gifts, subscriptions, commission-based referrals, and branded partnerships require platforms to maintain a dynamic, trustworthy, and compelling environment. This becomes critically complex when users upload content that may be sexually explicit, provocative, or bokep terbaru violating regional statutes. The unmanageable volume of uploads makes on-demand curation logistically unviable, and machine learning tools often struggle to separate ethical erotic expression, cultural art, and harmful material. over-blocking can silence legitimate creators, while missed detections allow exploitative media to remain visible. Regional norms and laws further create regulatory chaos, as what is acceptable in one region may be illegal in another. Platforms are torn between the need to ensure safety, especially adolescents, and the desire to preserve speech rights and monetization opportunities. Heavy-handed enforcement can reduce engagement, while lenient guidelines risk compliance failures and reputational damage. Many companies are turning to combined systems that integrate machine learning with human judgment, but even these approaches are cost-prohibitive, inconsistent, and subject to prejudice. The lack of clear global standards means platforms must frequently revise, often following viral outrage rather than systematically developing solutions. As creator earnings tie directly to participation, the need for accurate moderation will only grow, demanding not just improved tools but also ethical frameworks that protect users without stifling innovation or equity.