Explainable Creator Intelligence: A Human-Centered Framework for Transparent AI Monetization and Content Recommendation in Social Commerce
Keywords:
explainable AI, social commerce, content recommendation, monetization transparency, creator economy, fairness, governance, multi-stakeholder systems, AI infrastructureAbstract
The rapid convergence of social commerce, artificial intelligence, and digital content creation has given rise to complex socio-technical ecosystems in which creators, platforms, advertisers, and consumers interact under opaque algorithmic regimes. Existing recommendation and monetization systems often prioritize engagement metrics and revenue optimization, leaving creators and users without meaningful explanations for why certain content is promoted or how value is distributed. This paper proposes a human-centered framework termed Explainable Creator Intelligence (ECI), which integrates transparency mechanisms into the core architecture of AI-driven content recommendation and monetization in social commerce. The framework builds upon principles of explainable AI, multi-stakeholder governance, and incentive alignment to design systems that are interpretable, auditable, and fair. We examine structural trade-offs between predictive performance and explainability, and between platform efficiency and creator autonomy. The proposed architecture incorporates content provenance verification, micro-licensing compliance, and path-level safety interventions to ensure robust and accountable operations. We also discuss fairness constraints for recommendation algorithms that mitigate creator bias and echo chambers, and we analyze policy implications for regulatory compliance and creator welfare. Sustainability challenges related to computational overhead and data sovereignty are considered. Through cross-domain comparisons with traditional media and finance, the paper highlights the need for standardized transparency APIs and interoperable governance protocols. The ECI framework offers a blueprint for next-generation social commerce platforms that empower creators while maintaining commercial viability and trust. This work contributes to the growing literature on responsible AI commercialization and provides actionable guidance for platform designers, policymakers, and researchers.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
