<![CDATA[The rapid expansion of generative artificial intelligence has transformed media broadcasting by enabling automated content creation, synthetic personalities, real-time production, and personalized audience interaction within decentralized digital ecosystems. However, this transformation also raises critical concerns regarding ethical accountability, audience trust, algorithmic transparency, energy consumption, and the sustainability of AI-driven broadcasting infrastructure. This study aims to examine how human-centered generative AI can support ethical and sustainable media broadcasting while maintaining creativity, journalistic integrity, audience engagement, and environmental responsibility. The method research employs a qualitative conceptual approach based on a structured literature review of recent studies on generative AI, digital media broadcasting, decentralized content systems, AI ethics, and green computing. The analysis is organized around key dimensions, including human-centered design, synthetic media governance, audience personalization, decentralized infrastructure, and energy-efficient AI implementation. The Result findings indicate that human-centered generative AI can enhance broadcasting innovation by improving content efficiency, adaptive storytelling, audience relevance, and interactive media experiences. At the same time, ethical safeguards such as AI labeling, provenance tracking, privacy protection, editorial oversight, and transparent algorithmic governance are essential to prevent misinformation, manipulation, and audience distrust. The study also highlights that sustainable broadcasting re- quires optimized AI models, green data centers, and responsible infrastructure management. This paper concludes that the integration of human-centered, ethical, and sustainable principles is necessary to ensure that generative AI strengthens media broadcasting ecosystems without replacing human values, creativity, and social responsibility.]]>
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