Artificial Intelligence Applications in Media Content Production; Emerging Risks or Technological Revolutions?

What is it about?

The rapid integration of Artificial Intelligence (AI) into media content production and screenwriting marks a significant advancement in creative and communicative domains. This study explores the dual impact of AI on one side, its capacity to enhance human creativity, efficiency, and productivity; on the other, it is potential to disrupt established legal frameworks, ethical standards, and cultural representations. In the media production, tools like The Washington Post’s Heliograf exemplify how AI enables real-time, data-driven news production, while simultaneously raising concerns about public trust, misinformation, and editorial transparency. In the realm of screenwriting, generative models such as ChatGPT and ScriptBook introduce innovative methods for content creation, yet also challenge traditional notions of authorship, intellectual property, and labour rights—issues brought into sharp focus by the 2023–2024 Writers Guild of America strike. Through a thematic analysis of legal, ethical, and technological concerns (Tables 3–7), the research highlights risks associated with AI-curated media content, including the reinforcement of bias, marginalization of underrepresented groups, and promotion of cultural uniformity—outcomes often rooted in limitations of training data and editorial oversight. Furthermore, governance challenges—such as system opacity and inadequate stakeholder representation—further complicate AI’s integration into the creative industries. The emotional monotony and cultural inauthenticity of AI-generated scripts underscore the limitations of algorithmic storytelling. The paper concludes that while AI offers transformative possibilities for augmenting human creativity, its responsible implementation necessitates stronger legal protections, robust ethical frameworks, and inclusive governance. The evolution of AI in media production should prioritize equity, diversity, and the human voice over mere efficiency. A collaborative model—where human insight and machine capabilities intersect—offers a path toward innovation rooted in democratic values and culturally resonant storytelling.

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