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Generative Artificial Intelligence (AI) offers tremendous potential in various domains but also raises critical ethical concerns. Key issues include the potential for misuse in spreading misinformation, the perpetuation of biases present in training data, the implications for privacy and data rights. It is crucial for developers, regulators and the public to collaborate in establishing robust ethical frameworks. These frameworks should guide the development and deployment of generative models, ensuring responsible use that maximizes benefits while mitigating risks. In this context the transparency, accountability, and public engagement emerge as foundational principles for navigating the ethical landscape of Generative AI. The aim of the paper is to propose a conceptual framework for solving ethical issues in Generative AI, after exploring issues, challenges, and implications for finding a more accountable integration of the technology into society.
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Stored only when both papers are in the corpus — 43 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.