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Navigating LLM Ethics: Advancements, Challenges, and Future Directions (2406.18841v3)

Published 14 May 2024 in cs.CY, cs.AI, and cs.CL

Abstract: This study addresses ethical issues surrounding LLMs within the field of artificial intelligence. It explores the common ethical challenges posed by both LLMs and other AI systems, such as privacy and fairness, as well as ethical challenges uniquely arising from LLMs. It highlights challenges such as hallucination, verifiable accountability, and decoding censorship complexity, which are unique to LLMs and distinct from those encountered in traditional AI systems. The study underscores the need to tackle these complexities to ensure accountability, reduce biases, and enhance transparency in the influential role that LLMs play in shaping information dissemination. It proposes mitigation strategies and future directions for LLM ethics, advocating for interdisciplinary collaboration. It recommends ethical frameworks tailored to specific domains and dynamic auditing systems adapted to diverse contexts. This roadmap aims to guide responsible development and integration of LLMs, envisioning a future where ethical considerations govern AI advancements in society.

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Authors (4)
  1. Junfeng Jiao (22 papers)
  2. Saleh Afroogh (15 papers)
  3. Yiming Xu (64 papers)
  4. Connor Phillips (1 paper)
Citations (9)