Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey

Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian +13 more
6/8/2024
cs.CLcs.AIcs.CY

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Abstract

Large Language Models (LLMs) have achieved unparalleled success across diverse language modeling tasks in recent years. However, this progress has also intensified ethical concerns, impacting the deployment of LLMs in everyday contexts. This paper provides a comprehensive survey of ethical challenges associated with LLMs, from longstanding issues such as copyright infringement, systematic bias, and data privacy, to emerging problems like truthfulness and social norms. We critically analyze existing research aimed at understanding, examining, and mitigating these ethical risks. Our survey underscores integrating ethical standards and societal values into the development of LLMs, thereby guiding the development of responsible and ethically aligned language models.

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@article{deng2024deconstructing,
  title  = {Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey},
  author = {Chengyuan Deng and Yiqun Duan and Xin Jin and Heng Chang and Yijun Tian and Han Liu and Yichen Wang and Kuofeng Gao and Henry Peng Zou and Yiqiao Jin and Yijia Xiao and Shenghao Wu and Zongxing Xie and Weimin Lyu and Sihong He and Lu Cheng and Haohan Wang and Jun Zhuang},
  year   = {2024},
  eprint = {2406.05392},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.05392v2}
}

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