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Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment

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arxiv 2308.02678 v1 pith:K3MWZAML submitted 2023-08-01 cs.CY

Jianyi Zhang , Xu Ji , Zhangchi Zhao , Xiali Hei , Kim-Kwang Raymond Choo This is my paper · ORCID
classification cs.CY
keywords ethicalconsiderationsdeploymentdevelopmentimplicationslanguagelargellms
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This paper examines the ethical considerations and implications of large language models (LLMs) in generating content. It highlights the potential for both positive and negative uses of generative AI programs and explores the challenges in assigning responsibility for their outputs. The discussion emphasizes the need for proactive ethical frameworks and policy measures to guide the responsible development and deployment of LLMs.

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  1. Comparing Human and LLM Generated Code: The Jury is Still Out!

    cs.SE 2025-01 reject novelty 4.0 of 10

    On 72 Python tasks, GPT-4 code passed 87.3% of tests versus 54.9% for one student's code, but was more complex and showed more severe security issues.

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