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

arXiv: https://arxiv.org/abs/2308.02678 · HTML: https://mlsanity.com/paper/2308.02678/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Aug 2023.

## Built on by (most cited first, 5 of 5)

- [Large Language Models for Software Engineering: A Systematic Literature Review](https://mlsanity.com/paper/2308.10620/) (2023)
- [ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming](https://mlsanity.com/paper/2404.08676/) (2024)
- [Advances in Embodied Navigation Using Large Language Models: A Survey](https://mlsanity.com/paper/2311.00530/) (2023)
- [ChatGPT Code Detection: Techniques for Uncovering the Source of Code](https://mlsanity.com/paper/2405.15512/) (2024)
- [EXPLORA: Efficient Exemplar Subset Selection for Complex Reasoning](https://mlsanity.com/paper/2411.03877/) (2024)

## Abstract (arXiv)

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.