How do human and GPT ethics differ in multi-robot systems?
GPT versus Humans – Uncovering Ethical Concerns in Conversational Generative AI-empowered Multi-Robot Systems
November 23, 2024
https://arxiv.org/pdf/2411.14009This paper explores the ethical concerns arising from using Large Language Models (LLMs) like ChatGPT in multi-robot systems, particularly in conversational settings. It compares the ethical considerations raised by human experts with those generated by LLM agents themselves.
Key points for LLM-based multi-agent systems:
- LLMs offer potential for improved human-robot and robot-robot interaction, but introduce ethical challenges related to bias, misinformation, manipulation, security vulnerabilities, and dependence on technology.
- Human expert concerns focused on deviance, privacy, bias, and corporate misconduct, whereas LLM-generated concerns aligned more with existing AI ethics guidelines.
- The non-deterministic nature of LLMs introduces complexities in multi-robot communication and coordination.
- LLMs' ability to generate human-like text raises concerns about manipulation through seemingly polite and helpful language.
- Human oversight, explainability, transparency, and established communication protocols are crucial for mitigating ethical risks.
- Culture significantly influences both the perceived ethics of the systems and the values encoded within them.
- Deepfakes and their potential impact on multi-robot systems require further investigation.