# We Need a New Ethics for a World of AI Agents

arXiv: https://arxiv.org/abs/2509.10289 · HTML: https://mlsanity.com/paper/2509.10289/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 3 references that are in the map.
- First posted on arXiv 12 Sep 2025.

## Builds on (most cited first, 2 of 2)

- [Role-Play with Large Language Models](https://mlsanity.com/paper/2305.16367/) (2023)
- [Why human-AI relationships need socioaffective alignment](https://mlsanity.com/paper/2502.02528/) (2025)

## Built on by (most cited first, 9 of 9)

- [Agentic Business Process Management: A Research Manifesto](https://mlsanity.com/paper/2603.18916/) (2026)
- [On the Regulatory Potential of User Interfaces for AI Agent Governance](https://mlsanity.com/paper/2512.00742/) (2025)
- [Would a Large Language Model Pay Extra for a View? Inferring Willingness to Pay from Subjective Choices](https://mlsanity.com/paper/2602.09802/) (2026)
- [What Challenges Do Developers Face in AI Agent Systems? An Empirical Study on Stack Overflow & GitHub Issues](https://mlsanity.com/paper/2510.25423/) (2025)
- [A Research Roadmap for Augmenting Software Engineering Processes and Software Products with Generative AI](https://mlsanity.com/paper/2510.26275/) (2025)
- [A Criminology of Machines](https://mlsanity.com/paper/2511.02895/) (2025)
- [Inducing language models to assert their own consciousness restores human beliefs and values](https://mlsanity.com/paper/2607.28607/) (2026)
- [Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility](https://mlsanity.com/paper/2511.13725/) (2025)
- [Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures](https://mlsanity.com/paper/2604.18133/) (2026)

## Abstract (arXiv)

The deployment of capable AI agents raises fresh questions about safety, human-machine relationships and social coordination. We argue for greater engagement by scientists, scholars, engineers and policymakers with the implications of a world increasingly populated by AI agents. We explore key challenges that must be addressed to ensure that interactions between humans and agents, and among agents themselves, remain broadly beneficial.