提出可信自治武器系统设计框架，强化军事场景下AI透明性与责任归属
Trust or Bust: Ensuring Trustworthiness in Autonomous Weapon Systems
- 构建跨领域协作机制，融合技术、伦理与战略视角
- 强调人机协同与系统可解释性以保障合规与问责
- 适合关注军事AI伦理与可信系统设计的研究者
自主武器系统（AWS）在军事行动中的应用带来巨大机遇与挑战。本文探讨了AWS中信任的多维度特性，强调建立可靠透明系统对降低偏见、操作故障及责任不清风险的重要性。尽管人工智能取得进展，其在高风险军事场景中的可信度仍是关键问题。通过系统梳理现有文献，研究识别出开发与部署阶段对信任动态理解的空白，并倡导技术专家、伦理学者与军事战略家协同应对。研究强调人机协同与系统可解释性对确保责任追溯和遵守国际人道法的重要性。本文旨在推动对自主武器系统伦理影响的持续讨论，以及国防领域可信AI的必要性。
原文摘要 · Abstract (English)
The integration of Autonomous Weapon Systems (AWS) into military operations presents both significant opportunities and challenges. This paper explores the multifaceted nature of trust in AWS, emphasising the necessity of establishing reliable and transparent systems to mitigate risks associated with bias, operational failures, and accountability. Despite advancements in Artificial Intelligence (AI), the trustworthiness of these systems, especially in high-stakes military applications, remains a critical issue. Through a systematic review of existing literature, this research identifies gaps in the understanding of trust dynamics during the development and deployment phases of AWS. It advocates for a collaborative approach that includes technologists, ethicists, and military strategists to address these ongoing challenges. The findings underscore the importance of Human-Machine teaming and enhancing system intelligibility to ensure accountability and adherence to International Humanitarian Law. Ultimately, this paper aims to contribute to the ongoing discourse on the ethical implications of AWS and the imperative for trustworthy AI in defense contexts.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。