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Trust or Bust: Ensuring Trustworthiness in Autonomous Weapon Systems

arXiv 2410.10284 ↗First posted 14 Oct 2024cs.CY cs.AI cs.ROcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 56 references that are in the map. First posted on arXiv 14 Oct 2024.

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References · 3

  1. 2021Trustworthy AI: From Principles to Practicescited by 207
  2. 2019When Autonomous Intelligent Goodware will Fight Autonomous Intelligent Malware: A Possible Future of Cyber Defensecited by 3
  3. 2020Regulating human control over autonomous systemscited by 3

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