Reasoning about responsibility in autonomous systems: challenges and opportunities

Reasoning about responsibility in autonomous systems: challenges and opportunities
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推理自治系统中的责任:挑战与机遇

DOI:
10.1007/s00146-022-01607-8
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发表时间:
2022
期刊:
影响因子:
3
通讯作者:
Yazdanpanah V
Yazdanpanah V
中科院分区:
--
文献类型:
--
作者:
Yazdanpanah V

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确保自主系统和人工智能的可信赖性是一项重要的跨学科努力。在本立场文件中,我们认为,这一努力将受益于技术进步,以获取各种形式的责任,我们提出了一个全面的研究议程,以实现这一目标。特别是,我们认为确保自主系统的可靠性可以利用技术方法来量化责任程度并在此基础上协调任务。此外,我们认为,在证明人工智能系统的合法性时,责任、指责、问责和责任的正式和计算上可实现的概念适用于解决潜在的责任差距(即一个群体负责,但个人责任可能不明确的情况)。这是一个呼吁,使人工智能系统本身,以及那些参与设计、监控和治理人工智能系统的人,能够表示和推理谁可以被视为在未来负责(例如,在未来完成任务),谁可以被视为在过去负责(例如,对于已经发生的失败)。为此,在这项工作中,我们表明,在设计、开发和部署可信自治系统(TAS)的所有阶段,责任推理应该发挥关键作用。这份立场文件是建立一个路线图和研究议程的第一步,关于责任的概念如何为确保人工智能的可靠性和合法性提供新的解决方案概念,从而使人工智能技术有效地融入社会。
Ensuring the trustworthiness of autonomous systems and artificial intelligence is an important interdisciplinary endeavour. In this position paper, we argue that this endeavour will benefit from technical advancements in capturing various forms of responsibility, and we present a comprehensive research agenda to achieve this. In particular, we argue that ensuring the reliability of autonomous system can take advantage of technical approaches for quantifying degrees of responsibility and for coordinating tasks based on that. Moreover, we deem that, in certifying the legality of an AI system, formal and computationally implementable notions ofresponsibility,blame,accountability, andliabilityare applicable for addressing potential responsibility gaps (i.e. situations in which a group is responsible, but individuals’ responsibility may be unclear). This is a call to enable AI systems themselves, as well as those involved in the design, monitoring, and governance of AI systems, to represent and reason about who can be seen as responsible in prospect (e.g. for completing a task in future) and who can be seen as responsible retrospectively (e.g. for a failure that has already occurred). To that end, in this work, we show that across all stages of the design, development, and deployment of trustworthy autonomous systems (TAS), responsibility reasoning should play a key role. This position paper is the first step towards establishing a road map and research agenda on how the notion of responsibility can provide novel solution concepts for ensuring thereliabilityandlegalityof TAS and, as a result, enables an effective embedding of AI technologies into society.
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