Reasoning about responsibility in autonomous systems: challenges and opportunities
Reasoning about responsibility in autonomous systems: challenges and opportunities
复制标题
推理自治系统中的责任:挑战与机遇
DOI:
10.1007/s00146-022-01607-8
复制
发表时间:
2022
期刊:
影响因子:
3
通讯作者:
Yazdanpanah V
中科院分区:
文献类型:
--
作者:
Yazdanpanah V
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.
登录
查看更多内容
影响因子:
5.8
作者:
Ramchurn SD;Stein S;Jennings NR
通讯作者:
Jennings NR
DOI:
--
发表时间:
1989
期刊:
影响因子:
--
作者:
J. Searle
通讯作者:
J. Searle
DOI:
--
发表时间:
2017
期刊:
Adaptive Agents and Multi-Agent Systems
影响因子:
--
作者:
N. Alechina;Joseph Y. Halpern;B. Logan
通讯作者:
B. Logan
DOI:
--
发表时间:
2002
期刊:
AJR. American journal of roentgenology
影响因子:
--
作者:
L. Berlin
通讯作者:
L. Berlin
DOI:
--
发表时间:
2000
期刊:
ATAL
影响因子:
--
作者:
T. Norman;C. Reed
通讯作者:
C. Reed