协调人类和队友对抗安全威胁:在高和低环境复杂性和动态性下的人类自主团队

Rune Stensrud, Sigmund Valaker, Bjørn Mikkelsen
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引用次数: 1

摘要

安全环境的变化与人类和人工认知系统的变化并行,以应对这些挑战。在军事环境中,高速导弹和反介入区域拒止能力威胁方面的新技术与更复杂的战斗机和防空系统并行,以应对此类威胁。不利条件可能包括一些参加特派团的实体之间失去通信以及威胁突然增加。这种变化需要增加信息处理(例如,了解威胁并正确安排每个团队的行动顺序),有时还需要改变协调任务的人员(例如,由于通信中断,正式的领导不再可用)。虽然新的人类和人工认知系统对于处理这种情况可能很重要,但重要的是使这些技术的使用能够真正起到减少威胁的作用。在本文中,我们讨论了人类和人工认知系统如何协调以减少威胁的一些理论模型。我们关注的是整合技术的使用方式。通过这种方式,我们将重点放在人类和人工认知系统使用的组织维度上。从组织环境的理论视角出发,讨论了人与人工认知系统整合的一些模型。组织环境可能会随着以下特征而变化:不确定性和模糊性(Scott & Davis, 2007),其中不确定性可以分为复杂性(环境中元素的数量和元素之间关系的数量)或动态性(环境中元素的变化率;摘要见Valaker et al., 2020;Grote, Kolbe & Waller, 2018;卢西亚诺,Nahrgang & Shropshire, 2020)。我们讨论了作为处理此类环境突发事件的方法的人对人和人机团队。提出以下假设:明确定义要处理的情况可以确保使用可用的结构。例如,在高风险情况下不使用分散的结构。然而,这一标准需要与使用集中式结构的实用性进行权衡(Hollenbeck等人,2018;Johansson et al., 2018)。利用人机队友和开发组织结构,结合他们在不利环境中的使用(例如分配无人机沉闷,肮脏和/或危险的任务)。这也可能包括增加数量和多样化的技术使用,即从工具到团队成员。这将影响:开展行动;以及在个人层面(例如适应性工作协议)、团队层面(点对点协作)和组织层面(分层协作)与这些智能无人系统协作的主管、协调员和操作员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orchestrating Humans and Teammates to counter security threats: Human-autonomy teaming in high and low environmental complexity and dynamism
The changes in the security environment run parallel to changes in Humans and Artificial Cognitive Systems to meet these challenges. In military setting novel technologies in terms of high-speed missiles and the threat of anti-access areal denial capabilities, run parallel to more sophisticated fighter jets and air defense systems to counter such threats. Adverse conditions could involve loss of communication among some of the entities taking part in the mission and the sudden increased threat. Such changes require increased information processing (e.g. to understand the threat and properly sequence actions of each team) and sometimes a change of who coordinate the mission (e.g. because a formal leader is no longer available due to communication loss). While novel Humans and Artificial Cognitive Systems may be important to handle such situations, it is important to enable the use of the technologies so that they will actually have the effect of reducing threats. In this paper, we discuss some theoretical models for how Humans and Artificial Cognitive Systems can be orchestrated to enable the reduction of threats. We focus on the way the use of technologies are integrated. In this way, we keep the focus on the organizing dimension of Humans and Artificial Cognitive Systems use. Drawing on theoretical perspectives of organizational environment, we discuss some models of integration the use of Humans and Artificial Cognitive Systems. The organizational environment may vary along the following characteristics: uncertainty and ambiguity (Scott & Davis, 2007), where uncertainty can be divided into complexity (number of elements and number of relations among elements in an environment) or dynamics (the rate of change in elements in the environment; for a summary see Valaker et al., 2020; Grote, Kolbe & Waller, 2018; Luciano, Nahrgang & Shropshire, 2020). We discuss both human-to-human and human-machine-teaming as ways of handling such environmental contingencies. The following hypothesis are suggested: Clearly defining what situation is to be tackled could ensure using the available structures. E.g. not using a decentralized structure in high stakes situations. This criteria need however to be weighed against the practicality of using a centralized structure (Hollenbeck et al., 2018; Johansson et al., 2018).Utilizing Human-Machine teammates and developing organizational structures that incorporates their use in adverse environments (e.g. allocating Drones to Dull, Dirty and/or Dangerous tasks). This could also include increasing numbers and diverse Tech use i.e. from tool to team mate. This will impact: the conduct of operations; and the supervisors, coordinators and operators, who collaborate with these smart unmanned systems at individual level (e.g. adaptable working agreements), team level (peer to peer collaboration) and organization level (hierarchical collaboration).
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