Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, ML 47, Locked Bag 4, Maroochydore DC, Queensland, 4558, Australia; Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia.
Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia; School of Health, University of the Sunshine Coast, Australia. Electronic address: https://twitter.com/gemma_read.
Appl Ergon. 2025 Jan;122:104382. doi: 10.1016/j.apergo.2024.104382. Epub 2024 Sep 11.
The introduction of advanced digital technologies continues to increase system complexity and introduce risks, which must be proactively identified and managed to support system resilience. Brain-computer interfaces (BCIs) are one such technology; however, the risks arising from broad societal use of the technology have yet to be identified and controlled. This study applied a structured systems thinking-based risk assessment method to prospectively identify risks and risk controls for a hypothetical future BCI system lifecycle. The application of the Networked Hazard Analysis and Risk Management System (Net-HARMS) method identified over 800 risks throughout the BCI system lifecycle, from BCI development and regulation through to BCI use, maintenance, and decommissioning. High-criticality risk themes include the implantation and degradation of unsafe BCIs, unsolicited brain stimulation, incorrect signals being sent to safety-critical technologies, and insufficiently supported BCI users. Over 600 risk controls were identified that could be implemented to support system safety and performance resilience. Overall, many highly-impactful BCI system safety and performance risks may arise throughout the BCI system lifecycle and will require collaborative efforts from a wide range of BCI stakeholders to adequately control. Whilst some of the identified controls are practical, work is required to develop a more systematic set of controls to best support the design of a resilient sociotechnical BCI system.
先进数字技术的引入持续增加系统复杂性并引入风险，必须主动识别和管理这些风险，以支持系统弹性。脑机接口 (BCI) 就是这样一项技术；然而，该技术在广泛的社会应用中产生的风险尚未得到识别和控制。本研究应用基于结构化系统思维的风险评估方法，前瞻性地识别假设未来 BCI 系统生命周期的风险和风险控制。网络危害分析和风险管理系统 (Net-HARMS) 方法的应用在 BCI 开发和监管到 BCI 使用、维护和退役的整个系统生命周期中确定了超过 800 个风险。高关键性风险主题包括不安全 BCI 的植入和退化、未经请求的大脑刺激、错误的信号被发送到安全关键技术以及 BCI 用户支持不足。确定了 600 多个风险控制措施，这些措施可以实施以支持系统安全性和性能弹性。总体而言，在 BCI 系统生命周期中可能会出现许多具有高度影响力的 BCI 系统安全性和性能风险，这将需要广泛的 BCI 利益相关者共同努力，以充分控制。虽然已经确定了一些可行的控制措施，但仍需要开展工作，制定更系统的控制措施，以最佳支持弹性社会技术 BCI 系统的设计。
