Identifying risk controls for future advanced brain-computer interfaces: A prospective risk assessment approach using work domain analysis

Brandon J King; Gemma J M Read; Paul M Salmon

doi:10.1016/j.apergo.2023.104028

Identifying risk controls for future advanced brain-computer interfaces: A prospective risk assessment approach using work domain analysis

Appl Ergon. 2023 Sep:111:104028. doi: 10.1016/j.apergo.2023.104028. Epub 2023 May 4.

Authors

Brandon J King¹, Gemma J M Read², Paul M Salmon³

Affiliations

¹ Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia. Electronic address: Brandon.King@research.usc.edu.au.
² 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.
³ Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia. Electronic address: https://twitter.com/DrPaulSalmon.

PMID: 37148587
DOI: 10.1016/j.apergo.2023.104028

Abstract

Brain-computer interface (BCI) technologies are progressing rapidly and may eventually be implemented widely within society, yet their risks have arguably not yet been comprehensively identified, nor understood. This study analysed an anticipated invasive BCI system lifecycle to identify the individual, organisational, and societal risks associated with BCIs, and controls that could be used to mitigate or eliminate these risks. A BCI system lifecycle work domain analysis model was developed and validated with 10 subject matter experts. The model was subsequently used to undertake a systems thinking-based risk assessment approach to identify risks that could emerge when functions are either undertaken sub-optimally or not undertaken at all. Eighteen broad risk themes were identified that could negatively impact the BCI system lifecycle in a variety of unique ways, while a larger number of controls for these risks were also identified. The most concerning risks included inadequate regulation of BCI technologies and inadequate training of BCI stakeholders, such as users and clinicians. In addition to specifying a practical set of risk controls to inform BCI device design, manufacture, adoption, and utilisation, the results demonstrate the complexity involved in managing BCI risks and suggests that a system-wide coordinated response is required. Future research is required to evaluate the comprehensiveness of the identified risks and the practicality of implementing the risk controls.

Keywords: Brain-computer interfaces; Risk assessment; System modelling.

MeSH terms

Brain-Computer Interfaces*
Electroencephalography / methods
Humans
Prospective Studies
Risk Assessment