Gemma Read

Recent advancements in brain–computer interface (BCI) technology suggest that the potential for wide-spread introduction into society is rapidly approaching. Therefore, it is timely to consider how they can be designed to ensure that safe, high performing, and commercially viable technologies are developed. Considering the BCI system development lifecycle, key processes range from the marketing of regulatory approved BCIs, the mitigation of safety risks, and providing appropriate and long-term support to users to name a few. Systems thinking theories and methods are uniquely suited to analyze the BCI development lifecycle and identify design insights to influence such considerations. This chapter describes the analysis of an envisioned future invasive BCI system using a systems hierarchical task analysis, the development of a model of BCI safety and performance risk sources, and the identification of design insights using sociotechnical system design principles. The subgoals or system functions throughout the BCI system lifecycle and their operations were identified. Sources of BCI risks were identified and themed into broad categories, including BCI design, BCI application, the user, user support, and society. BCI system data and risk sources were applied alongside sociotechnical system design principles to identify a variety of system-wide design insights. These insights may be applied by BCI organizations to evaluate their performance on proactive safety and performance measures and to prompt the mitigation of shortfalls.

Ensuring that artificial intelligence (AI) technologies support ethical decision-making is a critical contemporary challenge in defense. Human factors and ergonomics (HFE) has a key role to play in the evolution of AI; however, there is little guidance on how HFE methods can be used to inform the design of ethical AI technologies. More broadly, there is little guidance on HFE methods that can be used to assess other aspects of AI technologies such as usability and safety. This chapter presents a framework of HFE methods for safe, ethical, and usable AI, developed through a review of HFE methods and a series of workshops. The framework describes a range of activities that should be undertaken throughout the defense life cycle to ensure the design and operation of ethical AI technologies, along with a set of HFE methods that could be applied during each phase. The framework highlights multiple opportunities to assess ethical principles, as well as the need to apply HFE methods early in the life cycle. We discuss important areas for future research, including applications of the framework as well as the development of early life-cycle methods that could be used to prospectively consider ethical principles when identifying capability needs.

This chapter covers the value and utility of computational modelling in the field of sports injury prevention research. First, an overview of what computational modelling is and why it should be used is provided. This section includes the different purposes of computational modelling more generally and is not specific to sports injury research. Second, two computational modelling approaches, Agent-Based Modelling (ABM) and System Dynamics (SD) Modelling, are introduced given their capability to study the characteristics of complex sports injury systems. There are many different types of computational modelling methods to choose from; however, the emphasis throughout this chapter is placed on approaches that can be used to simulate and dynamically understand the behaviour of complex systems. Third, the association between computational modelling, systems ergonomics research and the science of sports injury control is clarified, and future directions proposed.

Despite Olympic success in the equestrian discipline of eventing, Australia has struggled to qualify to send a team in the discipline of dressage. Performance pathways give direction to athletes whilst providing the opportunity to be recognised and facilitate acquisition of the skills integral to success. Literature on performance pathways in all sports is generally limited in its reductionist approach. Further there has been no research in the area of dressage or performance pathways in dressage. This study aimed to apply a systems approach to identify the current dressage performance pathways. A model of Australian Dressage Performance Pathways was developed using the Systems Theoretic Accident Model and Processes (STAMP) approach. It was validated by subject-matter experts, who indicated a high level of agreement with a draft STAMP model and recommended minor amendments which were incorporated into a final model. The STAMP model showed that there were many constraints within the system with little feedback loops coming from the bottom up. The model highlights the need for new feedback mechanisms within dressage to promote performance pathways. For example, improvements in communication between riders and the associations such as Equestrian Queensland and Equestrian Australia. This model could be taken as a general model of dressage and other Olympic equestrian disciplines such as show jumping. Further, given the similarity in the structure of dressage to other sports, the model could be easily adapted for other sports also.

Hierarchical task analysis (HTA), arguably the most popular task analysis method of all time, provides a useful approach for describing expert behavior and the factors influencing it. Its utility is enhanced by the fact that there are various ergonomics analysis methods that build on HTA outputs to provide in-depth analyses of behavior. This chapter provides an overview of HTA and its origins, followed by practical guidance on how to apply the method. Two rail level crossing case study applications are presented. These are used to showcase how HTA can be used to describe and analyze both behavior at the sharp end (i.e., at the rail level crossing itself) as well as the behavior of overall sociotechnical systems (i.e., the behavior of the overall rail level crossing “system”). In closing, the main strengths and weakness of HTA are discussed.

Over the past decade, Cognitive Work Analysis (CWA) has been one of the popular human factors approaches for complex systems evaluation and design applications. This is reflected by a diverse range of applications across safety critical domains. The book brings together a series of CWA applications and discussions from world-leading human factors researchers and practitioners. It begins with an overview of the CWA framework, including its theoretical underpinnings, the methodological approaches involved (including practical guidance on each phase), and previous applications of the framework. The core of the book is a series of CWA applications, undertaken in a wide range of safety critical domains for a range of purposes. These serve to demonstrate the contribution that CWA can make to real-world projects and provide readers with inspiration for how such analyses can be practically carried out. Following this, a series of applications in which new approaches or adaptations have been added to the framework are presented. These show how practical applications feedback into the theories/approaches underpinning CWA. The closing chapter then speculates on future applications of the framework and on a series of new research directions required in order to enhance its utility. In emphasising the practical realities of performing CWA, and the real-world impacts it can provide, the book tackles several common misconceptions in a constructive and persuasive way. It provides a welcome demonstration of how CWA can be a powerful ally in tackling complexity-related problems that afflict systems in all areas. [Book Synopsis]

Over the past decade, Cognitive Work Analysis (CWA) has been one of the popular human factors approaches for complex systems evaluation and design applications. This is reflected by a diverse range of applications across safety critical domains. The book brings together a series of CWA applications and discussions from world-leading human factors researchers and practitioners. It begins with an overview of the CWA framework, including its theoretical underpinnings, the methodological approaches involved (including practical guidance on each phase), and previous applications of the framework. The core of the book is a series of CWA applications, undertaken in a wide range of safety critical domains for a range of purposes. These serve to demonstrate the contribution that CWA can make to real-world projects and provide readers with inspiration for how such analyses can be practically carried out. Following this, a series of applications in which new approaches or adaptations have been added to the framework are presented. These show how practical applications feedback into the theories/approaches underpinning CWA. The closing chapter then speculates on future applications of the framework and on a series of new research directions required in order to enhance its utility. In emphasising the practical realities of performing CWA, and the real-world impacts it can provide, the book tackles several common misconceptions in a constructive and persuasive way. It provides a welcome demonstration of how CWA can be a powerful ally in tackling complexity-related problems that afflict systems in all areas. [Book Synopsis]

Advocates of systems thinking approaches argue that accident prevention strategies should focus on reforming the system rather than on fixing the "broken components." However, little guidance exists on how organizations can translate incident data into prevention strategies that address the systemic causes of accidents. This article describes and evaluates a series of systems thinking prevention strategies that were designed in response to the analysis of multiple incidents. The study was undertaken in the led outdoor activity (LOA) sector in Australia, which delivers supervised or instructed outdoor activities such as canyoning, sea kayaking, rock climbing and camping. The design process involved workshops with practitioners, and focussed on incident data analyzed using Rasmussen's AcciMap technique. A series of reflection points based on the systemic causes of accidents was used to guide the design process, and the AcciMap technique was used to represent the prevention strategies and the relationships between them, leading to the creation of PreventiMaps. An evaluation of the PreventiMaps revealed that all of them incorporated the core principles of the systems thinking approach and many proposed prevention strategies for improving vertical integration across the LOA system. However, the majority failed to address the migration of work practices and the erosion of risk controls. Overall, the findings suggest that the design process was partially successful in helping practitioners to translate incident data into prevention strategies that addressed the systemic causes of accidents; refinement of the design process is required to focus practitioners more on designing monitoring and feedback mechanisms to support decisions at the higher levels of the system.

Collisions at rail level crossings (RLXs) involving pedestrians represent a significant public safety concern in Australia and internationally. The most recent statistics available show that between 2002 and 2011, 92 pedestrians were struck by trains at RLXs in Australia (Australian Transport Safety Bureau, 2012). In the United Kingdom, over a similar time frame, 72 pedestrians were killed at level crossings (Rail Safety and Standards Board, 2015). The European Railway Agency has reported 373 fatalities associated with collisions at RLXs in Europe in 2012 alone, with approximately 40% of those killed being pedestrians (European Railway Agency, 2014). It has been noted that Australia and the United States have achieved reductions in the numbers of motor vehicle-train collisions, but not in pedestrian-train collisions (e.g., Australian Transport Safety Bureau, 2012; Metaxatos and Sriraj, 2013). To make gains in improving pedestrian safety at RLXs, a new approach is required. Such an approach recognizes that RLXs are complex sociotechnical systems. Taking this perspective, safety at RLXs is the outcome of interactions between social and technical components such as road users, vehicles (road and rail), equipment, and infrastructure. The interactions can be diverse and random, particularly due to the openness