Ontologies as Backbone of Cognitive Systems Engineering

Cognitive systems are starting to be deployed as appliances across the technological landscape of modern societies. The increasing availability of high performance computing platforms has opened an opportunity for statistics-based cognitive systems that perform quite as humans in certain tasks that resisted the symbolic methods of classic artificial intelligence. Cognitive artefacts appear every day in the media, raising a wave of mild fear concerning artificial intelligence and its impact on society. These systems, performance notwithstanding, are quite brittle and their reduced dependability limips their potential for massive deployment in mission-critical applications -e.g. in autonomous driving or medical diagnosis. In this paper we explore the actual possibility of building cognitive systems using engineering-grade methods that can assure the satisfaction of strict requirements for their operation. The final conclusion will be that, besides the potential improvement provided by a rigorous engineering process, we are still in need of a solid theory -possibly the main outcome of cognitive science- that could sustain such endeavour. In this sense, we propose the use of formal ontologies as backbones of cognitive systems engineering processes and workflows

Cognitive Systems Engineering Models Applied to Cybersecurity

Cybersecurity is an increasing area of concern for organizations and individuals alike. The majority of successfully executed cyberattacks are a result of human error. One common type of attack that targets human users is phishing. In spite of this, there is a lack of research surrounding human implications on phishing behavior. Using an online survey platform with both phishing and legitimate emails, the present research examined the utility of various cognitive engineering models for modeling responses to these example emails. Using Signal Detection Theory (SDT) and Fuzzy Signal Detection Theory (Fuzzy SDT), the influence of familiarity with phishing and having a background in cybersecurity on phishing behavior was examined. The results from SDT analysis indicated that familiarity with phishing only accounted for 11% of the variance in sensitivity and 5% in bias. When examining the same using Fuzzy SDT analysis, familiarity with phishing accounted for 6% of the variance in bias. When examining background in cybersecurity using SDT analysis, t-tests indicated the null hypothesis could be rejected for the relationship of background in cybersecurity with sensitivity and bias. When examining the same for Fuzzy SDT, the null hypothesis could only be rejected for the relationship between bias and background in cybersecurity. In addition to these findings, the use of a confusion matrix revealed that the percentage of successfully transmitted information from the stimuli to the judgements made by participants was only 26%. Participant identification of phishing cues was also examined. Participants most frequently identified requests for personal information within the emails. Future research should continue to explore predictors of phishing behavior and the application of the different cognitive engineering models to phishing behavior

Affordances in activity theory and cognitive systems engineering

For the last decade, the Gibsonian concept of affordances has at- tracted much attention within Human-Machine Interaction (HMI) and related research communities. The application of Gibson's ideas in HMI has lead to the notion of direct manipulation of interface objects. Previously, the focus has been on design for low level interaction modalities. To incorporate the concept of affordances in the design of human computer interaction it is necessary to systematically unravel affordances that support human action possibilities. Furthermore, it is a necessity that Gibson's theory of affordances is supplemented by careful analyses of other human modalities and activities than visual perception. Within HMI two well established perspectives on HMI, Activity Theory (AT) and Cognitive Systems Engineering (CSE), have discussed such analyses and design of action possibilities focusing on providing computer support for work situations. Within these perspectives, the primary unit of analysis in HMI is human work activity and the socio-cultural context in which this activity is carried out. Thus, they emphasise the actors' purposeful activity as the most important design rationale. According to previous views in HMI, notably those that have been put forward by Norman and Gaver, affordances are in the foreground, whereas the system or work area is in the background. AT and CSE share the view that the actors' perception of foreground and background shifts dynamically according to the actors' situational context in purposeful activity. AT and CSE follow the original notion by Gibson on the actor's dynamic shifting between foreground and background of the environment. Furthermore, their work- and actor-centred approach to analysis and design of information sys..

Application of Cognitive Systems Engineering Approach to Railway Systems (System for Investigation of Railway Interfaces)

This chapter presents the results of a cognitive systems engineering approach applied to railway systems. This application is through the methodology of ’System for Investigation of Railway Interfaces – SIRI’. The utility of the chapter lies in highlighting errors in the current approaches to safety risk management

Collaborative damage mapping for emergency response : the role of Cognitive Systems Engineering

Remote sensing is increasingly used to assess disaster damage, traditionally by professional image analysts. A recent alternative is crowdsourcing by volunteers experienced in remote sensing, using internet-based mapping portals. We identify a range of problems in current approaches, including how volunteers can best be instructed for the task, ensuring that instructions are accurately understood and translate into valid results, or how the mapping scheme must be adapted for different map user needs. The volunteers, the mapping organizers, and the map users all perform complex cognitive tasks, yet little is known about the actual information needs of the users. We also identify problematic assumptions about the capabilities of the volunteers, principally related to the ability to perform the mapping, and to understand mapping instructions unambiguously. We propose that any robust scheme for collaborative damage mapping must rely on Cognitive Systems Engineering and its principal method, Cognitive Task Analysis (CTA), to understand the information and decision requirements of the map and image users, and how the volunteers can be optimally instructed and their mapping contributions merged into suitable map products. We recommend an iterative approach involving map users, remote sensing specialists, cognitive systems engineers and instructional designers, as well as experimental psychologists

Specifying Space Defense Operator Interfaces through the Application of Cognitive Systems Engineering and Prototyping

The Department of Defense needs better tools to support its operators as they strive to defend its space assets. The growing sophistication of anti-satellite weapons increasingly challenges the nation’s orbital communications and surveillance infrastructure. Operators face difficulties gathering useful information and dealing with the complexity of potential enemy actions. This research applied cognitive systems engineering and ecological interface design (EID) methodologies to create a prototype space mission management tool that enhances operator situation awareness and decision-making ability. Applied cognitive task analysis interviews were used to document space operator decision-making in their domain. Model-based systems engineering was applied to integrate work domain concepts into system models. EID methods were applied to inform user interface designs that support high-level decision making in addition to low-level tasks. User interface concepts were developed using rapid prototyping software, Axure 9.0, to satisfy the system requirements. The software prototypes were shown to space operators and assessed for validity. This process demonstrated how cognitive systems engineering can be used to derive system requirements and create system designs, the elements of which can be captured in a systems model and traced to operator goals, resulting in systems that are more capable of supporting operator needs in challenging environments

Cognitive Systems Engineering: The Next 30 Years

This presentation is part of panel discussion on Cognitive Systems Engineering. The purpose of this panel is to discuss the challenges and future directions of Cognitive Systems Engineering for the next 30 years. I intended to present the work we have been doing with the Aviation Safety program and Space Human Factors Engineering project on Work Domain Analysis and some areas of Research Focus. Specifically, I intend to focus on the shift on the need to understand and model attention in mixed-initiative systems, the need for methods which can generate results to be used in trade-off decisions, and the need to account for a range of human behavior in the design

Cognitive engineering in aerospace applications

The progress that was made with respect to the objectives and goals of the research that is being carried out in the Cognitive Systems Engineering Laboratory (CSEL) under a Cooperative Agreement with NASA Ames Research Center is described. The major objective of this project is to expand the research base in Cognitive Engineering to be able to support the development and human-centered design of automated systems for aerospace applications. This research project is in support of the Aviation Safety/Automation Research plan and related NASA research goals in space applications