Measuring the meta and cognitive abilities of air defence operators

Introduction: This study aimed to understand more fully some factors that influence decision confidence and accuracy related to air defence. To investigate the metacognitive abilities of air defence operators a Within-Subjects Confidence-Accuracy (W-S C-A) measure was used. Specifically, therefore, this study investigated the impact of Decision Criticality (DC) and Task Stress (TS) on decision making, measures of confidence, accuracy, and the W-S C-A relation. Personality constructs, workload and situation awareness were also included. Method: Participants were allocated to either a high, moderate or low task stress condition. Each participant then took part in a computer generated air defence scenario where they were required to make various decisions and provide a confidence rating for each of those decisions. Confidence, accuracy and W-S C-A were calculated. Results & Discussion: DC impacted both on decision confidence and accuracy, with low DC increasing confidence in decisions and high DC increasing accuracy in decisions

Design Requirements for Effective Hybrid Decision Making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

Design requirements for effective hybrid decision making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

A Cognitive Analysis of Truck Drivers’ Right-hand Turns

This paper presents an investigation of truck drivers' performance during right-hand turns performed in in- tersections with traffic lights in order to elicit the truck drivers' domain, decision-making processes, and the strategies used while executing the turns. To gain knowledge about this, a truck driving instructor was inter- viewed, and four truck drivers were observed and interviewed. This resulted in a cognitive work analysis with the phases work domain analysis, control task analysis and strategies analysis. Through this study it is indi- cated that many different types of information are sought using several brief glances in mirrors, and the results shows how the front and near-zone mirrors were never used by the participants during the observed right-hand turns. Controlling the vehicle was found to be mainly automatic, whereas their focus is on the orientation about surroundings. Lastly, the drivers' behavior is discussed in relation to change blindness, con- firmation bias and schemes

A Cognitive Analysis of Truck Drivers’ Right-hand Turns

This paper presents an investigation of truck drivers' performance during right-hand turns performed in intersections with traffic lights in order to elicit the truck drivers' domain, decision-making processes, and the strategies used while executing the turns. To gain knowledge about this, a truck driving instructor was interviewed, and four truck drivers were observed and interviewed. This resulted in a cognitive work analysis with the phases work domain analysis, control task analysis and strategies analysis. Through this study it is indi- cated that many different types of information are sought using several brief glances in mirrors, and the results shows how the front and near-zone mirrors were never used by the participants during the observed right-hand turns. Controlling the vehicle was found to be mainly automatic, whereas their focus is on the orientation about surroundings. Lastly, the drivers' behavior is discussed in relation to change blindness, confirmation bias and schemes

Design requirements for effective hybrid decision making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

Interoperability: maintaining clear superordinate goals, reducing task complexity, and optimizing team size to ensure inter-agency action implementation in critical incident decisions.

This study demonstrates how naturalistic decision-making (NDM) can be usefully applied to study ‘decision inertia’ – Namely the cognitive process associated with failures to execute action when a decision-maker struggles to choose between equally perceived aversive outcomes. Data assessed the response and recovery from a sudden impact disaster during a 2-day immersive simulated emergency response. Fourteen agencies (including police, fire, ambulance, and military) and 194 participants were involved in the exercise. By assessing the frequency, type, audience, and content of communications, and by reference to five subject matter experts’ slow time analyses of critical turning points during the incident, three barriers were identified as reducing multiagency information sharing and the macrocognitive understanding of the incident. When the decision problem was non-time-bounded, involved multiple agencies, and identification of superordinate goals was lacking, the communication between agencies decreased and agencies focused on within-agency information sharing. These barriers distracted teams from timely and efficient discussions on decisions and action execution with seeking redundant information, which resulted in decision inertia. Our study illustrates how naturalistic environments are conducive to examining relatively understudied concepts of decision inertia, failures to act, and shared situational macrocognition in situations involving large distributed teams

Um estudo sobre a dificuldade enfrentada pelos decisores em projetar impactos de decisões complexas.

Decision makers face challenges in complex decisions making. Many of them are associated with these decisions characteristics and the context in which they are embedded. To make a decision you need to know and detail the different possibilities. These are tasks that cognitively overload the decision maker, since complex analysis and decision-making deals either with the unknown and with the high volume of actions. This report presents the difficulty faced by decision makers in designing impacts of complex decisions, through a bibliographical survey and analysis of approaches to decision support. In this analysis it was observed that some proposals support the impacts projection in a superficial way, preventing in some cases the impacts discovery and making difficult the analysis of dynamic objects. The results obtained with this analysis were confirmed in interviews with real decision makers.Decisores enfrentam desafios na tomada de decisões complexas. Muitos destes, estão associados às características dessas decisões e ao contexto em que elas estão inseridas. Para tomar uma decisão é preciso conhecer e detalhar suas diferentes possibilidades. Essas são tarefas que sobrecarregam cognitivamente o decisor, uma vez que a análise e tomada de decisão complexa lida ou com o desconhecido e com o volume alto de ações. Este relatório apresenta a dificuldade enfrentada pelos decisores em projetar impactos de decisões complexas, através do levantamento bibliográfico e análise de abordagens para o suporte à decisão. Nesta análise foi observado que algumas propostas oferecem suporte à projeção de impactos de maneira superficial, impedindo em alguns casos a descoberta de impactos e dificultando a análise de objetos dinâmicos. Os resultados alcançados com essa análise foram confirmados em entrevistas com decisores reais