Cognitive Engineering Research Articles

Stumbling Towards a Shared Apprehension of Automation Failure

Fifteen commentaries have either responded to, or been inspired by, our article about the automation failure construct, which introduced a taxonomy of failure mechanisms for consideration in the design of cognitive engineering experiments. Our rejoinder organizes these responses into those aligned with the objectives of the target article, those inspired by it, a couple that rehash our earlier articles, and one that seeks to put us all in our place. We conclude with an assessment of points of consensus and divergence in our shared apprehension of the automation failure construct.

Choosing the Sweet Life with DOLCE

An ontology in philosophy is a description of what exists; an ontology in information science is the formal specification of a domain for information organization. A top-level ontology is an ontology of high-level abstractions that is meant to provide a standard for other ontologies to make them interoperable. Top-level ontologies commit to certain philosophical assumptions in the worlds they model, such as naive scientific realism, or the choice to model only those worlds which “actually” exist. This paper uses a comparison of Basic Formal Ontology (BFO) and Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) to investigate whether naive scientific realism is useful as a philosophical stance in ontological modelling. It investigates the specific philosophical and technical features of DOLCE which make it unique. BFO and DOLCE are compared, as well as a miniature literature review of comparisons between other top-level ontologies. Then it describes the history of DOLCE and BFO’s development in the context of the collaboration between Barry Smith and Nicola Guarino. Finally, it examines the application of DOLCE in various domains, such as “sweetening” WordNet.

Faces of Oppression: Future directions for Ergonomics and Human Factors

The growing interest in Diversity, Equity, and Inclusion (DEI) centred work in the field of Ergonomics and Human Factors (EHF) can greatly benefit from Iris Young’s Five Faces of Oppression theory, which details how well-intentioned systems can perpetuate harm in a number of ways. We call for a greater focus on systems of oppression in EHF research and practice along with increased collaboration with social sciences to tackle important societal issues. This article reviews the current state of research in the child welfare domain and provides examples for how cognitive engineering approaches can take inspiration from the social sciences to help create a more equitable future. These examples outline the potential mutualism between social sciences and EHF and the way this collaboration might dismantle various oppressive systems.

Trolling for Media Bias, Censorship, and Cognitive Warfare Engineering Psycho-Social Discord

Trolling for Media Bias, Censorship, and Cognitive Warfare Engineering Psycho-Social Discord

Ethical Considerations in AI-Powered Work Environments: A Literature Review and Theoretical Framework for Ensuring Human Dignity and Fairness

This article critically examines the integration of artificial intelligence (AI) into work environments, focusing on the ethical implications that arise. It seeks to underscore the need for balancing technological advancements with the protection of human dignity and fairness, exploring how AI's transformative potential can be harmonized with the core tenets of human rights. The article utilizes a comprehensive literature review to construct a theoretical framework that outlines AI's capabilities and ethical considerations. This framework encompasses the interdisciplinary foundations of AI, including its roots in cognitive psychology, decision theory, and computer engineering. It further delves into the ethical dilemmas presented by AI in the workplace, such as privacy concerns, the risk of bias, issues of accountability, and the broader impact on human rights. This exploration is aimed at understanding the complexities of AI's integration into the labor market and its implications for occupational safety and health. The findings of the article highlight the dual nature of AI as both a catalyst for efficiency and innovation and a source of ethical challenge. It's important to include a lot of different points of view and include everyone in the process of developing AI to make it more fair and respect human rights. Laws and policies need to keep changing to keep up with AI's progress and protect people legally from possible abuses. Strong moral guidelines and clear AI systems are also needed to protect privacy and reduce bias. The study's originality and value emphasize the need for AI ethical discussions in human rights contexts, contribute to technology governance and human rights discussions, and discuss theoretical debates on human dignity, fairness, and privacy in the face of technological advancement.

Literature review: A study of cognitive aspects in minimizing human error in construction

Human error is a mistake due to human negligence, both consciously and unconsciously, which can cause a system to experience disruption and not run as planned. These errors can occur at the managerial, conceptual, or technical level. One of the activities with a high potential for finding human error is construction activities. Construction activities are a series of activities that include the construction, operation, maintenance, demolition, and construction of a building. Infrastructure development is one of the government’s policy focuses in 2023, with development from four main areas: water resources, roads and bridges, settlements, and housing. These infrastructure projects must have a good quality because they are closely related to user safety and security. Based on data from the Social Security Organizing Agency (BPJS) Employment and statements from the Ministry of PUPR, the industrial sector is an enormous contributor to work accidents with an average percentage of 32% each year. The human factor is one of the forerunners of human error apart from equipment and working environment conditions. Viewed from the perspective of Cognitive System Engineering, human error is caused by the failure of human cognitive processes where the process is related to Human Information Processing (HIP). This paper will describe and briefly discuss the problem of human error and its relation to Human Information Processing (HIP). This paper will examine various literature and summarize efforts that can be applied to improve the information processing process in the hope of minimizing the occurrence of human error in the scope of construction work.

Towards Joint Activity Design Heuristics: Essentials for Human-Machine Teaming

As machines increasingly behave more like active cognitive agents than passive tools, additional heuristics for supporting joint human-machine activity are urgently needed to complement existing usability heuristics. Despite the rich and extensive design guidance produced by forty years of cognitive systems engineering (CSE) and related fields, the lack of large-scale impact can be attributed, in part, to insufficient translation of CSE principles and guidelines to language and tools that are ready for designers and other decision-makers responsible for these automation-infused solutions. Towards this need, we synthesized a partial and preliminary list of ten machine requirements intended to capture some of the essentials of joint activity. We believe solidifying these essentials and their implications for machines is a first and necessary step towards deriving joint activity design heuristics that are valuable, practical, and sustainable for operational personnel. Through iterative refinement, we believe the combination of strong ideas and strong practicality in these tools can be the basis for a large-scale shift in the design and evaluation of human-machine teams.

How to explain the rationale of putting research into practice? A book review on <em>Visual-Spatial Ability in STEM Education Transforming Research into Practice</em>

The book is crucial for exposing educational settings to research academics since it is visually appealing. It explains how spatial ability is tested and improved and explores the research procedures and skills utilized in educational settings. It concentrates on the problematic meta-analytic review and addresses two distinct cross-questions, including how large gender disparities in spatial ability are and where gender differences in spatial ability are first observed. The book purposefully covers a wide range of viewpoints, including those from cognitive psychology, educational psychology, science, technology, engineering, mathematics, computer science and information technology. It also addresses human growth. This book gives ideas about the early life span of visuospatial working memory development, along with the impact. As a reader, I found that these abilities have on academic learning with a biological explanation for the observed gender differences that seems to be a contribution to brain development that was shared through the book by the author for readers.

Promoting Honesty in Children, or Fostering Pathological Behaviour?

Promoting Honesty in Children, or Fostering Pathological Behaviour?

HyperCube4x: Exploring and Analyzing Data in Virtual Reality Using HyperRelational and HyperAnalyzer

Hypercube is a novel viewport management and information visualization system proposal that introduces three applications (called WorkScenes), focusing on interaction, immersive reading, data exploration, analysis, and visualization concepts. After presenting the conceptual description, interaction metaphors, and the prototype in a previous publication, this article presents HyperRelational and HyperAnalyzer, the WorkScenes focused on multidimensional data exploration, analysis, and visualization. First, the manuscript explores previous work on Human-Computer Interaction-related disciplines, such as cognitive psychology, cognitive engineering, and neuroscience. Then, we introduce HyperRelational and HyperAnalyzer, focusing on their fundamental concepts 1) Geometrical visualization; 2) mapping relationships among information as spatial dimensions. Also, the Screenshots help illustrate the mentioned concepts. Finally, the “Results and Discussion” section demonstrates how these features integrate with the flow, presence, and immersion of Virtual Reality, fit Shneiderman’s visual-information-seeking mantra and solve some desktop metaphor-related issues. Additionally, we present test results conducted with 26 participants that show an acceptability rate of 74% amongst users and highlight their positive feedback/experience regarding HyperAnalyzer. On the other hand, the System Usability Scale (SUS) evaluation scored 60.6731. The score demonstrates that HyperAnalyser scored a little better than Microsoft Excel. Therefore, we conclude that the concepts presented here are viable, but it is still necessary to evolve usability to make HyperCube commercially viable.

Exploring patient flow management through a lens of cognitive systems engineering

Hospitals work to provide quality, safety, and availability to patients with a wide variety of care needs, which makes efficient prioritisation and resource utilisation essential. Anticipation of each patients’ trajectory, while monitoring available resources across the hospital, are major challenges for patient flow management. This study focuses on how hospital patient flow management is realised in situ with the help of concepts from cognitive systems engineering. Five semi-structured interviews with high level managers and shadowing observations of seven full work-shifts with management teams were conducted, to explore how patient flow is coordinated and communicated across the hospital. The data has been analysed using qualitative content analysis. The results describe patient flow management using an adapted Extended Control Model (ECOM) and reveal how authority and information might be better placed closer to clinical work for increased efficiency of patient flow. Practitioner summary: This study describes how a large tertiary paediatric hospital’s patient flow management functions. The results offer a new understanding of how patient flow management is communicated and coordinated across organisational levels of the hospital and how authority and information might be better placed closer to clinical work for increased efficiency.

The Cognitive Engineering in Manufacturing Process through Reinforcement Learning

The reinforcement learning (RL), through its role, in business integrated manufacturing, means the manufacturing system capacity to ’learn’ in permanent interaction with the economic environment, to inform and update the information about the auctions and to anticipate, before deciding to conclude a contract, the level of costs, profit and what is the best way to act. In other words this means that the manufacturing system ’learns’ what actions to take in certain situations, based on the data supplied by the economic environment, so that such actions increase the possibilities of achieving the aim proposed. The business integrated manufacturing should ’exploit’ what it already knows to obtain profit, but at the same time it must ’explore’ the possibility of finding other suitable actions for the future. The manufacturing system should try a variety of actions and then choose those that seem best. This study shows the potential of RL for application to the business integrated manufacturing.

Successes and critical failures of neural networks in capturing human-like speech recognition

Natural and artificial audition can in principle acquire different solutions to a given problem. The constraints of the task, however, can nudge the cognitive science and engineering of audition to qualitatively converge, suggesting that a closer mutual examination would potentially enrich artificial hearing systems and process models of the mind and brain. Speech recognition — an area ripe for such exploration — is inherently robust in humans to a number transformations at various spectrotemporal granularities. To what extent are these robustness profiles accounted for by high-performing neural network systems? We bring together experiments in speech recognition under a single synthesis framework to evaluate state-of-the-art neural networks as stimulus-computable, optimized observers. In a series of experiments, we (1) clarify how influential speech manipulations in the literature relate to each other and to natural speech, (2) show the granularities at which machines exhibit out-of-distribution robustness, reproducing classical perceptual phenomena in humans, (3) identify the specific conditions where model predictions of human performance differ, and (4) demonstrate a crucial failure of all artificial systems to perceptually recover where humans do, suggesting alternative directions for theory and model building. These findings encourage a tighter synergy between the cognitive science and engineering of audition.

Towards a cognitive engineering of transactional services in IoT based systems

Cognitive computing is the capability of a system to mimic the ability of human brain to learn and adapt from the surroundings. Cognitive systems have decision-making capabilities based on new information, actions and outcomes. Similarly, Internet of Things (IoT) aims at making things smart, and enabling them to perform complex tasks. Reliability and flexibility are persistent challenges in the IoT context where the promise is managing a multitude of devices and delivering real-time responses for critical smart applications. A limited number of studies examine these challenges while considering cognitive capabilities of things and have failed to handle thing’s specificities in terms of communication bandwidth, power availability and storage capacity. Following the service oriented architecture (SOA), the functionality can be encapsulated as services. Thus, automating the management of transactional services in smart IoT ecosystem can be fulfilled through the coupling of transactional properties to cognitive things. This paper provides a comprehensive approach to alleviate reliability restrictions in cognitive IoT service compositions. The concept of cognitive faculty (CF) is introduced to leverage transactional properties of services and can be customized to specific requirements of IoT applications. A proof-of-concept is included in this paper based on a self-monitoring IoT application for diabetic patients.

Human Systems Integration: A Review of Concepts, Applications, Challenges, and Benefits

This paper provides a review of the concepts, applications, and challenges of Human Systems Integration (HSI). HSI is a multidisciplinary field that aims to optimize the performance of human-machine systems by considering the characteristics and capabilities of both human operators and technological systems. The review begins with a discussion of the fundamental concepts of HSI, including human factors engineering, human-computer interaction, and cognitive engineering. It then examines the application of HSI in specific domains such as aviation, transportation, and medicine. The paper concludes by discussing the challenges and future directions of HSI research. The paper highlights the importance of considering the cognitive and affective aspects of human operators in the design of systems and the challenges related to the integration of multiple systems and the consideration of social and organizational factors. Keywords: Human Systems Integration, Healthcare, Manufacturing, Transportation, Benefits, Challenges. DOI: 10.7176/JESD/14-4-04 Publication date: February 28 th 2023

A Task Complexity Analysis Method to Study the Emergency Situation under Automated Metro System.

System upgrades and team members interactions lead to changes in task structure. Therefore, in order to handle emergencies efficiently and safely, a comprehensive method of the traffic dispatching team task complexity (TDTTC) is proposed based on team cognitive work analysis (Team-CWA) and network feature analysis. The method comes from the perspective of the socio-technical system. Two stages were included in this method. In the first stage, four phases of Team-CWA, i.e., team work domain analysis, team control task analysis, team strategies analysis, and team worker competencies analysis, were applied in the qualitative analysis of TDTTC. Then in the second stage, a mapping process was established based on events and information cues. After the team task network was established, the characteristic indexes of node degree/average degree, average shortest path length, agglomeration coefficient, and overall network performance for TDTTC were extracted to analyze TDTTC quantitatively. The cases of tasks for screen door fault under grade of automation GOA1-GOA4 were compared. The results revealed that the more nodes and communication between nodes, the larger the network scale was, which would lead to the TDTTC being more complicated no matter what level of automation system it was under. This method is not only the exploration of cognitive engineering theory in the field of task complexity, but also the innovation of team task complexity in the development of automatic metro operation.

Decision Support for Flexible Manufacturing Systems: Application of the Cognitive Systems Engineering and Ecological Interface Design Approach

We applied the cognitive systems engineering (CSE)/ecological interface design (EID) approach to the work domain of flexible manufacturing systems (FMS). Work domain analyses (WDA) and activity analyses were conducted. Previous concerns regarding the suitability of CSE for FMS are addressed. Principles of EID (i.e., direct perception, direct manipulation, and visual momentum) were applied in designing an ecological interface for a flexible manufacturing system (EcoFlex). The critical links between the products of a WDA and the content of an ecological interface (a key innovation of EID) are made explicit. The evaluations of this interface were very positive across a wide variety of traditional and novel dependent variables (please see the companion manuscript). The overall success of this research program clearly demonstrates that the CSE/EID approach is capable of being applied to FMS. Contributions of this manuscript include both theoretical insights (defining properties of the FMS work domain, concrete examples of the principles of EID, critical links between CSE and EID, resolution of concerns about the overall framework) and practical applications (specific design solutions for FMS and similar work domains, and successful examples of the CSE/EID approach which can be studied and leveraged by students).

Impediments of Cognitive System Engineering in Machine-Human Modeling

A comprehensive understanding of human intelligence is still an ongoing process, i.e., human and information security are not yet perfectly matched. By understanding cognitive processes, designers can design humanized cognitive information systems (CIS). The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information systems. The researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency of human-computer interaction (HCI). A practice-oriented research approach included research analysis and a review of existing articles to pursue a comparative research model; thereafter, a model development paradigm was used to observe and monitor the progression of CIS during HCI. The scope of our research provides a broader perspective on how different disciplines affect HCI and how human cognitive models can be enhanced to enrich complements. We have identified a significant gap in the current literature on mental processing resulting from a wide range of theory and practice.

Multidisciplinary collaboration to develop a digital health solution for early detection of cognitive decline in primary care.

Developing digital healthcare solutions that facilitate rapid identification and effective management of patients with Alzheimer disease and related disorders (ADRD) is an area of intense study. A critical juncture for these efforts involves the early detection of cognitive decline. Because primary care providers (PCPs) are the first line of medical care, they are often the first to hear concerns about cognitive decline. However, under-diagnosis of ADRD in primary care settings is widely recognized, as are the many barriers to routine cognitive screening. While information about brief cognitive screening tools for detecting ADRD is plentiful, PCPs remain uncertain about which patients to assess, which tools to use and how to use them, and how to communicate results. The goal of this project was to design a risk assessment and cognitive screening (RACS) application that specifically addressed the needs and concerns of PCPs to facilitate identification of cognitive decline in primary care settings. We employed a multi-modal assessment approach in designing the RACS app, which first assesses risk for cognitive impairment and then assesses cognitive functioning using a working memory/processing speed task in combination with four speech/language tasks. We assembled a multidisciplinary team with the following expertise to develop and test the app: biostatistics, computational linguistics, computer science, computerized cognitive assessment, gaming/app development, engineering, neurology, neuropsychology, neuroscience, primary care, psychometrics, and speech-language pathology. Programming of app features and pilot testing with people with ADRD was completed in 3 months. Initial development of the connected speech analysis pipeline was completed in 4 months with ongoing testing. Data collection of 50 cognitively normal, 50 mild cognitive impairment, and 50 mild dementia participants is approximately 50% completed within 6 months. Preliminary results based on cognitive performance alone show good ability to discriminate groups. Reduction of speech-language variables for inclusion in a final cognitive performance score is underway using a variety of machine learning techniques, including the elastic net and random forests. The RACS app shows promise as a digital health solution to facilitate early detection of cognitive decline in primary care and may prove useful in other busy clinical settings.

Quality 4.0 and Cognitive Engineering Applied to Quality Management Systems: A Framework

In order to create high-quality products, quality engineering must be integrated across the entire product development process. To accomplish the ultimate goal, innovative approaches are required, and a Quality Management System-QMS is imperative to standardize all processes. All business areas depend on people and processes, but quality is especially dependent on them. A QMS can benefit from the application of Quality 4.0—Q4.0 and Cognitive Engineering—CE aspects to reduce the workload and cognitive capacity required from QMS specialists, using these technologies to tackle long-standing quality concerns and to re-optimize to deliver creative solutions. The decision to implement a QMS based on Q4.0 technologies is difficult to take due to the challenge that is to automatize dispersed activities. The purpose of this paper is to develop a framework that aids in the application of a Q4.0 QMS. The relationship between quality management practices and Industry 4.0 technologies that improve quality are deeply studied and connected with CE practices to develop an advanced framework, that makes it easier to overview all the dispersed activities within the manufacturing environment gathered as one, and simplify the application of new technologies to the QMS activities. The proposed framework was developed as result of this study.