ABSTRACT. There is an increasing and urgent need for infusing Human Systems Integration (HSI) and Human Factors Engineering (HFE) principles and methods to improve safety and quality of operations in complex, adaptive sociotechnical work systems such as in health care. In this presentation, Dr. Gurses will describe how HSI and HFE can be used to improve care across the entire care continuum (i) by systematically identifying hazards to patient safety, health care worker safety, and equity; and (ii) by developing effective and sustainable human-centered interventions with the purpose of eliminating and/or mitigating these hazards and improving adaptive capacity and resilience of the frontline care work and public health. Examples from a variety of health care settings (i.e., emergency department, operating rooms, patient home), and focus areas (e.g., infection prevention and control, pandemic preparedness, care transitions/ handoffs, healthcare information technology) will be provided. Lessons learned across the different projects and implications for future HSI efforts will also be discussed.

ABSTRACT. The integration of autonomous systems is increasing, while the development of future systems faces a growing complexity in their interactions with human operators. Conceptual modeling helps simplify the complexity while also being realistic enough to make sense. This paper demonstrates how a small company that develops an autonomous system for snow plowing machines at airports applies various conceptual models. The paper has classified the conceptual models according to A3AO, CAFCR+, and TOP frameworks with a Human Systems Integration perspective. Findings suggest that a mixed modeling approach with viewpoint hopping is used and found effective during the development of human and autonomous collaboration systems for confined industrial environment.

ABSTRACT. Fintech has sparked a wave of innovation due to the growing use of technology in financial ser-vices, creating consumer benefits and challenges. This research aims to pinpoint the elements affecting consumer protection and satisfaction with fintech services and create a relationship between the two. A questionnaire was used to collect quantitative data from 53 fintech users and six fintech experts. Data analysis was performed through Importance Performance Analysis and Pearson correlation analysis. The findings demonstrated that perceived usefulness through cost and time efficiency, ease of use, perceived risk through trustworthiness and reliability, and consumer innovativeness likely influence consumer satisfaction with Fintech. The paper emphasizes the need for a balanced approach to Fintech that promotes innovation and satisfaction while safeguarding consumer interests

ABSTRACT. The key to a successful implementation of an HSI plan lies in tailoring it to the size and needs of the organization and project. Many R&D project work plans share common milestones and a known structure utilized in most programs. However, the correct implementation of HSI activities and understanding their importance and benefits remain a challenge for many organizations. This is especially true in projects with high levels of technological challenges and system complexity, where the system engineering, along with other engineering teams, primarily focuses on 'making the system work'. In many instances, even experienced engineers are not familiar with the HSI approach. Thus, when it is introduced, often as a requirement or a contractual obligation, it may be perceived as an obstructive factor.

A well-designed HSI plan should serve the needs of the program and produce meaningful outcomes for the benefit of the developed system.

Having executed numerous HSI plans across various industries and projects of differing scales, I have identified several best practices that can help overcome objections and concerns from engineering disciplines and program management. This requires not only a thorough understanding of the subject but also depends on analyzing, understanding, and addressing the project's plan constraints and risks.

An effective HSI plan continually provides valuable inputs to the project, making the human factor an integral part of the basic set of requirements considered.

In my lecture, I will share strategies for setting up a functional HSI plan and how to address the challenges that may arise from the program.

ABSTRACT. In the proposed lecture, we will describe the development of a massive open on-line course (MOOC) entitled “Human-Systems Integration”. The course was developed by us in the recent months and is available in Campus IL, the main MOOC platform in Israel, with the intention to produce versions for international MOOC platforms such as Coursera and Webex. A MOOC makes the contents accessible to a large audience of potential learners who were previously not exposed to them or were partially exposed to them and can now complete their training and knowledge. The course allows learners to learn what they want at their own pace, an important flexibility that makes learning possible for a population that works and finds it difficult to make time for regular training. The course will be offered as part of academic courses, and successful completion of the course will be necessary as part of future training in the field of human-systems integration, in cooperation with various industry bodies and institutions. Up to date, there is no course in this field, in Hebrew or English. Ways to acquire this knowledge are through academic courses or training and practical training, but, in most cases, it only provides a portion of what this course includes. The goals of developing the course were to promote an understanding of the importance of integrating human factors in the development process of systems already in the first stages of the design, and throughout the development process. The project aims to make available to systems engineers knowledge and methodologies in the field of human factors engineering, and to help them integrate them into the design process of the system. It is also intended to enhance relevant background in the field of system engineering accessible to human factors engineering experts. In addition, the general public and industry practitioners will be able to expand their knowledge in the field of human-systems integration and system design. The course is composed of six units. In the first unit, we introduce the learners to the concept of human-systems integration, the importance of this concept and how it contributes to the development of excellent products and systems: systems with high compatibility with the people who operate them. In the second and third units, we focus on the cognitive and ergonomic aspects of human factors engineering and on the task analysis process. In the fourth and fifth units, we dive deeper into the actions and processes that must be carried out in the life cycle of the system to ensure proper integration between human operators and technology systems. We explain how to apply the principles that were taught as part of a complex system development project process. In the sixth unit, we demonstrate the human-system integration principles and process in two case studies: virtual worlds and augmented reality training in industry.

ABSTRACT. There is a strong pull for user-manuals and training documentation to be converted and translated into a format that can instantly integrate into existing data structures, tables, and digital formats for streamlined analysis, engagement, computation, and throughput. The synthesis, utilization, and application of information is imperative to the modern digital world. For instance, in facing life decisions such as whether to pursue self-study, university classes, or online tutorials, it was revealed that the failure to identify, organize, and engage bodies of information can lead to numerous failures and misallocation of time. There exists a need to analyze and sort information in real-time due to the excess and constant bombardment of information. In short, information overload was rampant and extremely costly. This paper describes a Digital Training Documentation Classification Technique that aims to minimize interface and hand-off losses and to standardize training information into Bloom’s Taxonomy for classification of educational learning objectives [1]. In the effort to leverage modern technologies to navigate and engage a body of information, the authors streamlined a learning process that declares broad labels and classifiers. A classification model was developed to curate and deliver information customized for the end-users’ individual training needs. The model seamlessly translates documentation and other source instructions and reading materials into a format that can readily be manipulated and engaged by software and ultimately human factors in the form of training material. The authors applied metrics and dimensions to the body of information that make

ABSTRACT. The novel design and application of algorithms has been the focus of machine learning research to create the highest performing models. As applications of deep neural networks re-emerged in 2012, algorithmic methods have converged to a more constrained set for applied usage as performance gains from algorithm improvements have plateaued. The search for improvement gains has shifted toward methods to increase data quality and availability as the alternate path toward further model performance. This early-stage research sets forth a journey toward constructing a data-informed annotation systems requirements framework that accounts for human factors beginning with the analyzing the implications of annotation tool interface design on NLP use case label quality (i.e. label accuracy). The design and analysis of a set of controlled annotation experiments will be foundation of this work. This contribution towards a consolidated annotation requirements framework for applied AI practitioners is intended to support improvements in production model performance gains through the cost-efficient creation of higher quality scaled datasets for model training and tuning.

ABSTRACT. The integration of artificial intelligence (AI) and blockchain technologies has the potential to revolutionize various industries, including finance, healthcare, supply chain, and more. This paper explores the potential of integrating AI and blockchain for human system integration, focusing on AI-based automation for future design. We discuss the current state of AI and blockchain, their challenges and opportunities, and propose a framework for integrating these technologies to create a more efficient and effective human system. The convergence of AI and blockchain technologies is poised to transform multiple sectors, such as finance, healthcare, and supply chain management. This research delves into the possibilities of amalgamating AI and blockchain to enhance human system integration, with a particular emphasis on AI-driven automation for future-oriented design. The paper scrutinizes the existing state of AI and blockchain, delineates the challenges and prospects they present, and advances a structured approach for harmonizing these technologies to foster a more streamlined and robust human system.

AI and blockchain technologies have individually demonstrated significant potential to revolutionize various industries. AI, with its ability to analyze vast amounts of data and make intelligent decisions, has been applied in diverse fields, from healthcare diagnosis to financial trading. On the other hand, blockchain technology, with its decentralized and immutable ledger, has provided transparency and security to transactions and data, particularly in the financial and supply chain sectors. However, the integration of these technologies presents several challenges, including interoperability issues, regulatory concerns, and the need for skilled personnel. Despite these challenges, the potential benefits of integrating AI and blockchain are immense. For instance, AI can be used to analyze blockchain data and make intelligent decisions, while blockchain can provide transparency and security to AI algorithms. This can lead to more efficient and effective human systems that leverage the strengths of both technologies.

In conclusion, the integration of AI and blockchain has the potential to revolutionize various industries and create new opportunities for businesses and individuals. By addressing the challenges and leveraging the opportunities, businesses can create more efficient and effective human systems that leverage the power of AI and blockchain.

ABSTRACT. The INCOSE Human Systems Integration Working Group (HSI WG) recently released Volume 1 of a new series of Primer artefacts in September 2023. The purpose of the primer volumes are to provide contemporary guidance on the latest understanding of HSI from a cross-industry and transdisciplinary perspective. The first volume has been well received and interest in both HSI and the remaining Primer volumes is gaining momentum worldwide. This workshop will focus on Volume 2 (Fundamentals) and Volume 3 (Transdisciplinary HSI) and will bring together attendees with an interest in contributing as authors to the Primer.

Two primer writing workshops will be held during HSI 2024: Workshop 1- Overview, Review, Small Team Writing Allocation & First Writing Sprint. Workshop 2 – Writing Sprints, Review & Next Steps.

All are welcome to attend and learn more about the work of the HSI WG and feed into this important primer work. It is essential that the primers not only convey useful information but are also useful for individuals with different levels of HSI knowledge. The intention in these workshops is to create mixed sector, industry and level of knowledge in small teams in order to leverage the benefits of having multiple perspectives. To ensure efficiency, the workshops will be structured and facilitated. Vol 2 and 3 are approximately 70% complete, the outcomes of the workshop will be: - Identifying, prioritising and filling any gaps - General usability improvements