Showing papers by "Tom McDermott published in 2021"

Artificial Intelligence and Future of Systems Engineering

Abstract: Systems Engineering (SE) is in the midst of a digital transformation driven by advanced modeling tools, data integration, and resulting “digital twins.” Like many other domains, the engineering disciplines will see transformational advances in the use of artificial intelligence (AI) and machine learning (ML) to automate many routine engineering tasks. At the same time, applying AI, ML, and autonomation to complex and critical systems needs holistic, system-oriented approaches. This will encourage new systems engineering methods, processes, and tools. It is imperative that the SE community deeply understand emerging AI and ML technologies and applications, incorporate them into methods and tools, and ensure that appropriate SE approaches are used to make AI systems ethical, reliable, safe, and secure. This chapter presents a road mapping activity undertaken by the Systems Engineering Research Center (SERC). The goal is to broadly identify opportunities and risks that might appear as this evolution proceeds as well as potentially provide information that guides further research in both SE and AI/ML.

Introduction to “Systems Engineering and Artificial Intelligence” and the Chapters

Abstract: In this introductory chapter, we first review the science behind the two Association for the Advancement of Artificial Intelligence (AAAI) Symposia that we held in 2020 (“AI welcomes Systems Engineering. Towards the science of interdependence for autonomous human-machine teams”). Second, we provide a brief introduction to each of the chapters in this book.

Learning Design for Sustainable Development

Abstract: Purpose : The purpose of this paper is to theorise an approach to learning design for formal education and training contexts, which can empower the student-led acquisition of competences for sustainable development with particular reference to engineering education. Design : the paper presents a conceptual framework which synthesises two extant bodies of empirical research (i) into the development of systems engineering proficiencies and (ii) the development of learning power and authentic enquiry. Findings: Bringing these two research-based bodies of knowledge together enables the conceptualisation of a practical learning design which integrates the development of self-leadership, learning relationships and complex problem solving for sustainable futures. These two approaches, and their synthesis, have been implemented in practice but not reported on or theorised before. Originality: This transdisciplinary theoretical study was undertaken by the original researchers to integrate and transcend the limitations of disciplinary and siloed approaches to learning design for 21C meta-competencies and to explore a common architecture capable of deployment over time and adaptable to different contexts. Research limitations/implications: Whilst the two strands of research underpinning this synthesis are well researched, the integrated model has yet to be empirically verified through appropriate scientific methodologies. Practical implications: this study provides a foundation for the development of a core curricular spine to be developed as an accreditation framework in formal education and work-based settings. The development of a rigorous measurement model has significant implications for policy and practice.