Lawless W.F., Mittu R. Systems Engineering and Artificial Intelligence

New York: Springer, 2021. — 566 p.This book provides a broad overview of the benefits of a Systems Engineering design philosophy in architecting complex systems composed of Artificial Intelligence (AI), Machine Learning (ML), and humans situated in chaotic environments. The major topics include emergence, verification, and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams — where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned but also raise questions that must be answered to further advance the general Science of Autonomy.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. 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.