Advanced Concepts for Evaluating, Aggregating, and Managing High-Tech Performance Risks and Promoting Resilience

Allan S. Benjamin
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Allan S. Benjamin: Allan Benjamin Company

Chapter Chapter 15 in Integration of Project, Infrastructure, and Enterprise Risk Management, 2025, pp 163-177 from Springer

Abstract: Abstract The practice of integrated risk management is in the process of being revolutionized by recent advances in information technology. This chapter addresses four such advances: (1) the prediction of tipping points and their effects on organizational and societal risk, (2) the use of AI red teaming to evaluate and protect against cyberattacks, (3) the use of specialized AI techniques to derive more accurate predictions of total aggregate risks, and (4) the use of AI to optimize organizational and operational resiliency. Methods such as agent-based modeling (ABM), empirically-derived leading indicators of tipping points, AI red teaming, hybrid AI-human red teaming, artificial neural networks, genetic algorithms, and L2 regularization are outlined at a preliminary level, but with sufficient detail to suggest how analyses may be performed consistent with the present state of development of these techniques and how ongoing research will enable improved realization using these techniques in the future.

Keywords: Tipping points; Leading indicators of tipping points; Agent-based modeling; Societal risk; Organizational risk; Artificial intelligence; AI red teaming; AI-human interfaces in red teaming; Penetration time; Recovery time; Artificial neural networks; Energy landscape; Genetic algorithms; Machine learning; L2 regularization; Organizational resilienc; Operational resilience (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:rischp:978-3-031-85070-7_15

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DOI: 10.1007/978-3-031-85070-7_15

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