Unpredictability & Adaptive Risk Management for our Deeply Uncertain World

Risk is often seen as something we can model and measure, but what happens when uncertainty can’t be quantified? Deep uncertainty arises in nonlinear systems, driven by complexity, unknowability, and interdependent dynamic variables. In such environments, shocks can accelerate through feedback loops, amplify across domains, and cascade systemically. As extreme and unprecedented events become more frequent, the limitations of traditional risk models are increasingly exposed. In this session, Roger Spitz will examine the nature of deep uncertainty and systemic risk, and explore adaptive and anticipatory frameworks for rethinking how we model, manage, and respond to systemic disruption in an unpredictable world: 

• What does risk decision-making look like in deeply uncertain complex environments, especially as AI takes on roles once thought too critical for machines?
• How do we respond when risks and events have multiple concurrent stressors that can cascade, spilling over as the systemic impacts of intersecting disruptions multiply and amplify?
• As impacts like climate change or geoeconomic shifts are not siloed, what adaptive, future-aligned strategies do we need for assessing risks and building resilience? 

In a recent paper, “The future of risk and insurability in the era of systemic disruption, unpredictability and artificial intelligence,” published in the Journal of Operational Risk (Risk.Net), which Roger Spitz co-authored with Olivier Desbiey, Head of Foresight at AXA, they analyze the fragile nature of traditional risk management techniques in the face of frequent, high-impact shocks. The authors advocate for a new approach that treats disruption as systemic rather than episodic. Read the paper here.