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| Format: | Preprint |
| Published: |
2025
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| Online Access: | https://arxiv.org/abs/2510.16409 |
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| _version_ | 1866909854445076480 |
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| author | Sornette, Didier |
| author_facet | Sornette, Didier |
| contents | Uncertainty defines our age: it shapes climate, finance, technology, and society, yet remains profoundly misunderstood. We oscillate between the illusion of control and the paralysis of fatalism. This paper reframes uncertainty not as randomness but as ignorance: a product of poor models, institutional blindness, and cognitive bias. Drawing on insights from physics, complex systems, and decades of empirical research, I show that much of what appears unpredictable reveals structure near transitions, where feedbacks, critical thresholds, and early-warning signals emerge. Across domains from financial crises to industrial disasters, uncertainty is amplified less by nature than by human behavior and organizational failure. To master it, prediction must shift from prophecy to diagnosis, identifying precursors of instability rather than forecasting exact outcomes. I propose a framework of dynamic foresight grounded in adaptive leadership, transparent communication, and systemic learning. Mastering uncertainty thus means transforming fear into foresight and building institutions that navigate, rather than deny, the complexity of change. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_16409 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Mastering Uncertainty: From Understanding to Prediction Sornette, Didier Physics and Society Uncertainty defines our age: it shapes climate, finance, technology, and society, yet remains profoundly misunderstood. We oscillate between the illusion of control and the paralysis of fatalism. This paper reframes uncertainty not as randomness but as ignorance: a product of poor models, institutional blindness, and cognitive bias. Drawing on insights from physics, complex systems, and decades of empirical research, I show that much of what appears unpredictable reveals structure near transitions, where feedbacks, critical thresholds, and early-warning signals emerge. Across domains from financial crises to industrial disasters, uncertainty is amplified less by nature than by human behavior and organizational failure. To master it, prediction must shift from prophecy to diagnosis, identifying precursors of instability rather than forecasting exact outcomes. I propose a framework of dynamic foresight grounded in adaptive leadership, transparent communication, and systemic learning. Mastering uncertainty thus means transforming fear into foresight and building institutions that navigate, rather than deny, the complexity of change. |
| title | Mastering Uncertainty: From Understanding to Prediction |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2510.16409 |