On strategies for risk management and decision making under uncertainty shared across multiple fields

Paper: arXiv 2309.03133

Authors: Alexander Gutfraind

Abstract

Decision theory recognizes two principal approaches to solving problems under uncertainty: probabilistic models and cognitive heuristics. However, engineers, public planners and decision-makers in other fields seem to employ solution strategies that do not fall into either field, i.e., strategies such as robust design and contingency planning. In addition, identical strategies appear in several fields and disciplines, pointing to an important shared toolkit. The focus of this paper is to develop a systematic understanding of such strategies and develop a framework to better employ them in decision making and risk management. The paper finds more than 110 examples of such strategies and this approach to risk is termed RDOT: Risk-reducing Design and Operations Toolkit. RDOT strategies fall into six broad categories: structural, reactive, formal, adversarial, multi-stage and positive. RDOT strategies provide an efficient response even to radical uncertainty or unknown unknowns that are challenging to address with probabilistic methods. RDOT could be incorporated into decision theory using workflows, multi-objective optimization and multi-attribute utility theory. Overall, RDOT represents an overlooked class of versatile responses to uncertainty. Because RDOT strategies do not require precise estimation or forecasting, they are particularly helpful in decision problems affected by uncertainty and for resource-constrained decision making.

Complexity vs Empirical Score

• Math Complexity: 2.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: The paper introduces a compelling taxonomy (RDOT) for non-probabilistic decision-making and risk management across disciplines under radical uncertainty. While conceptual clarity and novelty are strong, the work lacks rigorous mathematical derivations and quantitative backtesting or empirical validation.

Research Flowchart

  flowchart TD
    A[Identify Gap: Non-probabilistic & Non-cognitive Risk Strategies] --> B[Collect & Analyze >110 Strategy Examples Across Fields]
    B --> C[Develop RDOT Framework]
    C --> D[Categorize RDOT into 6 Broad Categories]
    C --> E[Integrate RDOT with Decision Theory Workflows & MAUT/MOO]
    D & E --> F[Outcome: Versatile Response to Radical Uncertainty & Resource Constraints]