‘ uncertainty ’

In risk science, uncertainty refers to the degree to which a value, outcome, or state of knowledge is unknown or imprecise. It is a core concept that affects how risks are identified, assessed, and communicated. Uncertainty can stem from a lack of information, inherent variability in systems, or limitations in scientific understanding.

There are several key types of uncertainty:

• Epistemic uncertainty arises from incomplete knowledge and is theoretically reducible through further study, data collection, or improved models.
• Aleatory uncertainty is due to inherent randomness or variability in natural systems and is not reducible, only characterizable through probabilistic means.
• Ambiguity relates to situations where there is disagreement or vagueness about the meaning or relevance of information.
• Value uncertainty occurs when stakeholders differ in how they weigh outcomes or prioritize trade-offs.

Uncertainty must be clearly distinguished from risk: while both involve unknowns, risk refers to uncertain outcomes that have potential consequences, whereas uncertainty refers more broadly to the limits of knowledge or predictability itself.

Example

In climate modeling, uncertainty can arise from model structure, initial conditions, future human behavior (e.g., emissions scenarios), and feedback mechanisms. These uncertainties are typically expressed through ranges or confidence intervals.

At Risk Sciences International (RSI), addressing uncertainty is central to risk assessment methodologies. RSI supports regulators, industry, and civil society by developing transparent, evidence-based approaches to characterizing and communicating uncertainty in decision-making contexts.