Risk science
Risk science asks how hazards, exposure and vulnerability combine to produce harm, how harm travels through networks of dependence, what causes what, and how certain we can be. The Global Centre for Risk and Innovation (GCRI) builds its work on these foundations: hazards, exposure, vulnerability, networks, causality and uncertainty. Getting them right is what separates evidence that helps a decision from numbers that only look precise. This page is part of science and methods.
- 01In briefThe short answer
- 02Building blocksRisk is more than the hazard
- 03Beyond single risksNetworks, causality and uncertainty
- 04Kinds of uncertaintyNot all uncertainty is the same
- 05Key termsTerms used on this page
- 06RelatedFrom foundations to application
GCRI · Institution · service level R0
The short answer.
Risk science is the study of how hazards, exposure and vulnerability combine to produce harm, how harm travels through networks of dependence, what causes what and how certain the evidence is. GCRI builds its work on these foundations because getting them right is what separates evidence that helps a decision from numbers that only look precise.
Systemic exposure in North America.
Where people and networks concentrate, the exposure through which shocks travel between systems, shown for North America as an example geography for this subject.
Risk is more than the hazard.
The same storm can cause minor disruption in one place and a disaster in another. The difference lies in the other building blocks.
| Concept | Question it answers | Example |
|---|---|---|
| Hazard | What could happen, how often and how severely? | A river flood of a given depth |
| Exposure | Who and what is in harm's way? | Homes, clinics and substations on the floodplain |
| Vulnerability | How badly would they be affected? | Building type, health status, income, backup power |
| Capacity | How well can they cope and recover? | Warnings, insurance, social networks, repair crews |
Networks, causality and uncertainty.
Dependence carries harm
Failures spread through supply, service and financial links, studied with network science and contagion.
What causes what
Separating cause from correlation with causal inference, and saying when we cannot.
How sure we are
Quantified with probability and statistics and reported with every result.
Not all uncertainty is the same.
- 01
Natural variability
Randomness in the system itself, which more data cannot remove.
- 02
Knowledge gaps
Limits in data and understanding, which better research can reduce.
- 03
Deep uncertainty
Situations where even the probabilities are unknown, explored with scenarios rather than single estimates.
Terms used on this page.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Risk | The effect of uncertainty on objectives, in ISO 31000 usage, often described through events, their consequences and likelihoods. |
| Hazard | A process, phenomenon or human activity that may cause loss of life, injury or other health impacts, property damage, social and economic disruption or environmental degradation, in UNDRR terminology. |
| Vulnerability | The conditions that increase the susceptibility of people, assets or systems to the impacts of hazards. |
| Aleatory uncertainty | Uncertainty that comes from natural variability, which further study cannot reduce. |
| Epistemic uncertainty | Uncertainty from incomplete knowledge, which better data or models can reduce. |
Questions and answers.
Why does GCRI separate hazard from risk?
Is a risk score a fact?
How does GCRI deal with risks that have never happened?
Can risk science tell us what to do?
Where can I learn the methods?
Around GCRI.
Start with an enquiry.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.