Hinsley Documentation
Crowdsourcing Scenario Likelihoods
After building scenarios, the next step is assessing how likely each one is. Rather than relying on a single analyst's judgment, Hinsley lets you crowdsource likelihood estimates from multiple people — team members, subject-matter experts, and external guests — and automatically aggregates them into a consensus view.
The Likelihood Scale
Every likelihood estimate in Hinsley uses a standardized seven-point scale aligned with common intelligence community probability language:
| Rating | Probability Range |
|---|---|
| Almost no chance | 1 – 5% |
| Very unlikely | 5 – 20% |
| Unlikely | 20 – 45% |
| Roughly even chance | 45 – 55% |
| Likely | 55 – 80% |
| Very likely | 80 – 95% |
| Almost certain | 95 – 99% |
This scale keeps assessments comparable across forecasters and ensures that when estimates are aggregated, the math maps cleanly to probability values.
Three Sources of Likelihood
Each scenario can display up to three likelihoods side by side, giving you a layered view of the assessment:
- Hinsley estimate — An AI-generated likelihood with a written justification. Hinsley draws on the analysis's source material, decomposition, and scenario details to produce this estimate. It also tracks trend direction over the past seven days.
- Your estimate — Your personal likelihood rating. You can set or update it inline from the scenario detail view at any time.
- Aggregate estimate — The combined consensus of all individual estimates. This appears automatically once two or more humans have submitted their assessments.
How Aggregation Works
When multiple humans submit their estimates, Hinsley computes an aggregate likelihood using the following approach:
- Each rating is converted to its midpoint probability. For example, Likely maps to 68% (the midpoint of 55–80%) and Very unlikely maps to 12% (the midpoint of 5–20%).
- The arithmetic mean of all individual midpoint probabilities is calculated.
- The mean is mapped back to the corresponding rating on the seven-point scale.
This process runs automatically each time a new estimate is submitted or an existing one is updated. The aggregate includes every current individual estimate — from logged-in users, guest forecasters, and the Hinsley AI alike.
Configuring Who Can Submit
Analysis owners control who can submit likelihood estimates through the submission settings. Three access levels are available:
- Collaborators only — Only users who have been added as collaborators on the analysis can submit estimates. This is the default.
- Account members — Any user in the same organization account can submit.
- Anyone with the link — Anyone who has the submission link can submit, including external guests without a Hinsley account. Use this option when soliciting input from outside experts.
Inviting External Forecasters
When accepting submissions from anyone with the link, you can send email invitations directly from the submission settings panel. Enter one or more email addresses and Hinsley will send each recipient a personalized link to the submission form. The link pre-fills their email address so they only need to enter their name and assessments.
Tracking Changes Over Time
Hinsley preserves a full history of every likelihood estimate. Each time a forecaster updates their rating, the previous value is retained in the history log. You can review this history from the scenario detail view to see how assessments have shifted as new information emerged.
The likelihood history also includes a chart that visualizes trends over time, plotting the aggregate likelihood, the Hinsley AI estimate, and individual forecaster estimates on a timeline. This makes it easy to spot divergence between forecasters or between human and AI assessments.