What “Accuracy” Really Means

Module 4 · Risk Tool Lessons

Accuracy is meaningful separation.

When people talk about a “more accurate” risk assessment tool, what do they mean? It is not just about getting individual cases right. A stronger tool separates lower- and higher-risk individuals more clearly.

Key takeaway

Accuracy is about how well a tool separates outcomes—not just how often it is “right.”

Two Tools Can Behave Differently

Both tools in the figure below assign risk scores. But they behave very differently.

One creates greater separation between lower- and higher-risk individuals
The other compresses people into a narrower range of probabilities

The idea: The difference is separation.

Illustration

Accuracy means separation

Two tools can assign risk scores, but differ in how much they separate lower- and higher-risk individuals.

Comparison of two risk assessment tools showing different levels of separation across predicted probabilities

A stronger tool creates clearer separation across risk levels. A weaker tool compresses people into a narrower range of predicted probabilities.

How to Read the Figure

The same score can correspond to very different predicted probabilities depending on the tool.

At a score of 20, one tool corresponds to about 20% risk, while the other corresponds to about 40%
At a score of 80, one tool corresponds to about 75% risk, while the other corresponds to about 45%

A stronger tool spreads people out meaningfully across risk levels. A weaker tool groups people closer together, even when outcomes differ.

Why This Matters

Better separation supports more informed decisions
Poor separation limits how useful a tool can be
Two tools can look similar on the surface but behave very differently

Bottom Line

Think of accuracy as meaningful separation. A useful risk tool does not just assign scores—it meaningfully distinguishes between different levels of risk.

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