Reflection: Making Sense of What You Saw
An assurance case works by decomposing a broad claim (like “our AI is fair and non-discriminatory”) into specific, manageable claims, and then providing evidence for each one. This structured approach helps build trust by making the reasoning clear and transparent.
In this page you will step back and reflect on the key elements you encountered in the Fair Recruitment AI assurance case. You’ll synthesise your learning and familiarise yourself with the vocabulary used to describe assurance cases.
The Core Elements
The following cards offer a refresher of the core elements you just encountered in the Fair Recruitment AI case. Click through each card to remind yourself of their definitions and see examples from the case.
Goal
A goal represents the top-level claim that the assurance case is trying to establish. It states what needs to be assured.
Key Points
Always appears at the top of the hierarchy
Must be clear and concise
Sets the direction for the entire argument
Example
"The AI recruitment system makes fair and non-discriminatory hiring recommendations."
Reflection & Synthesis
Now that you’ve reviewed the core elements, take a few minutes to reflect on what you’ve learned.
Reflection & Synthesis
Take a moment to reflect on what you've discovered
Following the Logic
How does the case build its argument from the main goal down to specific evidence? Can you describe the logical flow?