AIA Data Quality Checklist
Check whether your data is defensible before you start the Algorithmic Impact Assessment.
Built for Canadian public sector teams preparing data, documentation, and controls for an automated decision system.
6
Sections
60
Checklist items
~30 min
Time to complete
Get the checklist
~30 minWhy teams use it
Most projects do not fail because the questionnaire is hard. They fail because the data behind the system is incomplete, poorly documented, weakly governed, or harder to explain than expected.
This checklist helps you find those issues before they slow the AIA.
What you get
- A practical checklist you can use before starting the AIA
- Data quality checks covering source, completeness, relevance, consistency, timeliness, and bias risk
- A simple scoring page to flag red, yellow, and green areas
- A practical way to spot issues before they delay legal, privacy, or review work
Who this is for
- Program teams preparing an automated decision system
- Data and analytics teams supporting AIA work
- Policy, legal, privacy, and governance teams reviewing readiness
- Digital and transformation teams trying to reduce rework
What it covers
- Decision context and data purpose
- Source systems and ownership
- Quality checks across critical data dimensions
- Fairness and representativeness risks
- Documentation and lineage
- Controls and monitoring
Frequently asked questions
Is this the full AIA?
No. This is a practical pre-AIA checklist focused on data readiness. The AIA itself is a separate process.
Who should use this checklist?
It is best used by cross-functional teams involved in data, policy, privacy, legal, governance, and delivery.
How long does it take?
Most teams can complete it in about 30 minutes.