Data · · 5 min read
Why Data Quality Matters for AI
Models inherit the strengths and flaws of the data they learn from. Quality is not a preliminary step — it is ongoing work.
Every AI system reflects its training data. Gaps, errors and biases in that data become gaps, errors and biases in behaviour.
Dimensions of quality
- Accuracy: does the data reflect reality?
- Coverage: does it include the cases that matter?
- Consistency: are definitions stable across sources?
- Freshness: does it reflect current conditions?
Investing in data quality usually yields more improvement than switching to a more complex model.
Machine.sa editorial