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Could our AI system accurately capture the factors it's designed to measure?
Could our AI system accurately capture the factors it's designed to measure?
Construct validity bias occurs when a feature or target variable fails to adequately represent the concept it is intended to measure, leading to inaccurate measurements and potential biases. For example, measuring socioeconomic status using income alone overlooks important factors such as wealth and education. This bias can arise during various stages of the AI lifecycle and should be addressed early on to improve system accuracy.
If you answered No then you are at risk
If you are not sure, then you might be at risk too
Recommendations
- Collect multiple measures for complex constructs to ensure a more complete and accurate representation.
- Document and report the considerations and rationale behind the choice of target variables and features.
- Acknowledge and account for the variability in how features may be interpreted differently by diverse individuals.
- Regularly review the measures used to capture constructs to ensure they remain relevant and valid throughout the AI system’s lifecycle.