These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Pearson correlation coefficient (PCC)
In statistics, the Pearson correlation coefficient (PCC) ― also known as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC), the bivariate correlation, or colloquially simply as the correlation coefficient ― is a measure of linear correlation between two sets of data. It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1.
Trustworthy AI Relevance
This metric addresses Transparency, Robustness by quantifying relevant system properties. PCC supports Transparency by providing a clear, quantifiable measure of relationships within data or model outputs, which can improve understanding and openness about how AI systems operate. It also relates to Robustness by enabling evaluation of model consistency and reliability through correlation analysis under different conditions or datasets, helping detect potential weaknesses or instabilities.
About the metric
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Partnership on AI
