Monk Skin Tone Scale

The scale intends to replace the Fitzpatrick scale in fields such as computer vision research after an IEEE study found the Fitzpatrick scale to be "poorly predictive of skin tone." They noted that it tends to under-represent dark shades of skin relative to the global human population. The researchers then advised it "not be used as such in evaluations of computer vision applications."

The following table shows the 10 categories of the Monk Skin Tone Scale alongside the six categories of the Fitzpatrick scale, grouped into broad skin tone categories:

This table displays the colors of the ten MST skin tones:

Predecessor

Computer vision researchers initially adopted the Fitzpatrick scale as a metric to evaluate how well a given collection of photos of people sampled the global population. However, the Fitzpatrick scale was not intended for this purpose; it was instead developed to predict the risk of skin cancer in lighter-skinned people. Initially, the Fitzpatrick scale did not include darker skin tones at all.

Two additional categories for people with darker skin tones were later added to the original four to make it more inclusive. However, despite these improvements, the Fitzpatrick skin tones correlate more with self-reported race than with objective measurements of skin tone. Accordingly, computer vision models trained using the Fitzpatrick scale perform poorly on images of people with darker skin.