All people are created equal, but in the eyes of the algorithm, not all faces are just yet.

A new study from MIT and Microsoft researchers (pdf) is providing more evidence of exactly how bad facial-recognition software is at accurately identifying darker faces, especially when those faces belong to women. In a test to identify the sex of people from their faces, software was able to do so with more than 99% accuracy for light-skinned men. For darker-skinned women, the software could be wrong as frequently as one-third of the time.

The results shed more light on a known problem—how limited data sets can impact the effectiveness of artificial intelligence, which might in turn heighten bias against individuals as AI becomes more widespread.

In the paper, Joy Buolamwini of the MIT Media Lab and Timnit Gebru of Microsoft Research, discussed the results of a software evaluation carried out in April and May of last year.