Uncovering the Bias in Facial Expressions

Understand

Over the past decades the machine and deep learning community has celebrated great achievements in challenging tasks such as image classification.

• The deep architecture of artificial neural networks together with the plenitude of available data makes it possible to describe highly complex relations.
• Yet, it is still impossible to fully capture what the deep learning model has learned and to verify that it operates fairly and without creating bias, especially in critical tasks, for instance those arising in the medical field.
• One example for such a task is the detection of distinct facial expressions, called Action Units, in facial images.