#eye #eye
The analysis of large quantities of facial data via machine learning enables ‘non-existent faces’ to be generated. At the same time, the same technology is deployed and utilized by authorities and tech corporates to identify and track people through profiling the facial info, such as facial expressions, gender, age and ethnicity.

The machine learning-generated face is said to be “non-existent.” However, if run it through an face analyser based on machine learning, one can obtain information on the facial expression, gender, age range, and other characteristics of this “non-existent” face perceived by the machine.

By using the machine learning face analyser, this process in fact validates the existence of the “non-existent” face generated by machine learning. And it raises the questions:

This Person Does Not Exist?  If it does, then how?
Who determines our existence & defines our identities?

Work-In-Progress, 2021