Ground Truth (n.)

1. The reality of a situation as experienced firsthand by a human rather than by report

2. In statistics and machine learning, ground truth is ‘real world’ data used to verify the performance of algorithms trained using machine learning for accuracy. Ground truth can also be used as a verb to mean verify and calibrate.

Across Eastern and Western cultures, societies have developed ways to predict a person's character through facial features. In East Asian cultures, the esoteric practice of face-reading promises the power to see into one's future through facial analysis. Though face reading remains largely a folk belief, many continue to seek the occult power of predictions from face readers. In the West, the forgotten pseudo-science of physiognomy, combined with statistics and machine learning, re-enters our modern lives as facial recognition algorithms, perpetuating societal biases and individual prejudices.

In this project, I subject my face to various predictive processes, namely Western physiognomy, Eastern face reading, facial recognition, facial phenotyping, facial generation, and synthetic facial data. I blend the visual language of the occult in face reading with the "scientific" aesthetic of facial recognition to blur the lines between these practices from the East and West. This visual study reveals the similarities between the two predictive regimes centered around the face: one remains folklore, while the other is extensively applied to almost every aspect of our daily lives. The project challenges the automation bias of facial recognition (or what I term "Western face reading") and unveils the deeper, often unexamined meta-narratives underlying these practices.

Ultimately, a face is more than just a face. It is an interface of predictions trapped between two analytical frameworks and cosmological views that are not as different as they initially seem.

Digital Experience by FOAM

The artist would like to thank the Finnish Cultural Foundation for their kind support.