Open AccessWHICH HUMAN FACES CAN AN AI GENERATE? LACK OF DIVERSITY IN THIS PERSON DOES NOT EXIST
Author(s) -
Lucas Nunes Sequeira,
Bruno Moreschi,
Vinicius Ariel Arruda dos Santos
Publication year - 2021
Publication title -
selected papers of internet research
Language(s) - English
Resource type - Journals
ISSN - 2162-3317
DOI - 10.5210/spir.v2021i0.12240
Subject(s) - computer science , generative grammar , face (sociological concept) , python (programming language) , artificial intelligence , diversity (politics) , programming language , sociology , social science , anthropology
In this abstract we show the results of an interdisciplinary researchin which we audit fake human faces generated by the website This Person Does Not Exist(TPDNE), and discuss how this system can help perpetuate normativities supported by adependency on a limited database. Our analysis is centered on the “default generic face”that we created by overlapping random samples of fake human faces generated by TPDNE'salgorithms – a version of Generative Adversarial Network, the StyleGAN2. To carry theseexperiments, we built a database with 4100 fake human faces taken from TPDNE via webscraping; we analysed them through a Python language script; and discussed behavioursidentified in results. Our analyses are based on the use of images, called “cluster-images”,created from this overlapping of N arbitrary fake human faces by the TPDNE's algorithm. Ourexperiments showed that, independently of the group of fake human faces sampled, the samegeneric white face always appeared as a result. These results intrigue particularly becausethe lack of diversity of TPDNE's generated faces is not a mere problem to be fixed in thissystem in this digital infrastructure, but a dynamic of reinforcing standards thathistorically regulate bodies, territories and practices.