How much agency do you want over your facial data? How much agency do you likely have over that facial data?
In October, 20176, the Georgetown Law Center on Privacy and Technology released a report titled The Perpetual Line-Up in which the authors assert that “the [American] Government Accountability Office revealed that close to 64 million Americans do not have a say in the matter: 16 states let the FBI use face recognition technology to compare the faces of suspected criminals to their driver’s license and ID photos”; more succinctly, ” One in two American adults is in a law enforcement face recognition network.” This sharing of facial data is not restricted to law enforcement contexts: numerous social media platforms and app, like FaceApp, gather, keep and share facial data; government agencies interconnect their facial databases in order to provide border security, as exemplified by the Biometric Air Exit‘s use of passport and visa photos in combination with Customs and Border Patrol, the Transportation Security Administration, the Department of Homeland Security and industry partners like airlines. Outside of these American contexts, there have been countless international applications of facial recognition software, that include the capturing of facial data from crowds of protesters, concerts, and public spaces in general.
The Facial Agency project aims to educate about what your face’s place is in the development of new technologies, as well as expose the divergence between the control you may desire or expect to have over your facial data, and the control you probably do have based on your social capital and experiences.
The comparison takes place between to scores. The first is the Desired Agency (DA) score, provided by the user, reflecting the desired level of control over their facial data. The second is the Actual Agency (AA) score, calculated on the basis of 30+ variables, including the user’s biometric data and past usage sharing of it, weighted by factors such as citizenship, race, and social media usage. The variables are then weighted and combined through a mathematical formula into a final score. It is calculated automatically, and reflects the user’s actual likely level of control over their facial data.
The Facial Agency project has been developed by Aaron Tucker and Sol Pandiani.