Biometric scanners, such as face recognition technology, have seen widespread adoption in applications, such as identifying suspected criminals, analyzing candidate’s facial expressions during job interviews, and monitoring attendance at schools.
As these technologies have become more pervasive, many organizations have raised potential concerns about the way these technologies schematize faces. Studies have shown commercial face recognition software has noticeably lower accuracy on darker-skinned individuals, and automatic gender recognition systems regularly misgender trans and non-binary individuals.
In addition, many scholars have written about the rise of techno-surveillance and looming threat of constant government tracking of citizens. In this talk, I will discuss these issues, and what we as technologists do to prevent building software that enables harm upon vulnerable populations.