How Facial Recognition Is Helping Fight Child Sexual Abuse

Organization

Griffeye

Description

The article explores how facial recognition systems using machine learning can flag material depicting victims or criminals known by law enforcement. The system can also filter and group images that belong to the same case, which makes police officers’ work of going through child sexual abuse material (CSAM) more efficient as they do not need to jump in blindly without knowledge of what could be found or if there are any linking factors. Facial recognition systems have improved significantly in the past few years, especially when applied in uncontrolled circumstances, for example when a person’s face is seen from the side or in motion. Moreover, the systems have also become better at identifying and matching faces of children at different ages, which was almost impossible for the technology a few years ago. Today, systems designed specifically for CSAM exist and their impact has been transformative for the police forces embracing them.

File
Tags
Child Sexual Abuse Material (CSAM)Criminal investigationMachine learningArtificial intelligence
Type
Other publication
Year
2020