Facial Recognition Technology (FRT) is a biometric identification technology utilizing automation and machine learning, and its main intent is to identify, localize, and trace human faces through the captured images or live video feed. The technology consists of three functions: facial detection, verification, and identification, which can either be used separately or in conjunction with each other to authenticate, alter facial features, and track individuals in real time. The usage of Facial Recognition Technology has been constantly increasing over the past decade, but the research on its effects on individuals, especially the threats, is still scarce. The purpose of this thesis is to explore and identify said threats and build a solid foundation for possible further research. The thesis was conducted as qualitative research with semi-structured interviews as a main method of collecting data. Based on the analysis and prior literature, the threats could be divided into two categories: public and private use of FRT. In short, public use comprises the utilization of FRT in public spaces and public entities, while private use encompasses the usage of FRT either by a private organization in a public space, or completely in private, for example, through an individual’s phone. Additionally, our results show how individuals either fail to recognize the numerous threats of FRT altogether or perceive them as impossible be protected against. However, trust in local authorities and organizations diminishes the perception of threats. In order to indemnify an individual’s privacy, information security, and basic human rights, it is crucial to discuss the underlying threats of Facial Recognition Technology, both in scientific literature and generally.