Facial Recognition and the U.S. Fourth Amendment: Defining Reasonable Expectations of Privacy in Algorithmic Policing

Facial recognition technology (FRET) has completely transformed the manner of surveillance by introducing continuous and automatic identification of individuals in both digital and physical environments. This technological growth poses a challenge to the sufficiency of the Fourth Amendment, as its definition of reasonable expectation of privacy was designed in an analogue world of physical searches and physical evidence. This study proposes a technological proportionality and accountability framework (TPAF) that aims at balancing constitutional privacy rights with contemporary algorithm-based surveillance. Based on the principles of scale, persistence, and inference, TPAF provides a comprehensive mechanism that enables the courts and lawmakers to determine the proportionality, intent, and responsibility of digital surveillance operations. Recommending statutory and administrative changes in addition to transparency, fairness, and independent control, this article proposes that the Fourth Amendment should be interpreted dynamically in a way that conserves democratic values along with technological advancement in modern policing.