HIGH COURT OF JUSTICE APPROVES LAW ENFORCEMENT USE OF FACIAL RECOGNITION TECHNOLOGY

The UK High Court of Justice, sitting at Cardiff, has entered a judgment holding that police use of automatic facial recognition technology to conduct a search, in public, among crowds, is lawful. The Court noted that although the use of facial recognition software interferes with the privacy rights of individuals scanned by CCTV cameras, there IS a lawful basis for it, and the legal framework employed by the police in Wales was proportionate.

Containing all relevant legal citations, the well-documented 67-page decision of the High Court, Queen's Bench Division, discussed Legislation, AFR Technology, the police use of AFR, Human Rights issues, and Data Protection claims. Anyone involved in law enforcement use of facial recognition software platforms is urged to read the entire decision, as it is an excellent resource of information.

The Court, speaking through Lord Justice Haddon-Cave, held, in its Conclusion that "we are satisfied both that the current legal regime is adequate to ensure appropriate and non-arbitrary use of AFR* Locate, and that [South Wales Police's] use to date of AFR Locate** has been consistent with the requirements of the Human Rights Act and the data protection legislation. " [Judgment at Paragraph 159].

Readers who wish to review the complete text of the Judgment can access it here. The style of the case is: The Queen (on application of Edward Bridges) -and- The Chief Constable of South Wales Police et al,  Case No.: CO/4085/2018.EWHC (QB0.

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* Automated Facial Recognition Technology.
** "AFR Locate involves the deployment of surveillance cameras to capture digital images of members of the public, which are then processed and compared with digital images of persons on watch lists compiled by [South Wales Police] for the purposes of the deployment." Judgment at Paragraph 7].

Research Note: How AFR works-
(1) Uses an existing database of complied images.
(2) Conducts facial image acquisition, using CCTV.
(3) Employs Face Detection; detects and isolates facial images.
(4) Extracts unique facial features.
(5) Conducts Face Comparison.
(6) Matching: creates a Similarity Score on matches.