Miscarriages of justice in digital surveillance times:

the facial recognition algorithms in question

Abstract

The traditional problems of personal recognition, especially when performed from photographic albums, have been repaginated and given a scientific-technological varnish with the introduction of facial recognition algorithms. The coronavirus pandemic has served as justification for the multiplication of these technologies, under the pretext of fighting the virus. As a result, in many places, such as England and the United States, these algorithms began to be used in criminal prosecution, often under the argument of reducing the subjectivity of testimonies. In this context, the objective of this paper is to investigate how facial recognition can produce new miscarriages of justice. The specific objectives are to discuss the use of facial recognition cameras for digital surveillance, analyze some aspects of the increase in security measures during the pandemic, investigate miscarriages of justice in recognizing people, and explain how miscarriages of justice can occur during the use of these cameras. The hypothesis is that this technology, firstly, cannot meet minimum conditions for evaluating evidential reliability, and, on the other hand, when applied to images, it is nothing more than an update, in many cases quite poorly done, of the problematic photographic recognitions. The hypothetical-deductive method and the bibliographical research technique were used.