Fontes, C., & Perrone, C. (2021)
Ethics of surveillance: harnessing the use of live facial recognition technologies in public spaces for law enforcement
Technical University of Munich
https://ieai.mcts.tum.de/wp-content/uploads/2021/12/ResearchBrief_December_Fontes-1.pdf
Data dependency is one of AI’s intrinsic features. Personal data is paramount to feed the datasets used to train machine learning systems and build algorithmic models. Once the models are set, they can be applied to personal data and used to analyze or make inferences and predictions concerning particular individuals. This also applies to live facial recognition systems, implying risks for several individual rights, particularly privacy. In this Brief, we frame the implementation of these systems in the particular context of public space surveillance by public authorities for law enforcement purposes. Privacy, consent and proportionality are three intertwined aspects needed to describe the ethics of public space surveillance and to consider the responsible implementation of such AI-enabled systems.
