“Ethically contentious aspects of artificial intelligence surveillance: a social science perspective”

Abstract

Artificial intelligence and its societal and ethical implications are complicated and conflictingly interpreted. Surveillance is one of the most ethically challenging concepts in AI. Within the domain of artificial intelligence, this study conducts a topic modeling analysis of scientific research on the concept of surveillance. Seven significant scholarly topics that receive significant attention from the scientific community were discovered throughout our research. These topics demonstrate how ambiguous the lines between dichotomous forms of surveillance are: public health surveillance versus state surveillance; transportation surveillance versus national security surveillance; peace surveillance versus military surveillance; disease surveillance versus surveillance capitalism; urban surveillance versus citizen ubiquitous surveillance; computational surveillance versus fakeness surveillance; and data surveillance versus invasive surveillance. This study adds to the body of knowledge on AI ethics by focusing on controversial aspects of AI surveillance. In practice, it will serve as a guideline for policymakers and technology companies to focus more on the intended and unintended consequences of various forms of AI surveillance in society.