Privacy Implications Of AI-Based Surveillance Technologies: A Revised Panopticon

Anushree Raman, Reva University

ABSTRACT

This article examines the complex interplay between customary behaviour and developments in technology within today’s surveillance systems, centring on privacy concerns associated with AI-driven surveillance mechanisms. The research makes sense how big data analyses and AI algorithms have transformed the methodologies concentrating on the panopticon model developed by Michel Foucault which describes disciplinary power. Privacy concerns are on the rise due to advancements in technology and the decreasing costs for businesses to use smart monitoring systems. It's important for stakeholders to carefully consider the potential for misuse when it comes to Surveillance Analytics (SA) innovations. To help balance privacy implications and related issues stemming from the adoption of SA, a two-by-two Monitoring, Security, Privacy and Ethical Decision (SPED) Process Guide suggests reviewing key terms and ethical frameworks. The guide recommends using three ethical frameworks – Consequence, Duty, and Virtue – in one or more cases. In the SPED matrix, an organization's level of SA sophistication is shown on the vertical axis, while its current privacy level is evaluated on the horizontal axis. The matrix assesses the existing level of privacy and the rights granted for the surveillance targets, as well as the sophistication of the organization's SA. The suggested decision process guide can be used by senior managers and technicians to determine whether adopting SA is the right move.