Visual Privacy: Current and Emerging Regulations Around Unconsented Video Analytics in Retail
Scott Pletcher

TL;DR
This paper examines the evolving legal and ethical landscape surrounding the use of advanced video analytics in retail, highlighting privacy concerns and regulatory uncertainties associated with inferring detailed personal characteristics without consent.
Contribution
It provides an analysis of current and emerging regulations affecting unconsented video analytics in retail environments, emphasizing the need for cautious adoption due to legal and ethical considerations.
Findings
Legal landscape is rapidly evolving with new regulations.
Retailers face significant privacy and data ownership challenges.
Uncertainty in legislation urges caution in adopting video analytics.
Abstract
Video analytics is the practice of combining digital video data with machine learning models to infer various characteristics from that video. This capability has been used for years to detect objects, movement, and the number of customers in physical retail stores, but more complex machine learning models combined with more powerful computing power has unlocked new levels of possibility. Researchers claim it is now possible to infer a whole host of characteristics about an individual using video analytics, such as specific age, ethnicity, health status and emotional state. Moreover, an individuals visual identity can be augmented with information from other data providers to build out a detailed profile, all with the individual unknowingly contributing their physical presence in front of a retail store camera. Some retailers have begun to experiment with this new technology as a way to…
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