  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 better know their
customers. However, those same early adopters are caught in an evolving legal
landscape around privacy and data ownership. This research looks into the
current legal landscape and legislation currently in progress around the use of
video analytics, specifically in the retail store setting. Because the ethical
and legal norms around individualized video analytics are still heavily in
flux, retailers are urged to adopt a wait and see approach or potentially incur
costly legal expenses and risk damage to their brand.
