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Facial recognition technology involves using algorithms to identify people based on their faces. Distinctive details about people’s faces are compiled into “face templates,” which are then stored in a database and used to find facial matches,

Facial recognition is quickly being deployed by many companies for various purposes, such as authenticating identity (unlocking smart phones) and identifying people in photos.  Other uses include using the data to track people’s location and behavior.  Facial recognition technology also can detect people’s emotions – an ability that could be used to manipulate people.

Law enforcement is starting to turn to facial recognition to enhance its surveillance of people. Surveillance cameras are starting to pop up everywhere.  With widespread gathering of data that can be linked to people via facial recognition, the government will be able to have an unprecedented ability to track where people go, what they do, and how they are feeling.  In a report, Georgetown Law Center scholars note that law enforcement is already widely using facial recognition technology, and the facial data of half of U.S. adults is included in a law enforcement facial recognition system.  The scholars call this state of affairs a “perpetual lineup.”  Law enforcement use of facial recognition technology is mostly unregulated. There are hardly any limitations, barely any oversight, and little to no accountability. This is a bad recipe.

Facial recognition technology is more inaccurate for racial and ethnic minorities and women. The harms of errors in facial recognition are thus placing an unfair burden on some people.

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This post was authored by Professor Daniel J. Solove, who through TeachPrivacy develops computer-based privacy and data security training. He also posts at his blog at LinkedIn, which has more than 1 million followers.

Professor Solove is the organizer, along with Paul Schwartz, of the Privacy + Security Forum, annual events designed for seasoned professionals. 

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