Stop Blaming Facial Recognition for Workplace Surveillance Facial recognition has become the villain of choice in the workplace surveillance debate—the first technology critics name when they warn that America's factories and warehouses are turning into surveillance zones. That broader debate has reached Congress: Sens. Ed Markey (D-MA) and Brian Schatz (D-HI) reintroduced the Stop Spying Bosses Act and the No Robot Bosses Act in June 2026 to rein in employer surveillance of workers. States are pushing further: New York's Bossware and Oppressive Technology (BOT Act) would restrict electronic monitoring of employees, while a California bill that died in February would have banned workplace monitoring tools that use facial, gait, or emotion recognition—though its successor is already moving through the legislature. Rather than impose overly restrictive policies that limit facial recognition's utility in the workplace, policymakers should regulate what employers do with workplace data, not which device collects it. Part of the problem is vocabulary. As ITIF has explained, “facial recognition” is often used imprecisely as a catch-all term for a family of distinct technologies. Facial detection merely determines whether an image contains a face. Facial analysis estimates characteristics such as age or drowsiness without determining whose face it is. Facial recognition, by contrast, compares a face against stored templates, either to verify a claimed identity or to determine whether a person matches someone on a predefined list and, if so, retrieve information associated with that match. These uses involve different data and raise different privacy risks. They also rely on different technologies: cameras generally capture facial images, while some systems supplement them with infrared sensors. Other workplace devices collect different kinds of data altogether: a badge reader logs a credential, a handheld scanner logs task times, and a wearable logs motion. The same device can support very different data practices