But crucially, Jassy and Smith seem to argue, it’s also inevitable. In calling for regulation, Microsoft and Amazon have pulled a neat trick: Instead of making the debate about whether facial recognition should be widely adopted, they’ve made it about how such adoption would work.

In a statement to The Atlantic, Amazon said it’s working with researchers, lawmakers, and its customers “to understand how to best balance the benefits of facial recognition with the potential risks,” noting that Rekognition has a variety of uses, including fighting human trafficking and finding missing persons. Microsoft reiterated statements from Smith in support of facial-recognition regulation, including implementing safeguards against reported misuse and securing consent from anyone who is the target of the technology.

Read: You no longer own your face

But some privacy experts believe the companies have ulterior motives. Evan Selinger, a philosophy professor at the Rochester Institute of Technology, accuses Microsoft and Amazon of trying to “suck out the motivation” for robust regulation. He argues that companies are pushing for regulation at the federal level because national laws are typically written to be floors, not ceilings—baseline measures that are less likely than local legislation to include restrictions for how private companies use the tech.

“Federal rules don’t prohibit local and strong regulations,” Selinger says. “But you get to raise the flag of mission accomplished [and] make it seem like people who want something stronger than what’s been enacted at a federal level are extremists.” Turning bipartisan agreement itself—not robust legislation—into the goal can, as Seligner puts it, “take the wind out of the sails for local [regulation] so people won’t feel as motivated, because they think there’s been change.”

Without regulation, the potential for misuse of facial-recognition technology is high, particularly for people of color. In 2016 the MIT researcher Joy Buolamwini published research showing that tech performs better on lighter-skinned men than on darker-skinned men, and performs worst on darker-skinned women. When the ACLU matched Congress members against a criminal database, Amazon’s Rekognition software misidentified black Congress members more often than white ones, despite there being far fewer black members.

This includes House Chairman Elijah Cummings, a Baltimore native whose face was also scanned when he attended a 2015 rally in memory of Freddie Gray, the unarmed black teenager who died of a spinal-cord injury while in police custody. The Baltimore Police Department used facial recognition to identify protesters and target any with outstanding warrants. Most of the protesters were black, meaning the software used on them might have been less accurate, increasing the likelihood of misidentification. Expert witnesses at the committee hearing in May warned of a chilling effect: Protesters, wary of being identified via facial recognition and matched against criminal databases, could choose to stay home rather than exercise their freedom of assembly.