Privacy

US lawmakers want taxi apps to check driver fingerprints

Ride-sharing taxi apps Uber, Lyft and Sidecar have been asked by US lawmakers to adopt fingerprint-based background checks for their drivers,

Ride-sharing taxi apps Uber, Lyft and Sidecar have been asked by US lawmakers to adopt fingerprint-based background checks for their drivers,

Ride-sharing taxi apps Uber, Lyft and Sidecar have been asked by US lawmakers to adopt fingerprint-based background checks for their drivers, reports PC World.

Eight members of Congress have joined on the issue, hoping to improve passenger safety following reports of assault and sexual violence in recent months. The news follows similar security measures in India, where Uber was temporarily banned from operating in Delhi after the alleged rape of a female passenger by one of its drivers.

According to Planet Biometrics, state-regulated cab firms are already required to use fingerprint-based background checks, while Uber, Lyft and Sidecar currently outsource the screening process to private companies. As these companies become increasingly popular in the US, the Congress members argue it’s time for more “rigorous and comprehensive methods” to be used as standard.

“While we understand your companies conduct private background checks when vetting potential drivers, you should take additional steps to increase the safety of your customers,” they wrote, in identical letters addressed to the CEO of each company.

“Specifically, we urge you to adopt comprehensive fingerprint-based background checks for new and existing drivers. […] Following multiple instances of sexual assault by drivers hired to work in your industry, it is clear that there is an urgent need to improve screening standards currently in place.

While the move from Congress will likely force its hand, Uber at least has already said it will be considering biometrics as part of its “enhanced driver screening” process, as reported by We Live Security.

Meanwhile, the company recently admitted to a security breach that could result in 50,000 stolen driver names and licence numbers due to a flaw in its database.

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