4 ms·

> For example, the technology sometimes matched customers with people who had originally been enrolled in the database based on activity thousands of miles away

> For example, the technology sometimes matched customers with people who had originally been enrolled in the database based on activity thousands of miles away, or flagged the same person at dozens of different stores all across the United States, according to the complaint. So it's not that the data was wrong, just not properly scoped to stores in a given city/region? Or was it misidentifying people because they looked like someone in the database?

eesmith 3y ago
It's in a paragraph about false-positive matches, so FTC is saying the data was likely wrong. The complaint has more specific details: > a. In numerous instances, Rite Aid’s facial recognition technology generated match alerts that were likely false positives because they occurred in stores that were geographically distant from the store that created the relevant enrollment. For example, between December 2019 and July 2020, Rite Aid’s facial recognition technology generated over 5,000 match alerts in stores that were more than 100 miles from the store that created the relevant enrollment. ... > b. Some enrollments generated high numbers of match alerts in locations throughout the United States. For instance, during a five-day period, Rite Aid’s facial recognition technology generated over 900 match alerts for a single enrollment. The match alerts occurred in over 130 different Rite Aid stores (a majority of all locations using facial recognition technology), including hundreds of alerts each in New York and Los Angeles, over 100 alerts in Philadelphia, and additional alerts in Baltimore; Detroit; Sacramento; Delaware; Seattle; Manchester, New Hampshire; and Norfolk, Virginia. In multiple instances, Rite Aid employees took action, including asking consumers to leave stores, based on matches to this enrollment. > c. Between December 2019 and July 2020, Rite Aid’s facial recognition technology generated over 2,000 match alerts that occurred within a short time of one or more other match alerts to the same enrollment in geographically distant locations within a short period of time, such that it was impossible or implausible that the same individual could have caused the alerts in the different locations. For example, for a particular enrollment image that was originally captured at a Los Angeles store, Rite Aid’s facial recognition technology generated over 30 match alerts in New York City and Philadelphia between February 2020 and July 2020. Each of the New York and Philadelphia matches occurred within 24 hours of a match alert in a California store and thus was likely a false positive.

eesmith 3y ago

It's in a paragraph about false-positive matches, so FTC is saying the data was likely wrong. The complaint has more specific details: > a. In numerous instances, Rite Aid’s facial recognition technology generated match alerts that were likely false positives because they occurred in stores that were geographically distant from the store that created the relevant enrollment. For example, between December 2019 and July 2020, Rite Aid’s facial recognition technology generated over 5,000 match alerts in stores that were more than 100 miles from the store that created the relevant enrollment. ... > b. Some enrollments generated high numbers of match alerts in locations throughout the United States. For instance, during a five-day period, Rite Aid’s facial recognition technology generated over 900 match alerts for a single enrollment. The match alerts occurred in over 130 different Rite Aid stores (a majority of all locations using facial recognition technology), including hundreds of alerts each in New York and Los Angeles, over 100 alerts in Philadelphia, and additional alerts in Baltimore; Detroit; Sacramento; Delaware; Seattle; Manchester, New Hampshire; and Norfolk, Virginia. In multiple instances, Rite Aid employees took action, including asking consumers to leave stores, based on matches to this enrollment. > c. Between December 2019 and July 2020, Rite Aid’s facial recognition technology generated over 2,000 match alerts that occurred within a short time of one or more other match alerts to the same enrollment in geographically distant locations within a short period of time, such that it was impossible or implausible that the same individual could have caused the alerts in the different locations. For example, for a particular enrollment image that was originally captured at a Los Angeles store, Rite Aid’s facial recognition technology generated over 30 match alerts in New York City and Philadelphia between February 2020 and July 2020. Each of the New York and Philadelphia matches occurred within 24 hours of a match alert in a California store and thus was likely a false positive.