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| DATE | 2020-08-14 |
| FROM | Ruben Safir
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| SUBJECT | Subject: [Hangout - NYLXS] Race identification Software
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https://www.wsj.com/articles/the-quiet-growth-of-race-detection-software-sparks-concerns-over-bias-11597378154?mod=hp_listc_pos1
The Quiet Growth of Race-Detection Software Sparks Concerns Over Bias
Parmy Olson
13-16 minutes
When Revlon Inc. wanted to know what lipstick women of different races
and in different countries were wearing, the cosmetics giant didn’t need
to send out a survey. It hired Miami-based Kairos Inc., which used a
facial-analysis algorithm to scan Instagram photos.
Back then, in 2015, the ability to scan a person’s face and identify his
or her race was still in its infancy. Today, more than a dozen companies
offer some form of race or ethnicity detection, according to a review of
websites, marketing literature and interviews.
In the last few years, companies have started using such race-detection
software to understand how certain customers use their products, who
looks at their ads, or what people of different racial groups like.
Others use the tool to seek different racial features in stock
photography collections, typically for ads, or in security, to help
narrow down the search for someone in a database. In China, where face
tracking is widespread, surveillance cameras have been equipped with
race-scanning software to track ethnic minorities.
The field is still developing, and it is an open question how companies,
governments and individuals will take advantage of such technology in
the future. Use of the software is fraught, as researchers and companies
have begun to recognize its potential to drive discrimination, posing
challenges to widespread adoption.
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Munich-based Betaface offers a facial-analysis tool that estimates a
person's ethnicity. In this case, it says with 91% certainty that the
woman in the photo is Asian.
Photo: Betaface
A spokeswoman for Revlon says it was unable to comment because the
Instagram scanning happened several years ago. Kairos didn’t respond to
repeated requests for comment.
Race-detection software is a subset of facial analysis, a type of
artificial intelligence that scans faces for a range of features—from
the arch of an eyebrow to the shape of the cheekbones—and uses that
information to draw conclusions about gender, age, race, emotions, even
attractiveness. This is different from facial recognition, which also
relies on an AI technique called machine learning, but is used to
identify particular faces, for instance to unlock a smartphone or spot a
troublemaker in a crowd.
Facial analysis is “useful for marketers because people buy in cohorts
and behave in cohorts,” says Brian Brackeen, a founder of Kairos who
left in 2018 and now invests in startups through Lightship Capital.
For retailers and other businesses, facial analysis of camera footage
promises the ability to learn more about customers in bricks-and-mortar
settings, much like they have long used cookies, or small data files
that track people’s internet activity, to target online ads. “The
physical world is a big vacuum of data because there’s nothing there,”
says Ajay Amlani, senior vice president of corporate development at
French facial-recognition firm Idemia SAS. Now cameras are starting to
play a similar role to cookies.
New York-based Haystack AI Inc. says its customers use its
race-classification feature for ad targeting, market research and to
help authenticate people’s identities. Germany’s Cognitec Systems GmbH
offers ethnicity detection for retailers and other companies to collect
statistical data about their visitors, says Jeurgen Pampus, its sales
and marketing director. He said no customers had yet bought a license
for race-classification, though they had bought software for classifying
ages and genders.
Germany-based Cognitec Systems’s FaceVACS-VideoScan Console has a
filter, shown at mid-left, that lets users search faces by ‘ethnicity.’
Photo: Cognitec Systems
Spectrico, a Bulgarian startup that sells a perpetual, unlimited license
for its race-classification tool for 1,000 euros (about $1,170), says
that dating sites use it to check if profiles are accurate, while
advertisers use it to track the demographics of people looking at smart
billboards. Founder Martin Prenev said a few customers have purchased
the race-classification tool, and more bought it in combination with a
gender- and age-classification tool.
China’s Face++, one of the world’s biggest facial-recognition and
facial-analysis companies, was valued at $4 billion in May 2019,
according to market intelligence firm PitchBook. It says on its website
that its race-detection feature can be used for consumer-behavior
analysis and ad targeting.
Facial analysis has largely flown under the radar, even as facial
recognition has come under fire because poorly trained systems have
misidentified people of color. Places such as Boston, San Francisco,
Washington state and California have curbed the use of facial
recognition in law enforcement. IBM Inc., Alphabet Inc. and Microsoft
Corp. have limited their facial-recognition businesses, particularly in
selling to police departments.
Research into facial analysis continues. Some scientists say that
algorithms trained to identify a person’s race can be startlingly
accurate. In May, two scientists from Ruhr-Universitat Bochum in Germany
published a paper in the scientific journal Machine Learning showing
that their algorithm could estimate if a face was white, Black, Asian,
Hispanic or “other” with 99% accuracy. The researchers trained their
algorithms on a database of prison mug shots that included a label for
the race of each person, according to Dr. Laurenz Wiskott, one of the
study’s authors.
Some researchers and even vendors say race-based facial analysis should
not exist. For decades, governments have barred doctors, banks and
employers from using information about race to decide which patients to
treat, which borrowers to grant mortgages and which job applicants to
hire. Race-detection software poses the disconcerting possibility that
institutions could—intentionally or not—make decisions based on a
person’s ethnic background, in ways that are harder to detect because
they occur as complex or opaque algorithms, according to researchers in
the field.
For retailers and other businesses, facial analysis of camera footage
promises the ability to learn more about customers in bricks-and-mortar
settings.
Photo: Hannah Whitaker for The Wall Street Journal
Using AI to identify ethnicity “seems more likely to harm than help,”
says Arvind Narayanan, a computer science professor at Princeton
University who has researched how anonymized data can be used to
identify people.
A person of mixed race might disagree with how an algorithm classifies
them, says Carly Kind, director of the Ada Lovelace Institute in London,
a research group that focuses on applications of AI. “Technological
systems have the power to turn things into data, into facts, and
seemingly objective conclusions,” she says.
Software that lets employers scan the micro-expressions of job
candidates during interviews could inadvertently discriminate if it
starts to factor in race, Ms. Kind says. Police who classify ethnicity
using facial-analysis software run the risk of exacerbating racial
profiling, she says.
Ethnicity recognition could also be harmful if companies use it to push
marginalized people toward specific products or offer discriminatory
pricing, says Evan Greer, deputy director of digital rights group Fight
for the Future.
Use of face-scanning technology in China has been controversial, most
notably in Xinjiang, a region in the country’s northwest where
authorities have used it to surveil its Uighur Muslim minority. Last
year, a Chinese surveillance camera maker, Hangzhou Hikvision Digital
Technology, advertised a camera on its website that could automatically
identify Uighurs, according to security-industry trade publication IPVM.
China has used face-scanning technology to surveil its Uighur Muslim
minority in the Xinjiang region. This road, photographed in May 2019,
leads to a facility believed to be a re-education camp where mostly
Muslim ethnic minorities are detained.
Photo: greg baker/Agence France-Presse/Getty Images
Mr. Brackeen, who is Black, championed Kairos’s race-recognition system
because it could help businesses tailor their marketing to ethnic
minorities. Now, Mr. Brackeen believes that race-detection software has
the potential to fuel discrimination.
He is comfortable with businesses using it, but says governments should
not use it, and is wary of consumers using it too. Kairos released a
free app in 2017 that estimated race, showing how Black, white, Asian or
Hispanic people were if they uploaded a selfie. “I hoped that people
would see that 10% Black score and see the humanity in other people,”
Mr. Brackeen says.
More than 10 million people submitted selfies to the app to see the
results. Many of the app’s users, particularly in Brazil, complained on
social media that their scores weren’t white enough, Mr. Brackeen says.
The app was shut down.
In Northern Europe, a furniture chain used the facial-analysis software
of Dutch facial-recognition firm Sightcorp B.V. to screen customers
entering its stores, and learned that many of them were younger than it
had expected. It subsequently hired more people in their 20s and 30s to
be floor staff, according to Joyce Caradona, chief executive of
Sightcorp. Her company stopped selling its own ethnicity classification
feature in 2017, on concerns it might contravene Europe’s data-privacy
laws.
Facewatch Ltd., a British facial-recognition firm whose software spots
suspected thieves as they enter a store by screening them against a
watch list, earlier this year removed an option to track the race,
gender or age of shoppers, since “this information is irrelevant,” a
spokesman says.
There are security risks with collecting race data which could, either
by design or inadvertently, be linked to people’s identities, according
to Alex Heid, chief research officer at cybersecurity firm Security
Scorecard. His firm recently found about half a dozen websites with
security vulnerabilities around their databases holding people’s facial
data, including a facial-recognition firm and a U.S. engineering school
that required students to show their faces to log in.
Companies that offer facial-analysis services say the demographic data
their systems collect aren’t connected to individual identities. But
data brokers could, in theory, combine marketing databases that are
bought and sold online to create a more detailed picture of people on
them, Mr. Heid says, linking that data to identities.
A few years ago, companies that sold facial analysis were more open
about their ability to scan demographic features, says Zak Doffman, CEO
of Digital Barriers PLC, a British facial-recognition firm that works
with law enforcement. When large tech companies started getting flack
for their facial-recognition systems, “everyone stopped talking about
it,” he adds. “No one is talking about ethnicity identification now. Not
openly.”
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