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Alphabet Incs Google told Reuters this week that it is developing an alternative to the industry-standard method for classifying skin tones.

At issue is a six-color scale known as the Fitzpatrick Skin Type (FST), which dermatologists have been using since the 1970s. Technology companies are now using this to classify people and measure whether products such as facial recognition systems and smartwatch heart rate sensors work equally well across skin tones.

Critics say the FST, which includes four categories for white skin and one for black and brown, ignores diversity among people of color. At the Federal Technical Standards Conference last October, U.S. Department of Homeland Security researchers abandoned FST to assess facial recognition because FST does not adequately represent the color range of diverse populations. Recommended.

For the first time in Reuters’ question about FST, Google said it was quietly pursuing better measures ahead of its peers.

The company said it is working on more comprehensive alternatives that may help in product development and will work with scientific and medical professionals and groups that work with the color community. .. effort.

We assume that ensuring that technology works well for all skin tones is more important for new products.

The controversy is part of a larger calculation of racism and diversity in high-tech industries where the workforce is whiter than sectors like finance. Ensuring that technology works well not only for all skin colors, but also for different ages and genders, new products often equipped with artificial intelligence (AI) are delicate, such as in medical and law enforcement agencies. It is becoming more and more important as it extends to areas regulated by.

Companies are aware that their products may be defective for groups that are underestimated in survey and test data. The concern with FST is that its limited scale for darker skin can lead to techniques that work for, for example, golden skin, but fail for espresso red tones.

Many types of products offer a much richer palette than FST. Crayola launched 24 skin tone crayons last year, and Mattel Inc.’s Barbie Fashionista doll covers nine tones this year.

This issue is far from academic for Google. When the company announced in February that some Android smartphone cameras could measure pulse rates at the fingertips, it said the measurements would average 1.8% error, regardless of whether the user’s skin was light or dark. ..

The company later said that skin type had no noticeable effect on the results of the ability to filter backgrounds in Meet video conferencing and the results of an upcoming web tool for identifying skin conditions informally called Derm Assist. Guarantee was given.

These conclusions were drawn from testing with a 6-tone FST.

Starting point

Dr. Thomas Fitzpatrick, a late Harvard dermatologist, invented a scale to personalize UV ​​treatment for psoriasis, an itchy skin condition. He categorized white skin into Roman numerals I to IV and asked how much sunburn and sunburn occurred in specific sunlight.

Ten years later, Type V appeared on brown skin and Type VI on black. This scale is part of the US regulation for testing sunscreen products and continues to be a common dermatological standard for assessing patients’ cancer risk and more.

Some dermatologists say that this scale is an inadequate and worn-out scale for care and is often confused with race and ethnicity.

Dr. Susan Taylor, a dermatologist at the University of Pennsylvania who founded the Skin of Color Society in 2004 to facilitate research in a community that has reached its limits, says that I have a skin type V that causes almost no burns. I think you are thinking. Looking at my skin tone and saying I’m Type V hurt me. Until recently, tech companies were indifferent. Unicode, an industry group that oversees emoji, mentioned FST in 2014 as the basis for adopting five skin tones other than yellow.

In a 2018 study titled Gender Shades, facial analysis systems often misunderstood people with dark skin, and used FST to evaluate AI. The study explained the FST as a starting point, but scientists from similar studies later told Reuters that they used scales for consistency.

As a first step towards a relatively immature market, it serves the purpose of helping us identify danger signals, said Mozilla Fellow Inioluwa Deborah Raji, who focused on AI auditing.

In a April study testing AI to detect deepfake, researchers at Facebook Inc wrote that FST clearly does not include a variety of brown and black skin tones. Still, they released 3,000 videos used to evaluate AI systems and tagged them with FST based on the ratings of eight human evaluators.

The judgment of the evaluator is the main focus. Last year, facial recognition software startup AnyVision provided evaluators with examples of celebrities. Former baseball great Derek Jeter as Type IV, model Tyra Banks a V, and rapper 50 Cent a VI.

AnyVision told Reuters that it agreed with Google’s decision to reconsider the use of FST, saying Facebook could accept better measures.

Microsoft Corp and smartwatch makers Apple Inc and Garmin Ltd refer to FST when working on health-related sensors.

However, the use of FST can foster false assurances about heart rate readings from dark-skinned smartwatches, clinicians at the University of California, San Diego said in a social equality movement at Black Lives Matter. Inspired by, I wrote in last year’s journal Sleep.

Microsoft has acknowledged a flaw in FST. Apple said it uses a variety of means to test humans beyond skin color. Garmin said he believed the measurements were reliable for extensive testing.

Victor Casale, who founded the makeup company Mob Beauty and helped Crayola with a new crayon, developed 40 shades for the foundation, each about 3 percent different from the next shade, or so that most adults can distinguish it. I said that I did.

He added that the color accuracy of electronics suggests that the technical standard should have 12 to 18 tones.

Published in Dawn on The Business and Finance Weekly on June 21, 2021.

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