The term “artificial intelligence” might always remind us of Black Mirror or The Matrix, but there’s no denying that the once-futuristic tech has infiltrated our lives in nearly every way. Now, tech-minded skin-care founders are using machine learning to tackle concerns like acne, reports Allure.
AI in skin care
“The skin-care industry is very marketing driven and product development is based on trendy ingredients,” says Meghan Maupin, CEO and cofounder of Atolla, customized skin care designed to become more effective with each monthly shipment, thanks to subtle reformulations powered by customer feedback and a patented algorithm.
“Our approach is to let the data show us patterns across different customer groups, and what formulations might work best for each… machine learning is the start of the skin-care industry becoming more data-driven.”
Atolla collects its data points through a quiz that covers the participant’s skin goals and history, allergies, current product routine, medications, and lifestyle; a mail-in skin test that seeks to measure hydration and sebum levels through a blotting paper-like tool; and a selfie that helps remote aestheticians assess concerns.
How does this algo work?
Its algorithm then compares your data to other users who have similar skin concerns — seeing what worked for them — and scans for ingredient conflicts in your routine before generating a customized serum, which it will auto-ship to the customer for $39 a month or bundle with a cleanser and moisturizer for $69 per month.
“For customers with acne or breakouts, we’re able to titrate your dosage of active ingredients up or down each month in response to your skin progress,” Maupin adds.
Importance of the data collection
Atolla is just one of many new companies that understand the monetary value of data, the appeal of bespoke personal-care products, and the power of a subscription model. In some respects, there’s a data-driven beauty gold rush happening.
Then there are brands, like Curology, which use the expertise of medically-trained providers (doctors, physician assistants), to create unique formulations that target breakouts, fine lines, and other skin concerns.
Similarly, there is Docent, which employs medical doctors to assess a makeup-free selfie and vanity shelfie before shipping your skin prescription.Machine learning is even being used to improve the subscription box model.
“We use data to connect customers to products that work and curate high-performing skin-care routines that they never would have assembled on their own,” says Katrina Moreno Lewis, founder and CEO of Kura Skin, a quarterly subscription box that offers a complete, bespoke routine — from cleanser to sunscreen — that starts at $99 or can be purchased as a one-off.
How effective is this process?
“Self-reported data has limits,” says Corey L. Hartman, M.D., a board-certified dermatologist based in Birmingham, Alabama, explaining that the very language we use to describe our skin concerns is up for interpretation. “There aren’t very many specific parameters or criteria for some of these terms that we put a lot of credibility on.”
For example, he says the reason why medical papers don’t use the terms “dry,” “oily,” or “combination” is that they mean different things to different people. “These are things that we talk about in beauty spaces and marketing, but in terms of real scientific data, there’s nothing that’s tied to that, so what does it really mean?”
Is Your data safe?
Margaret Foster Riley, a health privacy expert and professor of law at The University of Virginia, raises a few red flags about this growing trend. “Sometimes you’ll see companies will assert that they’ll never sell or use your data improperly but what’s unclear is what happens in a succession context,” she says, noting that your data might not be protected in a bankruptcy or acquisition.
Then there are potential long-term risks: “A lot of people [who willingly provide their data to companies] are young and healthy and not thinking of the impact that might be with health insurance or, even in some contexts, employment,” Riley adds.
“They go into it willing to share everything, then, later on, they recognize that if things come out they may have an obligation to share it with a long-term care company or a life insurance company and they weren’t thinking about that at the time.” It gets more complicated when more-in depth tests are involved, a natural progression of the trend we are undoubtedly going to see increasing.
Right now, the tech is geared towards women, but Egan says they plan to expand to men in the future. “We focus on women because we test estrogen and progesterone, which are female dominant hormones, but have had men take the test,” she says. “In the future, we’ll be able to provide more customized insight for men.”
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