Am I Pretty Quiz Accurate – I first came across Qoves Studio through its popular YouTube channel, which offers great videos like “Do Hairstyles Make a Beautiful Face?” “What makes Timothée Chalamet so attractive?” And “How Jaw Alignment Affects Social Perception” to millions of viewers.
Qoves started as a studio that created airbrushed images for fashion agencies. Now it’s a “facial beauty consultant” who promises to answer the “aging question of what makes a face attractive”. Her website, featuring sketches of Parisian women wearing lipstick and colorful hats, offers a wide range of services related to the cosmetic surgery consulting business: Introduction to beauty care products Examples and instructions on how to enhance the image using your computer. But its most compelling feature is the “Face Assessment Tool”: an AI-powered system that promises to look at pictures of your face to tell you how beautiful you are – or not – and then tell you what you can do about it. .
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Last week I decided to give it a try. Following the site’s instructions, I washed off the little makeup I was wearing and found a neutral wall lit by a small window. I asked my boyfriend to take a picture of my face at eye level. I try not to smile. It is the opposite of greatness.
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I posted the most lasting photos, and in a matter of seconds, Qoves spread 10 “predicted bugs” report cards on his face. I am. On the list is the probability of 0.7 of nasolabial folds, then 0.69 the probability of depression of contraction under the eyes and the probability of 0.66 of vascular color. On the other hand, it is suspected (correctly) that I have dark bags under my eyes and smile lines, both of which register problems with the AI.
This report responds to the recommendations I can take to address my concerns. First, the article that introduced the smile line informed me that “they may need intervention by injection or surgery”. If I want, I can upgrade to a full report of surgery instructions written by a doctor for $75, $150 and $250. He also introduced five serums that I could try first, each with different ingredients for skin care skin – Retinol, neuropeptides, hyaluronic acid, EGF and TNS. I’ve only heard of Retinol. Before going to sleep that night, I looked at the ingredients of my facial moisturizer to see what it contained.
I am interested. This device breaks down my appearance into a list of bite-sized laser issues trained on what it thinks is wrong with my appearance.
However, Qoves is just a small startup with 20 employees in the ocean of face analysis companies and services. There is a growing AI-driven facial analysis industry, each claiming to parse images for traits such as mood, age or attractiveness. Companies that work on such technology are a profitable investment, and such algorithms are used in everything from selling cosmetics online to dating applications. These beauty scores, available for purchase online, use computerized facial and vision analysis to assess things like symmetry, eye size and nose shape, to sort and rank millions of visible and displayed pieces of content.Most attractive people.
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These algorithms train machine vision on photos and videos, releasing numerical values similar to credit ratings, with the highest scores opening up the best online opportunities to view and compare preferences. Experts say that if expectations are not relevant enough, technology exacerbates other problems. Most beauty scoring algorithms are laden with inaccuracies, ageism and racism, and the proprietary nature of these systems means that it is impossible to gain an understanding of how it really works, both are using or how it affects users.
Tests like those from Qoves are available online. One is powered by the world’s largest open facial recognition platform, Face++. Its beauty scoring system was developed by Chinese imaging company Megvii and, like Qoves, uses AI to examine your face. But instead of describing in detail what she sees in clinical language, she makes her findings a percentage of attraction. In fact, it gives two results: one score that predicts how men might respond to the image and the other reflects the views of women. Using the free demo of the service and the same unimpressive photos, I got my results quickly. “Men generally think this person is more beautiful than 69.62% of people” and “Women generally think this person is 73.877% more beautiful”.
It was temperature resistant but better than expected. A year since the epidemic, I could see the effects of stress, weight, and the closing of barbershops on my appearance. I’ve tried the device with my other two photos before, both of which I like. My score improved, putting me near the top 25 percent.
Beauty is always thematic and personal: our loved ones look attractive to us when they are healthy and happy and even when they are sad. Sometimes it is a common judgment: classification systems, such as beauty pageants or magazine lists of the most beautiful people, show how we treat attractiveness as a reward. This assessment can also be wrong and uncomfortable: when I was young, the boys in my high school would shout from number one to number 10 to the girls walking down the hall. But what’s really surprising about a beauty pageant is that it’s as frustrating as screaming. At school, however, his mathematics felt inhuman.
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Although the concept of human attractiveness ratings is not new, the way these special systems work is a recent development: Face++ released its beauty score feature in 2017.
When asked for details on how the algorithm works, a Megvii spokesperson simply said that it was “created about three years ago in response to the local market’s interest in entertainment-related applications.” The company’s website shows that Chinese and Southeast Asian faces were used to train the system, which attracted 300,000 developers immediately after it launched, but there was little other information.
A spokesperson for Megvii says that Face ++ is an open source platform and cannot control how developers can use it, but the site recommends “selling cosmetics” and “comparison” as two potential applications.
Known clients of the company include Chinese government surveillance systems, which cover the country with CCTV cameras, as well as Alibaba and Lenovo. Megvii recently filed for an IPO and is currently valued at $4 billion. According to a report in the New York Times, it is one of three companies that helped the Chinese government identify potential Uighur citizens.
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Meanwhile, Qoves has revealed more about how its face analysis works. The Australian-based company was established as a photo editing company in 2019, but switched to a mix of AI-driven analytics and cosmetic surgery by 2020. Its system uses a common deep learning technique known as a convolutional neural network. Or CNN. The CNNs used to evaluate attractiveness, are usually trained on a data set of hundreds of thousands of images that have been manually calculated for human attractiveness. By looking at existing images and ratings, the system infers what factors people think are attractive, so it can Predict when to show a new image.
Other big companies have invested in beauty AIs in recent years. They include US cosmetics retailer Ulta Beauty, worth $18 billion, which developed the skin scanner. Nvidia and Microsoft sponsored the “Robot Beauty Contest” in 2016, which led participants to develop the best AI to define attractiveness.
According to Evan Nisselson, partner at LDV Capital, vision technology is still in its infancy, creating “significant investment and growth opportunities”. LDV estimates that there will be 45 billion cameras in the world next year, excluding devices used for manufacturing or transportation, and claims that visual data will become important data for future AI systems . Soon. Nisselson says facial analysis is a “huge market” that will include “redesigning the technology stack to get closer or closer to or better than the human eye.”
Qoves founder Shafee Hassan claims that the beauty score could be even more widespread. He says social media apps and platforms often use systems that scan people’s faces, give them points for attractiveness, and pay more attention to those with higher rankings. “What we’re doing is doing something similar to Snapchat, Instagram and TikTok,” he says. “But we are making it more transparent.”
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“They’re using the same neural network and they’re using the same technique, but it doesn’t tell you that [they’ve] determined that your face has this nasolabial fold, it has thin fibers,” he added. “There are all these things, so [they] punish you as an unattractive person.”
I contacted a number of companies, including dating services and social media forums, and asked if beauty rating was part of their referral algorithm. Instagram and Facebook refused to use these algorithms. TikTok and Snapchat deny
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