black woman (1)Google search: Why do Black people…have big lips? Say “ax” instead of “ask”? Like watermelon? Like fried chicken? These are just a few of the collective stereotypes that often pop up when Google attempts to autofill users’ search terms.

Now a new search engine prejudice has reared its ugly head, thanks to a recent study by a trio of Brazilian researchers. Camila Souza Araujo, Wagner Meira Jr., and Virgilio Almeida of the Universidade Federal de Minas Gerais in Brazil released a report Wednesday examining the representation of female beauty on popular search engines like Google and Bing.

Appropriately titled “Identifying Stereotypes in the Online Perception of Physical Attractiveness,” the study confirmed the unsurprising “existence of stereotypes for female physical attractiveness, in particular, negative stereotypes about Black women and positive stereotypes about white women in terms of beauty.”

The trio analyzed the top 50 image results for “beautiful woman” and “ugly woman” across several international versions of Google and Bing. Sadly, for almost every country and region analyzed, images of white women were associated with the term “beautiful woman” while Black and Asian women were associated with “ugly woman.”

Negative stereotypes against older women were also revealed in the study.

According to the report, 85.7 percent of the countries examined in Google and 76.4 percent of the countries in Bing displayed negative stereotypes of Black women. These countries included Spain, Guatemala, Argentina, USA, Peru, Mexico, Venezuela, Chile, Brazil and Paraguay among others.

“…These are countries with a strong presence of the Hispanic and Latino cultures,” the study reads. “The centroid of this cluster (Black: -3.28, Asian: 0.60, white: 2:02) indicates that for this group of countries, there is a very negative stereotype regarding Black women and a positive stereotype for white women.”

Looking at the U.S. specifically, searches for “beautiful” women returned images that were 80 percent white, and featured women between the ages of 19 and 28. Searches for “ugly” women returned 60 percent white images and 30 percent Black, all between the ages of 30 and 50.

The study also reported negative stereotypes of Black women in African countries like Nigeria and Angola, which have predominant populations of people with black and brown skin.

This isn’t the first time bias on search engines has been observed, however. In June 2016, a Virginia teen searched the nearly identical search terms, “Three Black Teenagers” and “Three White Teenagers;” the results were striking. According to Atlanta Black Star, the first search produced several mug shots of Black male teens, but the second revealed stock photos of smiling white youths. The teen, Kabir Alli, posted video of himself conducting the search, which later went viral.

“I understand it’s all just an algorithm based on most visited pages, but Google should be able to have more control over something like that,” Alli told USA Today.

A former substitute teacher launched her own website promoting positive images of Black people after finding few images of African-Americans when she Googled the phrase “beautiful people.”

“…We focus on creating a healthy image I would say for men, women, and children of color because there’s so much negativity out there about African-Americans when it comes to the media,” Candace Edwards, founder of I Am Beautiful 365, told Atlanta Black Star.

“In my mind, it’s all about positive programming or positive brainwashing,” she continued. “I feel like perception equals reality. And so unfortunately, we do see a lot of negativity in the [media] about people of color. And you’re gonna start to believe it if you see it all the time. So we need to put something else out there.”

So are search engine algorithms to blame for the biased image results? According to researcher Virgilio Almeida, yes and no.

While pre-existing social biases play a major role in shaping image search results, Almeida explained that “the way search engines index and rank images” can also add to the creation and perpetuation of stereotypes.

“We do not have [enough] information about the techniques used by search engines to rank images and photos,” he told the Washington Post via e-mail.

The authors of the study also made it a point to note that they couldn’t determine exactly what caused the positive and negative stereotypes identified in their study.

“They may stem from a combination of the stocks of available photos and characteristics of the indexing and ranking algorithms of the search engines,” their report read. “The stock of photos online may reflect prejudices and bias of the real world that transferred from the physical world to the online world by the search engines.”

“Given the importance of search engines as source of information, we suggest that they analyze the problems caused by the prominent presence of negative stereotypes and find algorithmic ways to minimize the problem,” they concluded.

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