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AI art of a woman in a white dress, who is sitting in a chair looking resigned. Her fingers are funky looking. Image: Lensa AI

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Lensa’s viral AI art creations were bound to hypersexualize users

AI-generated art is rife with issues

Nicole Clark (she/her) is a culture editor at Polygon, and a critic covering internet culture, video games, books, and TV, with work in the NY Times, Vice, and Catapult.

This year, it feels like artificial intelligence-generated art has been everywhere.

In the summer, many of us entered goofy prompts into DALL-E Mini (now called Craiyon), yielding a series of nine comedically janky AI-generated images. But more recently, there’s been a boom of AI-powered apps that can create cool avatars. MyHeritage AI Time Machine generates images of users in historical styles and settings, and AI TikTok filters have become popular for creating anime versions of people. This past week, “magic avatars” from Lensa AI flooded social media platforms like Twitter with illustrative and painterly renderings of people’s headshots, as if truly made by magic.

These avatars, created using Stable Diffusion — which allows the AI to “learn” someone’s features based off of submitted images — also opened an ethical can of worms about AI’s application. People discovered that the “magic avatars” tended to sexualize women and appeared to have fake artist signatures on the bottom corner, prompting questions about the images that had been used to train the AI and where they came from. Here’s what you need to know.

What is Lensa AI?

It’s an app created by Prisma Labs that recently topped the iOS app store’s free chart. Though it was created in 2018, the app became popular after introducing a “magic avatar” feature earlier this month. Users can submit 10 to 20 selfies, pay a fee ($3.99 for 50 images, $5.99 for 100, and $7.99 for 200), and then receive a bundle of AI-generated images in a range of styles like “kawaii” or “fantasy.”

The app’s “magic avatars” are somewhat uncanny in style, refracting likenesses as if through a funhouse mirror. In a packet of 100, at least a few of the results will likely capture the user’s photo well enough in the style of a painting or an anime character. These images have flooded Twitter and TikTok. (Polygon asked Prisma Labs for an estimate of how many avatars were produced, and the company declined to answer.) Celebrities like Megan Fox, Sam Asghari, and Chance the Rapper have even shared their Lensa-created likenesses.

How does Lensa create these magic avatars?

Lensa uses Stable Diffusion, an open-source AI deep learning model, which draws from a database of art scraped from the internet. This database is called LAION-5B, and it includes 5.85 billion image-text pairs, filtered by a neural network called CLIP (which is also open-source). Stable Diffusion was released to the public on Aug. 22, and Lensa is far from the only app using its text-to-image capabilities. Canva, for example, recently launched a feature using the open-source AI.

An independent analysis of 12 million images from the data set — a small percentage, even though it sounds massive — traced images’ origins to platforms like Blogspot, Flickr, DeviantArt, Wikimedia, and Pinterest, the last of which is the source of roughly half of the collection.

More concerningly, this “large-scale dataset is uncurated,” says the disclaimer section of the LAION-5B FAQ blog page. Or, in regular words, this AI has been trained on a firehose of pure, unadulterated internet images. Stability AI only removed “illegal content” from Stable Diffusion’s training data, including child sexual abuse material, The Verge reported. In November, Stability AI made some changes that made it harder to make NSFW images. This week, Prisma Labs told Polygon it too “launched a new safety layer” that’s “aimed at tackling unwanted NSFW content.”

Stable Diffusion’s license says users can’t use it for violating the law, “exploiting, harming or attempting to exploit or harm minors,” or for generating false information or disparaging and harassing others (among other restrictions). But the technology itself can still generate images in violation of those terms. As The Verge put it, “once someone has downloaded Stable Diffusion to their computer, there are no technical constraints to what they can use the software for.”

Why did AI art generators become so popular this year?

Though this technology has been in development for years, a few AI art generators entered public beta or became publicly available this year, like Midjourney, DALL-E (technically DALL-E 2, but people just call it DALL-E), and Stable Diffusion.

These forms of generative AI allow users to type in a string of terms to create impressive images. Some of these are delightful and whimsical, like putting a Shiba Inu in a beret. But you can probably also imagine how easily this technology could be used to create deepfakes or pornography.

A series of four images of a shiba inu, shoulders up, wearing a red beret. They were created using the prompt “a close up of a shiba inu wearing a red beret, from the shoulders up, facing forward.”
These images were generated using DALL-E 2.
Image: DALLE-2

There’s also a degree of finesse that AI art just can’t seem to get — at least, not yet. It tends to struggle with fingers — did you want 12? — and has produced downright nightmarish creations like multiple broken heads and faces.

Stable Diffusion, unlike DALL-E, Midjourney, and Google’s Imagen, is open-source and has thus proliferated widely. Midjourney, which was created by an independent team, entered open beta this summer; you can generate 25 free images if you join its Discord. DALL-E, created by OpenAI, debuted in April before removing its waitlist and opening up beta access in September, at which point users generated some 2 million images a day. DALL-E gives users monthly free credits that can be used to generate images, and you can pay for additional credits. Anyone can use Stable Diffusion, granted they have adequate processing power. It is also, compared to its competitors, much more unfiltered — and thus able to be used to make more offensive images.

Stability AI, the company behind Stable Diffusion, acknowledged in a release that “the model may reproduce some societal biases and produce unsafe content.” Polygon reached out to Stability AI and will update this story with its response.

A series of four AI generated images made from the prompt “pikachu and eevee talking next to a pokemon trainer in a field of lowers, in an illustrated style.”
These images were generated using DALL-E 2.
Image: DALL-E 2

Prisma Labs acknowledges Stable Diffusion’s biases in its FAQ as well. When Polygon asked Prisma Labs about the existence of bias in generative AI, we got this response: “It’s crucial to note that creators of Stable Diffusion Model trained it on a sizable set of unfiltered data from across the internet. So neither us, nor Stability AI (creator of the Stable Diffusion Model) could consciously apply any representation biases. To be more precise, the man-made unfiltered data sourced online introduced the model to the existing biases of humankind. Essentially, AI is holding a mirror to our society.”

What types of bias show up in Lensa AI?

A number of reporters have pointed out Lensa AI’s “magic avatars” tend to sexualize women and anglicize minorities. Lensa has added large breasts and cartoonish cleavage to images of women — along with generating nudes — when such images weren’t requested.

Olivia Snow, a research fellow at UCLA’s Center for Critical Internet Inquiry, pointed out in Wired that Lensa produced sexualized images even when she submitted photos of herself as a child. A Jezebel reporter asked Prisma Labs about Snow’s findings; Prisma Labs said that Snow had “explicitly and intentionally violated [its] Terms of Use.” Lensa’s terms of service forbid submitting nudes and direct users to submit images of adults, “no kids.” The app also prompts users to click a box indicating that they are 18 years old or over before creating these “magic avatars.”

Lensa also perpetuates racist stereotypes, like the fetishization of Asian women. An Asian journalist writing for MIT Technology Review detailed her experience with Lensa’s app giving her a number of avatars that were “nude” or “showed a lot of skin,” while her white female colleagues “got significantly fewer sexualized images.”

TechCrunch has also noted that it’s fairly easy to create NSFW images of celebrities simply by feeding the AI photoshopped images. This has startling implications for the way such software could be used to create revenge porn, for example. (Particularly concerning, too, as the number of revenge porn victims skyrocketed during the COVID-19 pandemic.)

On Dec. 13, Prisma Labs launched new features aimed at tackling NSFW images. A communications representative pointed Polygon to a press release: “This was achievable by a thorough investigation to update and tweak several parameters of the Stable Diffusion model leveraged by the app. To address recent safety concerns and improve overall experience in the app, Prisma Labs developers ensured to make generation of such Avatars less likely. On rare occasions, when the new NSFW algorithm fails to perform and deliver desired results, the next security layer kicks in to blur any inappropriate visual elements and nudity in the end results.”

Have you seen it in action?

Yes, I have! On Dec. 13, I fed 19 images to Lensa in order to produce 100 avatars, which cost me $5.99. The images I chose presented my face in various angles and lighting. One of these images showed my body — I was wearing a loose dress, and taking a photo in the mirror.

I received 100 images in return, which offered a panoply of dissected features across so many faces that ultimately did not look like me. Lensa seemed to have no idea what to do with my face — I am Taiwanese and white — creating some images that looked East Asian but otherwise like complete strangers, save for one particular quirk or other of mine, like my jawline or eye shape. Some images simply looked like white women, with Lensa even giving me blue eyes — though I have brown eyes, and none of the images I submitted showed me with blue eyes.

These modifications clustered around particular “categories” delineated by the app. The images for “kawaii” looked more East Asian, with a few generating a body that was slim. Under “light” and “fantasy,” the results looked more white. Some of the images in the “iridescent” pack made me look like an android — I’d be interested in comparing my results to others’, as it reflects a trope where Asian women in science fiction tend to be depicted as robots more than they exist as human people. One image in the “cosmic” set gave me random cleavage. Luckily, none of the images were nudes.

Why are these AI image generators racist and misogynistic?

It comes down to how these AIs are “trained.” AI will reflect what it has “learned” through the data set it was fed, whether that be a gorgeous art style or grotesque societal bias.

A study conducted in June 2022 by researchers at Georgia Institute of Technology and Johns Hopkins University, among others, found that robots trained by the neural network CLIP “definitively show robots acting out toxic stereotypes” regarding gender and race. They were also “less likely to recognize women and people of color.” The robot more frequently chose a Black man’s face when prompted with “criminal,” for example, and selected Black women and Latina women when prompted “homemaker.”

Racism in AI isn’t new, but for years it’s felt more science fiction than reality; it’s only becoming more relevant as AI-generated art has “arrived” to the extent that you can pay a fee to enjoy it yourself. And it’s not just Stable Diffusion. DALL-E also generates images that reinforce misogynistic and racist stereotypes. Inputting “nurse” yields images of women, while “CEO” yields mostly images of white men. OpenAI is aware of this. An OpenAI blog post, published in July, detailed a “new technique” to “reflect the diversity of the world’s population.” OpenAI also blocks certain words that would yield hateful responses, like the word “shooting.”

Four images generated by DALL-E 2 showing a nurse talking to a patient. This was the prompt: “a nurse talking to a patient who is sitting in a chair, they are in a waiting room together.”
These images were generated using DALL-E 2. The results still overwhelmingly show women when prompted with “nurse.”
Image: Lensa AI

The “Risks and Limitations” section of OpenAI’s Github, updated April 2022, gives a bit of insight into the hurdles that came with training the AI. “Graphic sexual and violent content” were filtered from the training data set, but this also reduced the number of “generated images of women in general.” Put simply, getting rid of sexual violence meant the AI created fewer images of women.

“Bias is a huge industry-wide problem that no one has a great, foolproof answer to,” Miles Brundage, the head of policy research at OpenAI, told Vox in April.

Even Craiyon (née DALL-E Mini) has a limitations and biases section in its FAQ noting that it might “reinforce or exacerbate societal biases.” It further notes “because the model was trained on unfiltered data from the Internet, it may generate images that contain harmful stereotypes.”

And how do artists feel about Lensa?

Artists have expressed concern about Stable Diffusion training its AI model with art on the internet — some of which is almost certainly copyrighted, given the breadth of what was scraped — without asking those artists for their permission. There isn’t really a way for artists to opt out currently.

Some of Lensa’s “magic avatars” appear to have an artist’s signature on the bottom corner, which sparked debate on Twitter. Though the letters themselves tend to look incoherent, upon close examination, it does indicate that the AI was trained on images that do have artist signatures. (Prisma Labs acknowledges these phantom signatures in its Lensa FAQs.)

Using the site “Have I Been Trained” allows people to search whether an image has been scraped into the LAION-5B data set. Some people have found images of themselves in the data set, without understanding how they ended up there, to add this ethical Gordian knot.

In other pushback, people have said AI might replace artists in a variety of fields. In September, art created by Midjourney won first place at the Colorado State Fair’s fine arts competition. In June, DALL-E made a magazine cover for Cosmopolitan. Some have also argued that coming up with the right input query for an AI art generator, which can be a long and iterative process, should be considered its own form of art creation.

Examples of AI replicating artistic aesthetics are already spreading on the internet. Polish digital artist Greg Rutkowski’s artwork has become a dominant style that many of these AI-generated images appear to be based on. Twitter users have fed the prompt “in the style of Wes Anderson” to create frames of other films in the director’s signature twee style. Directors like Guillermo del Toro and Hayao Miyazaki (the latter in 2016, when the technology was far more emergent) have spoken against the use of AI in filmmaking, both calling it “an insult to life itself.”

Meanwhile, some artists have already cited Midjourney as crucial to their creative process, particularly designers who might otherwise not be able to afford early mock-ups — or professionals like interior designers who used it to render what a newly decorated room might look like.

There’s already one prominent example of AI art in video games. High on Life, created by Rick and Morty creator Justin Roiland, uses Midjourney-created AI art for “finishing touches,” Roiland confirmed to Sky News. Though he didn’t state what it was used for, Redditors have pointed out that in-game posters appear to be AI-generated. (Zoom in, and the text looks gibberish.) It’s not hard to imagine how AI art might displace environment and texture artists, for example, when it is free — or, at least, cheap — and human labor is not.

For its part, Prisma Labs provided this extraordinarily optimistic quote to Polygon about the future of AI and AI-generated art: “‘Democratization of access’ to cutting-edge technology like Stable Diffusion, which is now packaged in the shape and form of an app feature - is quite an incredible milestone. What was once available only to techy well-versed users is now out there for absolutely everyone to enjoy. No specific skills are required. As AI technology becomes increasingly more sophisticated and accessible, it is likely that we will see AI-powered tools and features being widely integrated into consumer-facing apps, making each app more powerful, customisable and user-friendly. We’d like to imagine that AI may also become more integrated into our daily lives with more consumers opting to use AI-powered services to enhance their experiences and ultimately make life a little easier and less stressful. Overall, we believe that the future of AI-powered apps looks bright and full of potential.”

It’s hard enough, on the internet, to detect fact from fiction. It’s also already difficult to make a living in a creative field, as competition and inflation wreak havoc across the industry. Generative AI will only make things more difficult. Regardless of how this technology is applied — and the degree to which artists are impacted — this much seems certain.