20 years after Mark Zuckerberg’s infamous ‘hot-or-not’ website, developers have learned absolutely nothing.
Two decades after Mark Zuckerberg created FaceMash, the infamously sexist “hot-or-not” website that served as the precursor to Facebook, a developer has had the bright idea to do the exact same thing—this time with all the women generated by AI.
A new website, smashorpass.ai, feels like a sick parody of Zuckerberg’s shameful beginnings, but is apparently meant as an earnest experiment exploring the capabilities of AI image recommendation. Just like Zuck’s original site, “Smash or Pass” shows images of women and invites users to rate them with a positive or negative response. The only difference is that all the “women” are actually AI generated images, and exhibit many of the telltale signs of the sexist bias common to image-based machine learning systems.
For starters, nearly all of the imaginary women generated by the site have cartoonishly large breasts, and their faces have an unsettling airbrushed quality that is typical of AI generators. Their figures are also often heavily outlined and contrasted with backgrounds, another dead giveaway for AI generated images depicting people. Even more disturbing, some of the images omit faces altogether, depicting headless feminine figures with enormous breasts.
According to the site’s novice developer, Emmet Halm, the site is a “generative AI party game” that requires “no further explanation.”
“You know what to do, boys,” Halm tweeted while introducing the project, inviting men to objectify the female form in a fun and novel way. His tweet debuting the website garnered over 500 retweets and 1,500 likes. In a follow-up tweet, he claimed that the top 3 images on the site all had roughly 16,000 “smashes.”
Understandably, AI experts find the project simultaneously horrifying and hilariously tonedeaf. “It’s truly disheartening that in the 20 years since FaceMash was launched, technology is still seen as an acceptable way to objectify and gather clicks,” Sasha Luccioni, an AI researcher at HuggingFace, told Motherboard after using the Smash or Pass website.
One developer, Rona Wang, responded by making a nearly identical parody website that rates men—not based on their looks, but how likely they are to be dangerous predators of women.
The sexist and racist biases exhibited by AI systems have been thoroughly documented, but that hasn’t stopped many AI developers from deploying apps that inherit those biases in new and often harmful ways. In some cases, developers espousing “anti-woke” beliefs have treated bias against women and marginalized people as a feature of AI, and not a bug. With virtually no evidence, some conservative outrage jockeys have claimed the opposite—that AI is “woke” because popular tools like ChatGPT won’t say racial slurs.
The developer’s initial claims about the site’s capabilities seem to be exaggerated. In a series of tweets, Halm claimed the project is a “recursively self-improving” image recommendation engine that uses the data collected from your clicks to determine your preference in AI-generated women. But the currently-existing version of the site doesn’t actually self-improve—using the site long enough results in many of the images repeating, and Halm says the recursive capability will be added in a future version.
It’s also not gone over well with everyone on social media. One blue-check user responded, “Bro wtf is this. The concept of finetuning your aesthetic GenAI image tool is cool but you definitely could have done it with literally any other category to prove the concept, like food, interior design, landscapes, etc.”
Halm could not be reached for comment.
“I’m in the arena trying stuff,” Halm tweeted. “Some ideas just need to exist.”
Luccioni points out that no, they absolutely do not.
“There are huge amounts of nonhuman data that is available and this tool could have been used to generate images of cars, kittens, or plants—and yet we see machine-generated images of women with big breasts,” said Luccioni. “As a woman working in the male-dominated field of AI, this really saddens me.”
The details are literally women being objectified, and blackface. You have intentionally chosen to not read words to… What exactly are you trying to achieve here? Actually read the post and the comment you have responded to and think deeply about your rhetoric and the meaning and time you chose to dedicate.
someone tried to shift the narrative to racism, comparing generating ai images of women to wearing blackface, asking the above poster if they thought that wasnt racist. I don’t think these are in any way equivalent, or even related, so I provided an example i considered comparable, and asserted that that would not be racist.
I don’t try to shift the narrative, I use the same method than Simone De Beauvoir in The Second Sex to highlight a discrimination.
Generating the picture of a black person is not racist (the AI could have bias, but that’s an other subject). But generating pictures of persons in different skin tons on a website called apartheid.ai and making people vote “white or black”, that would be racist.
The problem here is not generating picture of women, but how these pictures are used.
i’m sorry, then, i misunderstood - and if, as someone else suggested, you were simply being hyperbolic in bringing up blckface as a comparative example, then i’m sorry i didn’t catch that.
I’m sorry, I should have been more clear
We are certainly agreed that the circumstances surrounding and contained within an image impact the harm it does, be it racism or sexism or anything else.
Which begs the questions, do you know that the person you initially responded to was using hyperbole to draw out a point from the person they were responding to? Do you not care for analogy? Why did you choose to specifically not read the comment you were responding to to make a tangential point after being grilled for two additional comments to actually make your point?
The most charitable explanation to all of the above is that you’re here to win an argument, content and rhetoric or implications or literal interpretations of your comments text, be damned, despite otherwise actually (nominally) agreeing in no uncertain terms with the commenter you responded to negatively.