We’re thrilled to sit down with Laurent Giraud, a renowned technologist with deep expertise in Artificial Intelligence, particularly in machine learning, natural language processing, and the ethical challenges posed by AI. Today, we’re diving into a troubling trend flooding the internet: AI-generated “bikini interview” videos. These hyper-realistic, fabricated clips are raising serious concerns about sexism, trust in online content, and the broader societal impact of unchecked AI tools. In this conversation, we’ll explore how this technology works, why it often targets women in harmful ways, and what it means for the future of digital spaces.
How do AI-generated videos, like these so-called “bikini interviews,” achieve such a lifelike appearance, and what kind of technology drives their creation?
These videos leverage advanced AI models, particularly generative adversarial networks (GANs) and diffusion models, which are trained on massive datasets of real footage and images. They can synthesize visuals and audio that mimic human behavior down to tiny details—think facial expressions, lip sync, even background crowd noise. Tools in this space often combine machine learning with natural language processing to script dialogue or overlay voices. The result is content that feels authentic, even when it’s entirely fabricated. It’s a testament to how far AI has come, but also a warning about its potential for misuse.
Why do you think these AI-generated clips so often portray women in sexualized or derogatory ways, such as in bikinis or being mocked?
It’s largely a reflection of societal biases that already exist, amplified by the incentives of online platforms. Content creators—whether individuals or larger networks—know that shock value and sexualization drive clicks and engagement. AI just makes it easier to scale this kind of content without real people or accountability. It’s not that the technology itself is biased; it’s trained on data that mirrors our cultural flaws, including misogyny. So, when creators input prompts or seek viral content, the output often defaults to gendered stereotypes because that’s what’s rewarded by algorithms and audiences.
In what ways are these fake videos reshaping how people perceive and trust content on social media?
They’re eroding trust at an alarming rate. When you can’t tell if a video is real or AI-generated, every piece of content becomes suspect. This isn’t just about entertainment—it affects how we process news, personal stories, or even evidence. People are already skeptical of online information, and these hyper-realistic fakes blur the line further, making it harder to separate fact from fiction. Over time, this could desensitize users or make them disengage entirely from digital spaces as a source of truth.
Who’s behind the creation of these videos, and what motivates them to produce this kind of content?
It’s a mix of individual creators and emerging cottage industries. Many are everyday people—students, freelancers, or gig workers—who see AI as a quick way to make money through viral content. Platforms often have incentive programs that reward high engagement with ad revenue or partnerships, so there’s a clear financial driver. On the other side, you have more organized efforts where creators sell courses or tools to mass-produce this “slop.” The low barrier to entry with AI tools means almost anyone can jump in, often without considering the ethical fallout.
What are some of the real-world impacts of these videos on women, both in digital spaces and beyond?
The impact is profound and often damaging. Online, these videos perpetuate harmful stereotypes, normalizing misogynistic humor or behavior as entertainment. They contribute to a culture where women are objectified or ridiculed for views. In real life, this can translate to increased harassment or bias, as these attitudes bleed into everyday interactions. I’ve read accounts of women whose likenesses were used without consent in similar AI content, leading to personal distress and reputational harm. It’s a form of digital violence that can have very tangible consequences.
How are social media platforms handling the surge of AI-generated content like this, and are their efforts enough?
Platforms are struggling to keep up. Some have introduced policies to label or demonetize inauthentic content, but enforcement is inconsistent. The challenge lies in detection—AI content is getting harder to spot, and many platforms have cut back on human moderators in favor of automated systems, which aren’t always effective. There’s also a tension between free expression and regulation; cracking down too hard risks backlash, while doing too little allows harm to spread. Right now, their response feels like a patchwork—necessary, but far from sufficient.
What’s your sense of the scale of this issue, and do you see it growing in the near future?
The scale is staggering and likely underreported. Studies from just last year identified hundreds of AI-driven accounts posting sexualized content with millions of followers, and that number has almost certainly grown. As AI tools become more accessible and cheaper, more creators—amateur or otherwise—will jump on the bandwagon. Without stronger cultural pushback or platform accountability, this trend will keep expanding, flooding the internet with content that’s not just unrealistic but actively harmful.
Looking ahead, what’s your forecast for the trajectory of AI-generated content and its societal impact?
I see a dual path. On one hand, AI content creation will keep advancing, becoming even more seamless and pervasive. Without intervention, we risk a digital landscape where reality is nearly impossible to discern, and harmful narratives—like sexism or misinformation—dominate because they’re profitable. On the other hand, there’s potential for better tools to detect and label AI content, alongside stronger ethical guidelines for developers and creators. But this hinges on collective action—governments, platforms, and users all have a role. I’m cautiously hopeful, but we’re at a critical juncture where social and cultural shifts will determine whether AI amplifies harm or becomes a force for good.
