Artificial Intelligence
September 28, 2026
Artificial intelligence and the trends
Why are so many people joining in on the ChatGPT fun?
I was never the person for trends. I still am not. Some pass by my timeline, I see them, I find them interesting but not to the point of trying them out. This was the case, inclusive, with some recent waves of images made by artificial intelligence, like the 80s trend, the one that showed us older, or the one that showed our adult children.
But Barbie got me. I asked ChatGPT to create a version of myself inside a personalized package, with objects, people, and references related to me. And so it did.
Why did I decide to join this trend? I kept asking myself this and couldn’t attribute a single reason. I wanted to see how it would look, I was also curious about the result, I wanted to try the technology and I found the possibility of recognizing myself in that representation fun.
After it was ready, the image provoked another curiosity, now professional: why do so many people want to put themselves within the same trend? Especially those created by ChatGPT? The answer seems to be less about a single trigger and more about the combination of several factors.
When identity itself enters the prompt
Social networks have always been spaces for self-representation. We choose photography, biography, topics we talk about, and aspects of life we wish to make public. Researchers have been studying for years how these digital representations participate in the construction and perception of identity. A review by Walther and Lew (2022) shows, for example, that digital technologies allow for experimenting with alternative self-presentations and that these experiences can relate to how we perceive the “self”.
In the AI trends, this process gains a particular characteristic. To create my Barbie, I didn’t just choose a photograph. I provided profession, interests, values, affective relationships, and important objects to me. The AI reorganized this information and returned a visual representation to me. I went a bit beyond the standard prompt that asks the AI to create the image based on what it knows.
Therefore, perhaps part of the fascination lies precisely in seeing one’s own identity reinterpreted by a technology. We do not simply receive a ready-made image. We participate in the choice of what should represent us.
Being part and remaining unique
There is also a very interesting apparent contradiction: thousands of people use the same aesthetics, but want the result to be individual. This is very curious and is supported by studies on participatory culture and mimetic behavior on platforms. Diana and David Zulli (2022) show that digital environments favor imitation, repetition, and adaptation of formats, forming what they call imitation publics: groups that are also constituted by participation in shared practices.
A trend works precisely because it can be recognized. There is a kind of collective code: now we are cartoon characters, then action figures, versions from another era, or customized Barbies. Participating means temporarily entering this conversation. And that’s where the fun is.
But repetition does not eliminate individualization. Each person modifies the model to say something about themselves. In this sense, the trend combines two well-known social needs: belonging and differentiating oneself.
A syndrome known as FOMO, an acronym for Fear of Missing Out, or the fear of being left out of what other people are experiencing or following, can also help interpret part of this behavior, but with caution.
A meta-analysis by Fioravanti et al. (2021), which gathered 33 samples and over 21,000 participants, found a consistent association between FOMO and greater social media use, including in patterns of problematic use.
The study did not investigate artificial intelligence trends, therefore it does not allow us to say that someone creates their Barbie out of fear of being left out. What it does offer is a more general clue: in digital social environments, following what other people are doing and realizing that an experience is widely circulating can increase the motivation to participate as well.
From spectator to co-creator
Artificial intelligence adds another component: it lowers the technical barrier to participate in creation. Previously, transforming a photograph into a sophisticated illustration would require mastery of software, artistic skill, or hiring someone. With generative AI, a person describes what they want, receives a first version, corrects it, adds features, swaps objects, and asks for new attempts. The process takes on a co-creation dynamic.
It is an important difference compared to simply sharing a meme. In the Barbie trend, I provide the raw material, choose what goes in, evaluate the result, and ask for changes. Even without knowing how to draw a package or produce a digital illustration, I can participate in the construction of that image.
This accessibility helps explain the speed with which certain formats spread. When the execution barrier falls, many more people can experiment.
Curiosity, novelty and the desire to show
There is also the pleasure of discovery: “I want to see what AI will do with me” and, immediately after, the experience that does not necessarily end when the image appears on the screen. There is a second stage: showing it.
On social media, self-representation also occurs in front of an audience. Likes, comments, and replies function as forms of social feedback, and studies relate active interaction on platforms to opportunities for expression and social validation. Thus, publishing one’s own version of a trend also opens up space for comparison, conversation, and recognition: “it looks just like you,” “I want to do that too,” “look what the AI put on mine.”
It would be excessive to claim that the search for likes explains these trends. But it would be equally limited to ignore that they are produced to circulate socially, and not just to remain in the personal archive of those who created them. Perhaps we are experiencing new ways of representing ourselves.
One of the things that interests me most about these trends is that highly sophisticated technology is being used for a profoundly human practice: experimenting with ways of saying who we are and observing how others respond to them.
Generative AI has added a new possibility to this behavior. It allows each person to enter a collective aesthetic, bringing with them particular elements of their own history. We are simultaneously participants in a trend and characters within it.
Perhaps this is why so many of these images manage to spread so quickly. There is the technological novelty, curiosity about the result, the pleasure of creating, participation in a collective behavior, and the possibility of showing a singular version of oneself within a language that everyone recognizes.
I entered the trend to find out what my Barbie would be like, but the experience led me to a broader question about digital behavior. These images seem to bring together practices we already know from social media and that I mentioned above: self-representation, collective participation, the search for recognition and experimentation, with a relatively new possibility, which is asking a technology to produce a version of ourselves from the information we provide. Perhaps it is precisely this combination that makes these trends so attractive.
At the same time that we repeat an aesthetic shared by thousands of people, we use AI to negotiate what we want to highlight about ourselves and then submit this representation to the gaze of others. Technology changes, but the need to build, experiment with, and share identities remains present. What generative AI adds is a new tool to carry out this process.
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