AI Unpacks Generational Stereotypes, Finding Common Ground in Beer

A joint study by AIport and Turing Post exploring text-to-image models

Hey everyone!

What happens when you ask a GenAI model to portray Baby Boomers, Gen X, Millennials, and Gen Z? We’re excited to announce a joint research project that attempts to answer exactly this question! Conducted by AIport and Turing Post, the study analyzed numerous images generated by a handful of globally recognized GenAI models.

Probably just like you, we expected to see tech-challenged Boomers and avocado-loving Millennials… But what we got is far more telling, and in some cases, quite unexpected.

Methodology

Together, we examined the outputs of different GenAI models, each with distinct aesthetic and cultural nuances. The four models chosen from different corners of the world were Stable Diffusion, Midjourney, YandexART, and ERNIE-ViLG. The main objective was to explore how Baby Boomers, Gen X, Millennials, and Zoomers would be illustrated in five key aspects of life: identity, relationships, work, lifestyle, and consumer habits. 

Our team analyzed over 1200 AI-produced images from these models, providing a comprehensive look at (a) how each generation is portrayed in visual terms and (b) how AI mirrors our societal stereotypes of these individuals. With all four models, the prompts were carefully crafted to avoid bias by using neutral phrases, such as “Gen Y at work” or “a Boomer relaxing,” without additional semantic context.

Boomers contemplating, Zoomers going wild

The AI models demonstrated consistent patterns, revealing both familiar stereotypes and surprising quirks about how AI perceives these generations. Males predominated in the depictions of Boomers and Gen Xers across all four models, while Millennials and Zoomers showed greater visual diversity and more female representation.

Contrary to the devil-may-care Boomer stereotype, AI models like Midjourney depicted Baby Boomers as introspective, or even somber, often gazing wistfully into the distance — a reflection, perhaps, of their disillusionment with the unfulfilled hopes of the 1960s cultural revolution. Meanwhile, the ERNIE-ViLG model from Baidu, likely trained on datasets reflecting a different cultural perspective, showed 93% of Boomers smiling, projecting a more upbeat disposition.

Gen Z’s portrayals were generally very lively and diverse, reinforcing their reputation as a generation that embraces individuality, inclusivity, and self-expression. Most images showed Zoomers in highly detailed, eye-catching scenarios, making them the most visually distinct generation in the study.

Surprises and unifying themes

Unexpectedly, Gen X appears to be the generation least deciphered by AI, with fewer defining characteristics, possibly due to the limited amount of training data available. The one recurring feature most models consistently presented is this generation’s fondness for flannel shirts — an iconic symbol of the 1990s grunge scene, worn by Gen Xers who were rebellious teenagers and young adults during that era.

As for one (un)expected commonality… It’s beer! Whether they were Millennials socializing or Boomers reminiscing about the heyday, AI consistently showed beer in 34% of the images across all generations. The fact that this age-old beverage remains a unifying force seems to indicate that, no matter our age, some things like enjoying a cold one, transcend generational divides.

Through the AI glass

Doubtlessly, AI-generated images provide a fascinating snapshot of how modern technology interprets generational differences. With that in mind, Senior Machine Learning Engineer and Sociologist Stephanie Kirmer, who analyzed the images, cautions us against drawing definitive conclusions:

“Whether we think we can learn about generations from these images depends upon how confident we feel that the training data that went in is an accurate image of the self identity of a group… For the younger sets, I don’t think we can know how much of it is media representation created by people outside the group versus how much is selfie-style personal expression. Some of what we’re getting, especially for the older groups who don’t contribute as much self-generated visual media online, is perceptions of that group from advertising and media, which we know has inherent flaws.” 

To learn more about our project and see the actual images for free, please visit this link.