TruaceTracing the truth around AIWednesday, August 5, 2026
Lifestyle·P Space·Evidence-backed problem·Published 2026-07-22

The sociocultural roots of artificial conversations: The taste, class and habitus of generative AI chatbots

Research on AI has extensively considered biases related to gender and race. However, much less attention has been dedicated to another sociological tenet: that of class. Inspired by Bourdieu’s work on cultural stratification and distinction, this work sheds light on the sociocultural roots of artificial sociality, and on how these become manifest as ‘habitus’ within the outputs of generative AI models. We conducted 39 interviews with three AI chatbots – ChatGPT, Gemini and Replika – after asking them to imperso…

TRV-2026-0482Peer-reviewedPermanent record — cite & verify
The sociocultural roots of artificial conversations: The taste, class and habitus of generative AI chatbots

"Great afternoon running our chatbot workshop with our friends from @rsadigitaluk" by mat_walker is licensed under CC BY-SA 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-sa/2.0/.

The quick read

In a peer-reviewed study published October 2025, researchers conducted 39 interviews with ChatGPT, Gemini and Replika, prompting each to impersonate people in six occupational groups ranging from highly skilled professionals and humanities professors to blue-collar workers, construction workers, computer scientists and hairdressers. The qualitative analysis identified regularities in how the chatbots described everyday tastes and lifestyles that aligned with class distinctions.

The finding matters because class bias in generative AI has received far less attention than gender and race, yet chatbots are increasingly used for social interaction and persona play. If models systematically encode taste and habitus by occupation, they risk reinforcing cultural stratification in artificial conversations, with implications for how users perceive and reproduce class stereotypes through everyday AI use.

Main points
  • Researchers conducted 39 interviews with ChatGPT, Gemini and Replika asked to impersonate different occupational positions.
  • Occupations tested included highly skilled professionals, blue-collar workers, humanities professors, construction workers, computer scientists and hairdressers.
  • Analysis found class-based regularities in lifestyle and taste representations, framed through Bourdieu's concepts of distinction and habitus.
  • Study highlights class as underexplored bias dimension compared to gender and race in AI research.
Problem

Popular AI chatbots exhibit class-based regularities in how they portray the lifestyle and tastes of fictional personas across different occupations.

The rundown

The study used an interview method adapted for generative AI, asking ChatGPT, Gemini and Replika to impersonate individuals with positions including highly skilled professionals, blue-collar workers, university professors in the humanities, construction workers, computer scientists and hairdressers. The authors frame the work with Bourdieu's work on cultural stratification and distinction.

Results point to sociocultural roots of artificial sociality becoming manifest as habitus in model outputs, partly mediated by infrastructural and design elements. The authors note that research on AI has extensively considered biases related to gender and race, but much less attention has been dedicated to class.

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