The sociocultural roots of artificial conversations
The taste, class and habitus of generative AI chatbots
Bibliographic Data
| ID | 6443383 |
|---|---|
| Authors | Ilir Rama (0000-0002-6032-7000, University of Milan), Massimo Airoldi (0000-0002-6639-8715, University of Milan) |
| Year | 2025 |
| Volume | 27 |
| Issue | 10 |
| Pages | 5546-5567 |
| Publication date | 2025-10-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | New Media & Society (JOURNAL) |
| Journal identifiers | ISSN: 1461-4448 • E-ISSN: 1461-7315 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/14614448251338273 |
| OpenAlex | W4414812350 |
| Language | EN |
| Citations received | 3 |
| References cited | 39 |
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 impersonate individuals with different occupational positions: highly skilled professionals, blue-collar workers, university professors in the humanities, construction workers, computer scientists and hairdressers. Our qualitative study shows class-based regularities in how popular AI chatbots represent the lifestyle and tastes of fictional personas in artificial conversations, partly mediated by infrastructural and design elements. The article proposes a sociological perspective on bias in artificial sociality and experiments with interview methods in the study of generative AI
Digital Marketing and Social Media · Sentiment Analysis and Opinion Mining · Social and Cultural Dynamics
Artificial Communication
Semantics derived automatically from language corpora contain human-like biases
Distinction
Artificial Sociality
A longitudinal study of human–chatbot relationships
Exploring relationship development with social chatbots
Langage et pouvoir symbolique
The Logic of Practice
Should ChatGPT be biased? Challenges and risks of bias in large language models
Genres, Objects, and the Contemporary Expression of Higher-Status Tastes
Artificial intelligence and the affective labour of understanding
The promise of personalisation
The walkthrough method
How offline backgrounds interact with digital capital
Liking as taste making
Human-aided artificial intelligence
Ideal technologies, ideal women
Reclaiming the human in machine cultures
More human than human
Automating Inequality
Structured like a language model
Foundation models are platform models
Modes of consumption
Machine Habitus
Taste differentiation and hierarchization within popular culture
Class and Status
Why "cultural matters" matter
Social Space and Symbolic Power
Multi-Situated App Studies
Machine Learning as a Model for Cultural Learning
Why not a Sociology of Machines? The Case of Sociology and Artificial Intelligence
A Sociological Conversation with ChatGPT about AI Ethics, Affect and Reflexivity
A New Model of Social Class? Findings from the BBC's Great British Class Survey Experiment
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |