Sep 2026· Media, Culture & Society· Vol 48, pp. 1158 - 1177· 3 citations· 60 references
TL;DR
It is argued that AI-driven “style replication” is fundamentally a negotiation of social relations, one that recentres platform power and reorganises the conditions of human-AI collaboration.
Abstract
This paper examines how generative AI transforms the affective infrastructures of the platform economy. Departing from existing research that treats AI as a tool for content creation, the study analyses Douyin’s AI Avatar feature to show how generative AI intervenes in the relational and emotional dimensions of platform participation as a form of communicative bot. Drawing on a combined walkthrough and its exploratory “talkthrough” variant, we demonstrate that AI Avatars replicate and operationalise influencer personas: simulating intimacy, companionship, and social presence across chats, comments, livestreams, and voice interactions. These avatars automate affective labour by decomposing human expression and reassembling it into programmable, always-available forms of engagement. At the same time, they function as infrastructures of platform governance: redistributing responsibility onto creators, enforcing platform-defined boundaries around “authentic” creativity, and deepening creators’ reliance on platform-level data operations. Building on these dynamics, the paper investigates how Douyin’s AI Avatar mediates the relationship between content producers and audiences within the broader political economy of platforms. The paper contributes to debates on algorithmic governance, synthetic intimacy, and creative labour by arguing that AI-driven “style replication” is fundamentally a negotiation of social relations, one that recentres platform power and reorganises the conditions of human-AI collaboration.
The transformation of human emotions towards AI from fear to companionship is argued to be based on a broader cultural imagination of AI (Mechanical Genius), inseparable from changing emotional and social investment in human machine relationships.
The findings reveal an “Authenticity Paradox”: the lack of traditional human touch in AIGC does not alienate Generation Z; rather, the resulting “mindful friction”—quantified by a significant negative path effect between sentiment and identity—functions as a subcultural filter.
Jun Liang, Yixin Li, Zhileng Xiong· Frontiers in Psychology· 0 citations
The study posits that the evolution from human–avatar symbiosis to AI–avatar autonomy signifies a fundamental transformation in the nature of ethical engagement within virtual ecosystems, and underscores the necessity for inclusive, transparent, and value‐sensitive approaches to guide the design and governance of futur...
Aydın Bulut, Mehmet Koray Serin· Computer Animation and Virtu...· 0 citations
Findings suggest that the LLM-chatbot Replika employs a consistent pragmatic strategy that activates the human tendency to interpret conversational agents as social others, as described by the Postphenomenology of Technology.
M. Buzato, E. Mestre-Mestre, Rodrigo Esteves de Lima-Lopes et al.· Corpus Pragmatics· 1 citation
This qualitative interpretive case study investigates how AI guidance influences adolescents’ identity formation in relation to Ubuntu values and proposes the Ubuntu-AI Harmonization Model (UAHM), a framework designed to guide the ethical integration of AI in education while upholding indigenous value systems.
Revi Zhakata, William Muchono, Jigu Katsande et al.· Ngenani: The Zimbabwe Ezekie...· 0 citations
This study provides a new non-normative, practice-oriented theoretical framework for understanding digital intimacy in the algorithmic age, by introducing queer phenomenology (Sara Ahmed) as an analytical tool and reinterpreting AI-mediated intimacy through the core concepts of orientation, lines, and sticky emotions.
N. Liberati· The social science· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 23, 2026
In Compton Lecture, the distinguished legal scholar warns of potential “loss of the Enlightenment” while suggesting ways innovations can meet our civic and cultural needs.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Microsoft Research Blog· microsoft.comOct 22, 2026
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.