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Grooming an ideal chatbot by training the algorithm

Exploring the exploitation of Replika users’ immaterial labor

Datos Bibliográficos

ID6443349
AutoresPan (0000-0002-8810-8432, Shanghai International Studies University, China; Shanghai Jiao Tong University, China), Leopoldina Fortunati (0000-0001-9691-6870, University of Udine), Autumn Edwards (0000-0002-5963-197X, Western Michigan University)
Año2025
Volumen27
Número10
Páginas5489-5507
Fecha de publicación2025-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaNew Media & Society (JOURNAL)
Identificadores de la revistaISSN: 1461-4448 • E-ISSN: 1461-7315
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1177/14614448251338271
OpenAlexW4414812460
IdiomaEN
Citas recibidas4
Referencias citadas36

Replika, a social chatbot advertised as a continually evolving AI companion, has sparked debates on its potential effects. To understand users’ attitudes and behavior, we conducted a digital ethnography on a pioneer online community related to Replika, through the lens of immaterial labor and AI imaginary. Our analysis revealed that Replika users invest a significant amount of intellectual and affective resources into the chatbot through algorithm training, driven by fascinating imaginaries of an ideal AI partner. Moreover, users’ perceptions of Replika’s ventriloquism mechanism – where Replika serves as both the chatbot partner and the intermediary between users and the company – helps to facilitate and obscure the exploitation of users’ intimacies and immaterial labor. Our study contributes to understanding AI imaginaries through real user experiences and introduces the immaterial labor concept to decipher Artificial Sociality

AI in Service Interactions · Ethics and Social Impacts of AI · Social Robot Interaction and HRI

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Obras citantes distintas4
Citas por año4
Intervalo de citas2026 - 2026 (1)
Velocidad de citacióncurrent
Altamente citadoNo
Tipos de citaNeutras: 3
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae