PreprintCC BY 4.0PsyArXiv
When AI becomes social: the promise and risks of AI companions for mental health – a social brain perspective
Abstract
AI companions are emerging as psychosocial technologies that may reshape social connection and mental health, while also creating risks of emotional dependence. Here, we propose a social-brain framework explaining how attachment, reward, and emotion regulation systems may shape human–AI bonding. This framework highlights the importance of understanding how AI companionship may reshape social connection and mental health, suggests an overarching model that accounts for the complex interplay between the human interface, technology design and context, and provides insights for the responsible design of future AI systems.
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BibTeX
@misc{becker2026when,
title = {{When AI becomes social: the promise and risks of AI companions for mental health – a social brain perspective}},
author = {Benjamin Becker and Nan Qiu and Christian Montag},
howpublished = {PsyArXiv},
year = {2026},
month = nov,
doi = {10.31234/osf.io/n25bc_v1},
url = {https://osf.io/preprints/psyarxiv/n25bc_v1/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - When AI becomes social: the promise and risks of AI companions for mental health – a social brain perspective
AU - Benjamin Becker
AU - Nan Qiu
AU - Christian Montag
PY - 2026
DA - 2026/11/02
PB - PsyArXiv
DO - 10.31234/osf.io/n25bc_v1
UR - https://osf.io/preprints/psyarxiv/n25bc_v1/
AB - AI companions are emerging as psychosocial technologies that may reshape social connection and mental health, while also creating risks of emotional dependence. Here, we propose a social-brain framework explaining how attachment, reward, and emotion regulation systems may shape human–AI bonding. This framework highlights the importance of understanding how AI companionship may reshape social connection and mental health, suggests an overarching model that accounts for the complex interplay between the human interface, technology design and context, and provides insights for the responsible design of future AI systems.
ER -