@inproceedings{kandala-etal-2026-vision,
title = "A Vision for Cultural Alignment: Opportunities and Safety Imperatives for {AI} in Mental Health Support",
author = "Kandala, Ratna and
Moharir, Akshata Kishore and
Manchanda, Niva and
Adorno, Samantha",
editor = "Ranaldi, Leonardo and
Pucci, Giulia and
Ranaldi, Federico and
Valentino, Marco and
Birch, Alexandra and
Zanzotto, Fabio Massimo",
booktitle = "The Proceedings of the Workshop on Open Reasoning Across Cultures Languages ({ORACLE})",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.oracle-main.36/",
pages = "534--541",
ISBN = "979-8-89176-483-5",
abstract = "As Large Language Models (LLMs) are increasingly integrated into mental health applications, the prevailing paradigm of cultural neutrality risks creating a technical debt that undermines model generalization and safety. Current systems/frameworks, while focusing on multilingual capabilities, often fail to account for the diverse social and cognitive norms of global populations.This vision paper explores the transition from culturally invariant models toward a research trajectory that operationalizes cultural dimensions such as power distance and individualism as fundamental architectural parameters. Rather than viewing cultural adaptation as a post-hoc fine-tuning task, we advocate for systems that internally encode cultural variability as a primary driver of the model{'}s reasoning process. We outline a roadmap for architecturally encoding cultural variability as a firstclass parameter in AI/ML pipelines, moving beyond surface-level translation toward systems where cultural dimensions fundamentally shape model reasoning."
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%0 Conference Proceedings
%T A Vision for Cultural Alignment: Opportunities and Safety Imperatives for AI in Mental Health Support
%A Kandala, Ratna
%A Moharir, Akshata Kishore
%A Manchanda, Niva
%A Adorno, Samantha
%Y Ranaldi, Leonardo
%Y Pucci, Giulia
%Y Ranaldi, Federico
%Y Valentino, Marco
%Y Birch, Alexandra
%Y Zanzotto, Fabio Massimo
%S The Proceedings of the Workshop on Open Reasoning Across Cultures Languages (ORACLE)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-483-5
%F kandala-etal-2026-vision
%X As Large Language Models (LLMs) are increasingly integrated into mental health applications, the prevailing paradigm of cultural neutrality risks creating a technical debt that undermines model generalization and safety. Current systems/frameworks, while focusing on multilingual capabilities, often fail to account for the diverse social and cognitive norms of global populations.This vision paper explores the transition from culturally invariant models toward a research trajectory that operationalizes cultural dimensions such as power distance and individualism as fundamental architectural parameters. Rather than viewing cultural adaptation as a post-hoc fine-tuning task, we advocate for systems that internally encode cultural variability as a primary driver of the model’s reasoning process. We outline a roadmap for architecturally encoding cultural variability as a firstclass parameter in AI/ML pipelines, moving beyond surface-level translation toward systems where cultural dimensions fundamentally shape model reasoning.
%U https://aclanthology.org/2026.oracle-main.36/
%P 534-541
Markdown (Informal)
[A Vision for Cultural Alignment: Opportunities and Safety Imperatives for AI in Mental Health Support](https://aclanthology.org/2026.oracle-main.36/) (Kandala et al., ORACLE 2026)
ACL