Surfacing and Applying Meaning: Supporting Hermeneutical Autonomy for LGBTQ+ People in Taiwan

2026-03-23

AI Summary

Following the legalization of same-sex marriage in Taiwan, LGBTQ+ individuals continue to encounter online hostility on social media, exacerbating hermeneutical injustice during identity exploration. This study addresses this challenge by integrating the concept of “hermeneutic autonomy” into AI system design through in-depth interviews and participatory design. It proposes a conversational agent grounded in retrieval-augmented generation (RAG) and large language models (LLMs), structured around four interaction modes: reflection, validation, discussion, and alliance-building. The system empowers users to reframe hostile narratives, affirm lived experiences, foster identity development, and strengthen community connections. Empirical findings demonstrate that the agent significantly reduces the cognitive and emotional labor required to navigate online antagonism, thereby supporting more resilient and affirming identity work for LGBTQ+ individuals.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Multiagent Systems: Agent Communication

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

After Taiwan's legalization of same-sex marriage in 2019, LGBTQ+ communities continue to face hostility on social media. Using the lens of hermeneutical injustice and autonomy, we examine how technological conditions affect LGBTQ+ individuals' identity exploration, narrative seeking, and community resilience. We conducted a multi-stage study with Taiwanese LGBTQ+ individuals, including in-depth interviews, participatory design workshops, and evaluation sessions. Participants described fragile yet creative strategies such as seeking validation in online interactions, reframing hostile content through theory, and relying on allies. Building on these insights, we designed and evaluated a retrieval-augmented, LLM-powered chatbot with four modes of interaction: reflection, validation, discussion, and allyship. Findings show that the system fosters hermeneutical autonomy by helping participants reframe hostile narratives, validate lived experiences, and scaffold identity exploration, while reducing the hermeneutical labor of navigating social media hostility. We conclude by outlining design implications for AI systems that advance hermeneutical autonomy through fluid self-representation, contextualized dialogue, and inclusive community participation.

Problem

• hermeneutical injustice
• LGBTQ+
• social media hostility
• identity exploration
• hermeneutical autonomy

Innovation

• hermeneutical autonomy
• retrieval-augmented LLM
• participatory design
• LGBTQ+ identity
• AI for social justice