Knowledge Resource
Research Summary: Misgendering as Breakdown in Human-Machine Communication: How AI Companion Chatbot Users Experience and Repair Misgendering
- Original authors
- Attribution requires verification
- Original source
- arXiv — Computers and Society
- Summary & Analysis prepared by
- Aziz Shuaib Ausi
- Resource type
- Research Summary / Knowledge Resource
- Resource published on AZIZ OS
- 17 September 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
About this Summary & Analysis
AZIZ OS provides independently prepared summaries and analytical interpretations of externally published research and knowledge sources. The underlying works remain attributable to their original authors and rights holders. This resource is intended to improve accessibility and understanding and does not replace the original publication.
Research from arXiv investigates the phenomenon of misgendering within AI companion and role-play chatbots, which are increasingly popular for emotional support and digital role-play. The study, based on an analysis of 326 social media posts, documents how misgendering occurs and how users attempt to correct it, highlighting a significant breakdown in human-machine communication.
Why it matters
This research reveals critical human-machine interaction failures that can undermine user trust and experience with AI systems. Addressing inherent biases in AI, particularly regarding gender and identity, is crucial for the ethical development and broader acceptance of these technologies across various applications and user demographics.
Key insights
- AI companion and role-play chatbots are gaining popularity for emotional support and digital role-play activities.
- Previous research indicates that digital role-play can facilitate exploration of gender and sexuality.
- Large Language Model (LLM) based technologies, which underpin these chatbots, contain inherent biases related to gender and sexuality.
- Misgendering by AI chatbots is identified as a potential source of harm for users.
- Users actively engage in efforts to correct or 'curate' their chatbot's understanding in response to misgendering incidents.
Source
arXiv — Computers and Society — https://arxiv.org/abs/2609.18186
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- Verification ID
- ASA-EXE-2026-00667
- Version
- v1.0 · r0
- Issued
- 17 September 2026
- Resource prepared by
- Aziz Shuaib Ausi
- Resource status
- Research Summary / Knowledge Resource
- Underlying work
- Misgendering as Breakdown in Human-Machine Communication: How AI Companion Chatbot Users Experience and Repair Misgendering
- Original authors
- Attribution requires verification
- Original source
- arXiv — Computers and Society
- Provenance status
- Attribution requires verification
- Rights
- Underlying publication rights remain with the respective copyright holder(s). Refer to the original source for authoritative publication and licensing information.
This verification confirms the AZIZ OS resource record and its documented provenance. It does not establish authorship of the underlying external work.