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Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing

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Mitigating Stigma and Fostering Support: Improving AI-Generated Counterspeech for Microaggressions.

Hyeyoung Ryu¹, Sungha Kang¹, Wanda Pratt¹

¹The Information School, University of Washington, Seattle, WA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|February 23, 2026

Summary

Generative AI tools show limitations in addressing microaggressions related to sexual and reproductive health (SRH) stigma. AI must be improved to offer culturally sensitive counterspeech, avoiding harm and supporting individuals seeking care.

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Area of Science:

Digital Health
Artificial Intelligence in Healthcare
Sexual and Reproductive Health

Background:

Societal stigma surrounding sexual and reproductive health (SRH) deters women from seeking necessary care.
Cultural norms in South Korea specifically discourage unmarried women from accessing SRH services.
Online platforms, while offering support, can inadvertently perpetuate stigma through microaggressions.

Purpose of the Study:

To examine generative artificial intelligence (AI) tools, specifically ChatGPT-4 and Copilot GPT-4, in their capacity for counterspeech against SRH-related microaggressions.
To analyze AI-generated counterspeech strategies, their alignment with recommended approaches, and potential harms.
To propose improvements for AI to deliver more effective and culturally sensitive counterspeech.

Main Methods:

Analysis of counterspeech generated by ChatGPT-4 and Copilot GPT-4 in response to simulated microaggressions.
Evaluation of AI strategies against established counterspeech principles.
Identification of limitations and potential harms in AI-driven counterspeech.

Main Results:

AI tools demonstrated critical limitations, including failure to recognize implicit biases and stereotypes.
AI placed the burden of addressing microaggressions on the user, offering only superficial empathy.
Current AI counterspeech strategies are insufficient for effectively mitigating stigma in SRH contexts.

Conclusions:

Generative AI requires significant improvements to provide effective and culturally sensitive counterspeech for stigmatized healthcare.
AI must be developed to avoid perpetuating harm and to better support individuals facing microaggressions.
Enhanced AI could contribute to creating safer online spaces for SRH support.