  LGBTQ+ community face disproportionate mental health challenges, including
higher rates of depression, anxiety, and suicidal ideation. Research has shown
that LGBTQ+ people have been using large language model-based chatbots, such as
ChatGPT, for their mental health needs. Despite the potential for immediate
support and anonymity these chatbots offer, concerns regarding their capacity
to provide empathetic, accurate, and affirming responses remain. In response to
these challenges, we propose a framework for evaluating the affirmativeness of
LLMs based on principles of affirmative therapy, emphasizing the need for
attitudes, knowledge, and actions that support and validate LGBTQ+ experiences.
We propose a combination of qualitative and quantitative analyses, hoping to
establish benchmarks for "Affirmative AI," ensuring that LLM-based chatbots can
provide safe, supportive, and effective mental health support to LGBTQ+
individuals. We benchmark LLM affirmativeness not as a mental health solution
for LGBTQ+ individuals or to claim it resolves their mental health issues, as
we highlight the need to consider complex discrimination in the LGBTQ+
community when designing technological aids. Our goal is to evaluate LLMs for
LGBTQ+ mental health support since many in the community already use them,
aiming to identify potential harms of using general-purpose LLMs in this
context.
