"Girl, I'm so Serious": CARE, a Capability Framework for Reproductive Equity in Human-AI Interaction
This addresses equity issues for marginalized groups in high-stakes AI interactions, though it is incremental as it adapts an existing capability approach to a new domain.
The paper tackles the problem of ensuring reproductive equity in AI chatbots for sexual and reproductive health by introducing the CARE framework, which identifies epistemic harms like source opacity and response rigidity in existing tools.
Sexual and reproductive health (SRH) remains shaped by structural barriers that leave many without judgment-free information. AI chatbots offer anonymous alternatives, but access alone does not ensure equity when socioeconomic determinants shape whose capabilities these tools expand or constrain. Conventional methods for evaluating human-AI interaction were not designed to capture whether technologies holistically support reproductive autonomy. We introduce CARE, Capability Approach for Reproductive Equity, developing capabilities, functionings, and conversion factors into a Normative Design Lens and an Evaluation Lens for AI in SRH contexts. Evaluating SRH-specific non-LLM chatbots, general-use LLMs, and search engine features along credibility and reasoning, we identify two epistemic harms: source opacity and response rigidity. We conclude with design and evaluation recommendations, participatory auditing strategies, and policy implications for high-stakes domains where AI intersects with inequity.