Abstract
In India, Accredited Social Health Activists (ASHA) workers are crucial in delivering healthcare to marginalized rural communities. However, their effectiveness is hampered by challenges in accessing medical knowledge and decision-support tools. AI advancements offer potential to enhance ASHA capabilities, but cognitive biases’ impact on AI collaboration remains a concern for its adoption. This thematic discourse analysis investigates biases at the human-AI interface from a cognitive science perspective. It uncovers automation and confirmation biases, compounded by difficulties in interpreting complex AI behaviors. Through participatory design, frontline health workers can help in creating tools aligned with their needs. The proposed research, employing qualitative methods and co-design, aims to ensure cultural relevance while addressing frictions, barriers, and training gaps. It seeks to set guidelines for ethical AI integration. This approach strives for better access and dignity, prioritizing empathetic solutions over just technological implementation. The objective is to validate interventions fostering mutual understanding, essential for tackling inherent inequities in the current system.
Nimisha Karnatak
CS Ph.D. Student | Student Researcher
I conduct human-centered research in the domain of healthcare and accessibility.