AIFHC

The AI and Future of Health Committee (AIFHC) aims to explore and realize the potential of Artificial Intelligence (AI) in healthcare. This committee is focused on leveraging AI technologies to tackle issues related to anti-blackness, racism, ethics, and bias in all facets of health.

Our work is inspired by the "curb effect," which illustrates that interventions designed for marginalized groups are shown to benefit broader populations. Using California as a case study, disparities in health outcomes for Black Americans are examined, highlighting social and economic factors, as well as biases within the healthcare system.

The research questions focus on cancer diagnosis indicators and the impact of three bias mitigation strategies. Methodologically, the study employs data analysis, predictive AI modeling, and the aforementioned bias mitigation strategies, including standardizing electronic health records, providing educational community engagement, and developing culturally adept virtual health assistants.

The predictive modeling portion of our research aims to leverage cutting edge AI to improve healthcare outcomes for all people through discovering new information that can eventually support preventative care. By incorporating an intervention approach as well, we aim to make an impact based on the data and research readily available to us today while we pursue the more ambitious predictive modeling goal.