“Todos Somos, Somos Uno: We Are All, We Are One!” ODSS Celebrates Hispanic Heritage Month

Thursday, September 28, 2023

Guest Blog written by Dr. Samson Gebreab, AIM-AHEAD Program Lead

In celebration of the history, culture, and contributions of Hispanics and Latinos, the NIH Office of Data Science Strategy (ODSS) is highlighting one of its flagship initiatives. The Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program, launched in 2021, is increasing diversity in the AI/ML workforce and building a more inclusive research community to address health disparities and advance health equity.

AIM-AHEAD’s overall mission is to bring the benefit of AI/ML to all people of diverse backgrounds, especially those who may have been left out in the AI/ML research enterprise. Many historically underserved communities, including Hispanic and Latino communities, have not been well represented in the AI/ML workforce, datasets, research, and infrastructure development. The lack of representation can contribute to AI bias, leading to inaccurate clinical outcomes that may not reflect these underserved communities' health conditions or lived experiences.

ODSS recognizes that achieving diversity in the AI/ML workforce is critical to addressing the sources of AI bias contributing to health disparities and inequities. The AIM-AHEAD initiative provides a range of training opportunities across the academic continuum to increase the representation of Hispanic, Latino, and other underrepresented researchers in the AI/ML and data science space, including:

Professional Development Program: training underrepresented healthcare professionals in AI/ML and health equity.
PRIME Training Practicum: Enhancing technical competencies in AI/ML for graduate students from minority serving institutions.
Research Fellowship Cohort 1: Engaging early-career researchers from under-represented populations in biomedical research that uses AI/ML methodologies on Electronic Health Record Data.
Leadership Fellowship Cohort 1: preparing diverse leaders to champion the use of AI/ML in addressing persistent health disparities.

These training and fellowship programs include 15 Hispanic individuals. In recognition of Hispanic Heritage Month 2023, ODSS is pleased to share some of their perspectives in the video below.

AIM-AHEAD is also committed to using AI/ML to understand and addressing the varied factors driving the health disparities of Hispanic and Latino communities, including economic and healthcare access barriers, cultural factors, and lived experiences. In particular, the AIM-AHEAD program promotes community-centered AI/ML research projects that engage, empower, and closely collaborate with Hispanic and Latino community stakeholders when tackling their health challenges and needs:

An AIM-AHEAD-supported community-entered research project is a collaboration with ROSAesROJO that makes wellness and cancer prevention accessible to Hispanic/Latina women and their families in the United States. The researchers are working with the Bi-National Center at Texas A&M University and Hospital Mexico Americano in Nuevo Laredo, Mexico, to build a trilateral relationship to collect data and run a racially unbiased AI algorithm trial for breast cancer detection in the Mobile Mammogram vans.
AIM-AHEAD researchers, in partnership with Tepeyac Community Health Center and Clinic Chat LLC, are developing an artificially intelligent chatbot to facilitate improved access to cancer screening in English and Spanish-speaking Hispanic/Latino populations in Colorado experience disparities in cancer screening, timely diagnosis, and access to treatment for several cancers in comparison to other demographic groups.

These training and community-centered pilot projects reflect a small sample of AIM-AHEAD program activities focused on Hispanic and Latino researchers and communities. During Hispanic Heritage Month and beyond, we encourage you to visit the AIM-AHEAD website to engage and learn more about how the program is leading the way to advance health equity using AI/ML by bringing together diverse datasets, researchers, and communities.

“Todos Somos, Somos Uno: We Are All, We Are One!”