DSAIY teaches Rhode Island high school students machine learning concepts and data science skills in healthcare and medicine via a social justice lens. We aim to broaden participation in STEM through an innovative and inclusive learning ecosystem designed for evolving, interdisciplinary technologies. We are researching: how do students and teachers engage in data science and machine learning materials? How do teachers take up and enact materials? How do students engage with the learning environment and one another? We include: (1) PD to support teachers on how to use our curriculum, (2) implementation of the developed curriculum (one semester) through the differentiated lessons scaffolded on Scoutlier, (3) a Hive Learning Ecosystem meetings with topics determined by teachers to best meet their needs, (4) documentation of feedback and teacher-created resources to supplement and strengthen lessons for biannual revisions, (5) a datathon that provides an authentic workforce experience during which students team with their teachers, healthcare professionals, and data scientists to solve an authentic data based, bias-related critical care challenge. DSAIY increases students’ awareness and interest in data science, machine learning, AI, and healthcare careers, particularly for historically underrepresented populations. Quantitatively, students are more interested in careers. Qualitatively, they are excited to explore data in non-biased ways and learn about diverse healthcare caree