Source: NYU News
Photo by Jonathan King/NYU
Using real-world case studies and datasets, students in a new NYU School of Global Public Health class explore how algorithms are shaping our health
Big data and artificial intelligence are revolutionizing our health—detecting outbreaks, identifying those most at risk for diseases, and sorting through an ever-growing abundance of medical records and studies to spot patterns and improve outcomes. These technologies are also prompting questions about fairness, accuracy, and the evolving role of humans in our health systems.
A new course at the NYU School of Global Public Health is preparing the next generation of public health and data science professionals to navigate this rapidly changing landscape.
Designed and taught by Rumi Chunara, director of the NYU Center for Health Data Science, “Data, AI and the People’s Health” focuses on how data—from the earliest stages of gathering and sampling, through analysis and reporting with tools like AI—impact human health. The new course is being offered for the first time this fall, bringing together graduate students from the School of Global Public Health, Tandon School of Engineering, and the Center for Urban Science + Progress (CUSP).
"This topic is especially timely now because the amount of data that is informing AI and our health has grown dramatically,” says Chunara, an associate professor of biostatistics at NYU School of Global Public Health and of computer science and engineering at NYU Tandon School of Engineering. “We talk about data quality and how to improve it, what it means statistically, and cite research that people have done about real AI systems or products and the implications of those systems."