In this episode of What is Public Health, Dr. Julie Cakici, a leading expert in public health, precision medicine, and the ethical implications of emerging technologies, joins us to explore how artificial intelligence (AI) is transforming healthcare.

From disease prediction and personalized medicine to tackling health disparities and improving health communication, Dr. Cakici shares insights on the opportunities and challenges of integrating AI into public health. We discuss the importance of ethical AI design, the risks of algorithmic bias, and how public health professionals can stay ahead of the curve in an AI-driven world. Tune in to discover how AI is reshaping the future of health—and how we can ensure it benefits everyone.

Here’s a quick preview of what we’ll cover:

- The most exciting ways AI is being used to improve public health outcomes, including predictive modeling and personalized medicine.

- The biggest ethical and legal challenges of integrating AI into public health—privacy risks, bias, and algorithmic transparency.

- How AI can both reduce and *exacerbate* health disparities—and what needs to be done to ensure equity.

- Why public health professionals need to adapt to an AI-driven world—and the essential skills that will be required moving forward.

- The future of AI in public health policy and governance—how we can test and regulate AI responsibly before it causes harm.

- Practical advice for public health professionals on how to engage with AI without a technical background.

To learn more about Dr. Julie Cakici:

Dr. Julie Cakici ("chuck-eh-jeh") is a registered nurse with a PhD in Public Health. Her research emphasizes the ethical, legal, and social implications (ELSI) of emerging technologies and incorporates Dissemination and Implementation Science to assess contextual factors that impact the implementation of research and interventions. Her areas of expertise include precision health research, digital health technologies, artificial intelligence (AI), privacy, secondary research, and research ethics.

Most recently, she worked as a contractor for the NIH’s All of Us Research Program as a Health Science Policy Analyst in the ELSI division of the Policy Office. In this role, she informed program policies, guidance, and educational materials to promote ethical research using data from nearly 850K participants. This included evaluating the use of AI for programmatic support. Prior to pursuing her doctorate, Julie was the Manager of Genomics Research at Rady Children’s Institute for Genomic Medicine and a faculty member for the Children’s Mercy Bioethics Center’s Certificate in Pediatric Bioethics.

Additional Resources on AI and Public Health:

3Blue1Brown's Neural Networks Course, which also includes links to a free book that includes step-by-step instructions and code along with curated data to train a model.

Fujitsu's Social Digital Twin video

NASEM event with Dr. Gabriella Waters from NIST discussing Digital Twins for Social and Behavioral modelling

Weapons of Math Destruction, book