The 2024–2025 Scientific Workforce Diversity Seminar Series kicked off with a conversation on the benefits of diverse perspectives in data science.
Panelists:
- Discussed strategies to recognize and address bias in data science, including ensuring equitable representation in research spaces and increasing diverse participation.
- Highlighted the benefits of an inclusive environment and diverse perspectives of data science researchers and data sets in this scientific field.
- Described how diverse representation enhances machine learning and artificial intelligence accuracy, particularly in the context of health sciences, such as in electronic health record data sets.
The video recording of the event will be posted soon.
Presentation Slides
Monica M. Bertagnolli, M.D.
Director, NIH
Marie A. Bernard, M.D.
Chief Officer for Scientific Workforce Diversity (COSWD), NIH
Jennifer Couch, Ph.D.
Chief, Division of Cancer Biology, National Cancer Institute, NIH
Samson Gebreab, Ph.D., MSc.
Program Lead Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD), Office of Data Science Strategy, NIH
Manu O. Platt, Ph.D.
Director, Biomedical Engineering Technology Acceleration (BETA Center) and Associate Director, Scientific Diversity, Equity and Inclusion, National Institute of Biomedical Imaging and Bioengineering, NIH