Initiative #4a: Define, and then develop, public health data science & data equity resources, in collaboration with others across Yale​

• Create one-year task force to complete an inventory of existing resources
• Define and create a shared infrastructure for public health data science and AI (in data sources, data storage, data licensing and agreements, workforce, computing, and dissemination) in collaboration with others across the university​
• Evaluate and provide recommendations on how AI may enhance the implementation of other strategic priorities and areas of research focus

Initiative #4b: Strengthen public health data science, data equity, and artificial intelligence educational programming

• Enhance our MS training in public health informatics and data science​
• Enhance the quality of and access to public health data science and AI training across the MPH program​
• Enhance pipeline and continuing educational opportunities, especially regarding AI (e.g., R25s; public health workforce trainings; hands on interactive workshops on using AI tools)​

Initiative #4c: Serve as leaders on society-wide strategies to enhance health data privacy, security, ethics, and equity

• Create robust partnerships with others across Yale working on health data privacy, security, ethics, and equity​
• Convene leaders in AI, data privacy and security to advance health-related knowledge and practice
• Define and develop the methodology for novel interfaces for equitable AI-based health analyses
• (see also: 3c, strategic priority 5)

Initiative #4d: Create robust domestic and international community partnerships on public health data science and artificial intelligence

• Support US-based community-participatory approaches to understand barriers to, then engage individuals and communities in, equitable health data collection and analysis​
• Forge new partnerships with industry and national labs to leverage current state-of-the-art computational and technological progress towards positive health impact
• Launch new data partnerships and maintain/grow existing data partnerships with international partners
• Identify and pilot non-traditional health data sources​ to enhance equity and representativeness of systems solutions