Building bridges between public health and computer science departments in academia to foster artificial intelligence knowledge and skills for the digital age.

The current communication gap between Public Health (PH) and Computer Science (CS) academics is striking: public health professionals speak in terms of incidence rates, risk factors, interventions, health systems, health policy, and equity, while computer scientists converse in neural networks, optimization functions, scalability, and computational complexity. This linguistic and cultural divide often prevents natural collaboration, leaving valuable opportunities unexplored. In this Artificial Intelligence (AI) era, regardless of whether they are in high-, middle-, or low-income countries, these two departments stand to gain immensely from forging a simple yet powerful bridge between themselves. Connecting through joint seminars, cross-listed courses, shared research projects, co-mentorship of students, and informal faculty and staff exchanges offers clear, immediate advantages: accelerated innovation in AI applications for public health challenges, enhanced employability for graduates entering a job market hungry for "AI-savvy" health professionals, and the cultivation of ethical, context-aware AI solutions that truly serve populations rather than merely advancing technology. Yet overcoming institutional barriers such as siloed budgets, geographical barriers (different buildings, districts, or campuses), differing promotion criteria, or scheduling conflicts and cultural ones, such as mutual unfamiliarity with each other's priorities, demands deliberate but feasible strategic planning. This perspective article articulates these benefits and challenges and then concludes with a set of strategies, proposed by a group of public health, health, and computer science academics, to break this divide and build a bridge between PH and CS.