Advancing Public Health through Generative Artificial Intelligence: A Focus on Digital Well-Being and the Economy of Attention

The adoption of generative artificial intelligence (AI) by users to perform everyday, work, and academic activities has fostered a global debate about the benefits and threats of AI to human health. There is a growing need to consider and address the potential consequences of widely accessible, improved, and user-friendly AI on mental health globally. Generative artificial intelligence has emerged as a powerful tool with significant potential to transform various aspects of contemporary society. In the field of global public health, its impact is particularly relevant due to the opportunities it offers to improve the efficiency, accuracy, and accessibility of mental health services. Research into the effects of generative AI on mental health from an economic and behavioral perspective is critical to fully exploit its benefits, address its challenges, and ensure that its implementation is equitable and sustainable globally.

The rapid advancement of artificial intelligence (AI) presents unprecedented opportunities to address public health challenges, particularly in mental health. This intersection of AI, public health, and economics demands rigorous research to harness its full potential. AI's capacity to process vast amounts of data can revolutionize mental health diagnostics, treatment, and resource allocation. However, its implementation raises critical questions about efficacy, cost-effectiveness, and ethical considerations.

The economy of attention, which treats human attention as a scarce resource, is especially relevant in today's digital age where mental health is increasingly affected by information overload and digital distractions. Understanding how AI can be leveraged to optimize attention allocation in health interventions is crucial. Moreover, economic principles can guide the development of sustainable AI-driven health solutions, ensuring equitable access and efficient resource utilization. Research in this field is vital to inform evidence-based policies, improve health outcomes, and navigate the complex landscape of AI in public health.

This research topic aims to examine how AI technologies, combined with economic principles, can revolutionize our approach to public health challenges, particularly in the mental health domain. We seek papers that contribute to the following broad themes (but not limited to the themes mentioned below):

• AI applications in mental health screening, diagnosis, and intervention;

• The role of the economy of attention in designing effective public health interventions;

• Economic models for optimizing resource allocation in mental health services;

• AI-powered predictive analytics for public health policymaking;

• Ethical considerations in AI-driven mental health research;

• The impact of digital attention-grabbing technologies on mental well-being;

• Cost-effectiveness analysis of AI-based mental health interventions;

• AI's potential in addressing health disparities and improving access to care

We encourage interdisciplinary approaches that combine insights from public health, computer science, economics, psychology, and related fields. Submissions should highlight the potential of AI and economic concepts to drive innovation in public health research and practice.