AI-Powered systematic reviews in public and occupational health: Opportunities and ethical challenges

The exponential growth of scientific literature presents significant challenges for researchers conducting systematic reviews and meta-analyses, particularly in public and occupational health. Artificial intelligence (AI) offers transformative potential to streamline these processes by expediting literature screening, enhancing data extraction, and identifying critical evidence with unprecedented efficiency. This commentary explores the opportunities presented by AI in addressing these challenges, including its ability to manage large datasets, uncover hidden associations, and support rapid evidence synthesis for policymaking and clinical practice. While the benefits of AI are substantial, its integration into systematic reviews is not without challenges. Issues such as algorithmic bias, transparency, and the need for robust human oversight remain critical concerns. The commentary highlights these ethical and technical challenges and underscores the importance of standardized guidelines and interdisciplinary collaboration to ensure reliability and quality in AI-assisted research. By addressing these challenges, AI can advance evidence-based practices in public and occupational health, fostering innovation and improving health outcomes globally.