This chapter presents an analysis of the future trajectory of artificial intelligence (AI) in public health. It outlines the urgent and long-term challenges, such as diagnostic bias and global AI governance. The chapter provides a vision of the transformative opportunities, such as democratizing access to health knowledge (key to health equity) and public health as a “data-rich” field (Matthew effects). The chapter emphasizes commitment to ethical AI governance and a rethinking of public health education and systems reform.

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Challenges and Opportunities in the Future

  • Min Wu

摘要

This chapter presents an analysis of the future trajectory of artificial intelligence (AI) in public health. It outlines the urgent and long-term challenges, such as diagnostic bias and global AI governance. The chapter provides a vision of the transformative opportunities, such as democratizing access to health knowledge (key to health equity) and public health as a “data-rich” field (Matthew effects). The chapter emphasizes commitment to ethical AI governance and a rethinking of public health education and systems reform.