Role of Artificial Intelligence in Public Health

The rapid use of Artificial Intelligence (AI) in public health marks a watershed moment in public health. This technical innovation offers unparalleled opportunities in the use of public health practice to improve health outcomes, streamline service delivery, and enhance the efficiency of healthcare systems. This fusion of technology and healthcare, however, is not without its challenges. Ethical dilemmas, data privacy concerns, and the imperative for robust regulatory frameworks are the key issues ahead of AI’s rapid integration into public health. The multifaceted role of AI in public health and its potential, needs thorough examination. Moreover, a well-planned framework is essential to confront its challenges and chart a course for its future in public health. Public health is a team-based approach. Hence, public health professionals should own up to the responsibility of fostering interdisciplinary collaboration among technologists, healthcare professionals, ethicists, and policymakers. This is essential to effectively navigate the complex interplay between AI and public health.

The current surge in AI interest and application in public health signifies a critical juncture for public health professionals, challenging them to make informed decisions on AI deployment, fully understand its risks, and unlock its full potential. The transformative promise of AI in healthcare necessitates a collective endeavour among all stakeholders to develop, evaluate, and ethically deploy AI technologies, advocating for transparency and fairness in AI algorithms, and ensuring that advancements translate into evidence-based, ethically sound, and contextually relevant improvements in public health.

Processing and analyzing large datasets with speed is a powerful tool in the public health arsenal. However, the accuracy and ethical aspects of managing the data and inferences are important challenges that need resolution. Attention to detail of these concerns can be useful in piloting and scaling up the use of AI in disease surveillance, predictive modelling, and healthcare delivery, which are redefining our strategies for managing health crises, chronic diseases, and daily healthcare operations. AI-driven models can be instrumental in forecasting disease outbreaks, improving precision in screening algorithms, and customizing continuity of care, which are all key enhancements in strengthening preventive healthcare and early intervention strategies. Yet, human actions cannot be replaced. If anything, AI is a strong tool to strengthen the timely response of rapid response teams and ready-to-use dashboards and analytics, strengthening the implementation of public health programs.

The deployment of AI in public health is not devoid of challenges. Concerns over data privacy and security are discussed in the literature. The misuse of AI-based algorithms can also lead to exacerbating health disparities through biased algorithms. The path to fully leveraging AI in public health demands the establishment of comprehensive regulatory frameworks that ensure the safety, ethical integrity, and efficacy of AI applications. This involves crafting standards for data quality, algorithmic transparency, and accountability.

As AI reshapes the healthcare landscape, it beckons us to reevaluate our approach to public health challenges. Standing at the precipice of the AI revolution, it is imperative to responsibly seize the opportunity to enhance public health outcomes, diminish health disparities, and propel the global health agenda forward. Investing in education and training programs for healthcare professionals to adeptly work alongside AI technologies will bridge the gap between technological innovation and practical healthcare application, maximizing the potential of AI tools. By embracing collaboration, establishing stringent regulatory frameworks, and prioritizing education, we can harness AI’s power to conceive a healthier, more equitable future for all, heralding a new era of innovation and improved health worldwide.

The AI application utilized for screening and monitoring anemia by the Government of Telangana has demonstrated promising results. Traditionally, hemoglobinometers have been employed for anemia screening, but they are costly, invasive, and generate biomedical waste that requires proper disposal. Additionally, trained personnel are necessary for their operation. Hence, there exists a pressing need for a non-invasive screening method.

The AI application serves as a non-invasive tool with high accuracy, ease of use, and scalability for mass population screening of anemia. It is poised to bring substantial benefits to maternal and child health, as well as economic advantages. The Government of Telangana has already incorporated this method into its Anemia Mukth Bharath initiative, while the Government of Karnataka is in the process of adopting it.

Acknowledgement

This is to acknowledge and appreciate the contributions of friends and postgraduates in this editorial.