AI and Machine Learning in Pandemic Surveillance: Ethics and Security Implications

Artificial Intelligence (AI) and Machine Learning (ML) technologies have gained immense popularity in forecasting outbreaks, tracking their spread, and suggesting possible policies concerning COVID-19, much more than they were used to show intellectual merit. Real-time information on mobility patterns, electronic health records, and social media trends was analyzed along a fast data response line for the purpose of hotspot identification, behavior tracking, and resource allocation optimization by these technologies. Nevertheless, their rapid uptake also raised urgent ethical and security concerns. Issues like unfair treatment by algorithms, not getting permission to use personal data, and problems with privacy and excessive monitoring showed serious risks to people's rights and the fairness of using AI/ML tools during health emergencies. The paper examines the twin edge of AI/ML in pandemic surveillance, providing a review of applications in the real world, dissecting prominent ethical dilemmas, and exposing vulnerabilities in data-governance frameworks. With data collected through empirical research and current case studies, we highlight both the strengths and the weaknesses of these technologies with respect to enhancing public health responses. The findings reveal that ML models have improved the accuracy of outbreak predictions and resource planning; however, a fair number of inequities remain with which populations are surveilled, categorized, and treated. The study also assesses how the concentration of health data, coupled with limited regulatory oversight, magnifies the risk of data breaches, misuse, and lowering public trust. The paper makes strategic recommendations, including ethics-by-design methods, algorithmic accountability, reform of the law, and models of inclusive governance. The pandemic preparedness of the future will depend not only on technological sophistication but also on embedding fairness, accountability, and human rights in AI systems. It is essential to find a proper balance between innovation and ethical stewardship to ensure that AI/ML surveillance serves the common good without infringing upon fundamental freedoms.