Machine Learning Analysis of Algorithmic Influence on Economic and Social Dynamics in the Elderly Population of the Philippines: A Pilot Study

This pilot study explores how machine learning algorithms affect Philippine elderly population's economic and social activities. AI-driven technology for financial planning, healthcare, and social engagement is needed as the older population grows. K-Nearest Neighbors, Decision Tree, Support Vector Machine, and Logistic Regression are used to analyze 153 elderly survey participants from urban and rural locations. To address the digital gap and impediments to the elderly, it analyzed income distribution, employment status, AI technology accessibility, and views of AI's influence on social interaction. The findings suggest AI might improve elderly health care and financial stability. Access is unequal, particularly in rural regions, and job displacement, privacy, and social isolation remain concerns. SVM predicted AI acceptance best. The paper improves senior digital literacy and designs AI tools for them. Policymakers should address these ethical issues as AI becomes more important in this demographic and provide fair access to AI-driven services for inclusive economic and social progress.