Indigenous Knowledge, Traditional Practices, and the Implementation of Artificial Intelligence in Social Work Practices in Africa

Traditional practices in social work have always been rooted in indigenous knowledge, which plays a crucial role in addressing community needs in African societies. The objective of this study was to harmonize Indigenous Knowledge with artificial intelligence (AI), preserve cultural values, improve social interventions, promote inclusivity, and develop context-relevant, ethical, and sustainable solutions for African communities. Indigenous knowledge is based on centuries of cultural wisdom and includes practices that are deeply embedded in local traditions and values. Social workers have long relied on these practices to navigate complex social issues, focusing on holistic and community-centered approaches. With the advent of AI, there is potential to enhance social work practices. AI can assist with data analysis, decision-making, and providing more personalized care. However, implementing AI in social work, especially in Africa, presents challenges. There is a need to balance modern technology with traditional practices to ensure cultural relevance and maintain human connection in service delivery. Incorporating AI into socialwork in Africa may face resistance due to concerns over its compatibility with indigenous knowledge and practices. Additionally, limited resources, training, and infrastructure can impede AI integration. A more inclusive approach is essential to harmonize indigenous wisdom with technological advancements in social work across the continent. The study concluded that indigenous knowledge enriches social work, but AI's integration faces challenges in maintaining traditional practices while ensuring cultural relevance in Africa. The study recommended, among other things, that traditional practices in social work should be respected for their cultural value and used to promote community well-being through understanding and engagement with local customs and beliefs.