AI for Child Safety: Enhancing Protection Mechanisms in Kenya

Background

Child protection in Kenya faces significant challenges, including widespread child labor, trafficking, and abuse. Socio-economic factors such as drought-induced educational disruptions increase children’s vulnerability. In 2023, 29% of children aged 5-17 were out of school, with over half of households in regions like West Pokot and Marsabit involving children in labor activities for up to 10 hours daily. Alarmingly, 23% of girls and 12% of boys aged 13-17 have experienced sexual abuse. These issues highlight the urgent need for improved reporting, response, and support systems to safeguard children from exploitation and violence.

Objective

The project’s primary goal was to strengthen Kenya’s child protection mechanisms by leveraging AI and collaborative research. This involved identifying gaps in current practices, enhancing reporting mechanisms, improving response services, and developing comprehensive support systems for violence survivors.

Approach

The project employed a multi-phase strategy:

1. Literature Review: Comprehensive analysis of existing child protection frameworks in Kenya to establish a foundational understanding.
2. Data Analysis: Identification of gaps and challenges in current child protection mechanisms through rigorous analysis.
3. Collaboration: Partnering with Omdena and Save the Children (STC) to collect data and conduct surveys for enriched insights.
4. Global Insights: Exploration of AI applications in child protection worldwide to inform innovative local solutions.
5. Solution Development: Tailoring AI-driven solutions to address Kenya’s unique child protection needs.

Results and Impact

The project delivered a detailed report outlining Kenya’s child protection landscape and proposed AI-based innovations. Key outcomes included:

• Identification of critical gaps in reporting, response, and support mechanisms.
• Development of AI models for predictive analysis and efficient resource allocation.
• Insights that informed new policy recommendations to enhance child protection frameworks.
• Broader awareness and advocacy for the integration of AI into child protection initiatives, ensuring the safeguarding of vulnerable populations.

Future Implications

The findings from this project can significantly influence policy development and future research in child protection. By integrating AI into existing systems, Kenya can create more robust, efficient, and scalable mechanisms. The insights and innovations generated here could also serve as a model for other regions facing similar challenges, fostering global progress in child safety and welfare.