This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects. 

The problem

The project targets a pressing issue in Kenya: the inadequacy of current monitoring, reporting, and intervention strategies to effectively address child protection concerns. Despite various efforts, child protection agencies face significant challenges in gathering, analyzing, and acting upon data related to child abuse cases. The complexity of these challenges is compounded by the prevalence of child labor, trafficking, and abuse within the country, situations exacerbated by socio-economic factors such as poverty and educational disruptions due to environmental crises like droughts. For instance, the 2023 Child Protection Assessment by Save the Children highlighted that 29% of children aged 5-17 are not in school, primarily due to drought, leading to increased vulnerability to exploitation. Moreover, over half of the households in regions like West Pokot and Marsabit involve children in labor to supplement family income, often for up to 10 hours daily. A 2019 survey further illuminated the grim reality of child abuse in Kenya, revealing that 23% of girls and 12% of boys aged 13-17 experienced sexual abuse, with nearly half of females and over half of males aged 18-24 having experienced violence in childhood.

The impact of these issues is profound. The lack of effective monitoring and reporting mechanisms hinders the timely identification and intervention in child abuse cases, allowing many instances to go unreported and unaddressed. This not only perpetuates the cycle of abuse but also undermines the overall well-being and development of affected children, contributing to long-term psychological and physical health issues. Furthermore, the current system’s inefficiencies impede child protection agencies’ ability to plan and allocate resources effectively, limiting their capacity to provide comprehensive support to violence survivors. The absence of a centralized, real-time data access point further complicates these challenges, making it difficult for stakeholders to obtain a holistic view of child protection issues and respond accordingly.

In response, the development of a Conversational AI Powered Child Protection Dashboard aims to revolutionize how child protection data is collected, analyzed, and utilized. By integrating an AI chatbot with a comprehensive dashboard, the project seeks to provide stakeholders with real-time updates, detailed insights into various forms of child abuse, and data on violence hotspots. This enhanced access to enriched data is expected to significantly improve decision-making, planning, and resource allocation for child protection efforts, ultimately contributing to more effective monitoring, reporting, and intervention strategies. Through this initiative, the project aspires to address the urgent need for improved child protection mechanisms in Kenya, offering a model that could potentially be replicated in other regions facing similar challenges.

The project goals

The primary aim of this project is to revolutionize child protection efforts in Kenya through the development of an AI-powered Conversational Child Protection Dashboard. This innovative initiative is designed to significantly enhance the efficiency and effectiveness of monitoring, reporting, and intervention strategies employed by child protection agencies. By leveraging advanced AI technologies and data analysis, the project seeks to provide a comprehensive solution to the challenges faced in safeguarding children from abuse and exploitation. The project will unfold in the following planned phases:

• Design and Development of the AI-Based Prototype System: The first phase involves creating a sophisticated system comprising a web scraper, an AI chatbot, and an integrated dashboard. This system is aimed at streamlining the processes involved in child protection, making them more efficient and effective.
• Data Collection and Analysis: Utilizing the web scraper, this phase focuses on gathering data from a variety of online sources, with a particular emphasis on child protection cases across Nairobi. The collected data will encompass various forms of child abuse, including physical, emotional, and sexual abuse incidents, providing a broad overview of the current situation.
• AI Chatbot for Real-Time Data Synthesis: The development of an AI chatbot represents a crucial component of the project, designed to synthesize information from the dashboard and provide stakeholders with valuable insights. This includes identifying child violence hotspots, offering detailed information on different forms of child abuse, and delivering real-time updates on cases.
• Dashboard Integration for Enhanced Data Access: This phase involves the integration of the AI chatbot with a user-friendly dashboard, ensuring real-time updates and comprehensive data on child violence cases are readily accessible. The dashboard will serve as a pivotal resource for decision-making, planning, and resource allocation, enhancing child protection efforts.
• Testing of the Prototype System: The final phase focuses on rigorously testing the prototype system to ensure its functionality and reliability. This step is critical in validating the effectiveness of the AI-powered tool in supporting child protection agencies.

Through these phases, the project aims to deliver a Minimum Viable Product that showcases the capabilities of the Conversational AI Powered Child Protection Dashboard, setting the stage for further advancements. This initiative is set to make a significant impact on child protection in Kenya, providing agencies with the tools they need to respond more effectively to child abuse cases. By introducing AI into the realm of child protection, the project aspires to foster a safer environment for children, ensuring they are protected from harm and have the opportunity to thrive.

**More details will be shared with the designated team.

Team, Hours, and Timeline: 2 ML Engineers; Part-time (20 hrs); 8 weeks.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works