Social Tension Early Warning System | Horizon 360

“Our challenge is that current systems lack the capacity for real-time monitoring of social tensions, comprehensive needs assessments, and centralized knowledge management. This limitation hampers our ability to proactively respond to emerging threats and effectively plan interventions in Syria’s fragile socio-economic environment.”

History and Drivers: The challenge originates from the limitations of existing systems that are unable to provide real-time and accurate monitoring of social tensions in Syria. This deficiency is driven by a lack of integration and coordination among various data sources and methodologies currently in use. The systems in place are not equipped to harness modern technological capabilities such as AI-driven analytics and comprehensive data aggregation, which are essential for timely and predictive insights into social dynamics and potential conflicts. Involved Parties: The parties involved include UNDP’s Strategic Policy Unit, field staff, local authorities, community members, international partners, and donors. Each group plays a specific role in gathering, analyzing, and responding to data, but the effectiveness of their efforts is hindered by the disjointed nature of existing systems. Current Situation: Currently, the systems for monitoring social tensions are fragmented and lack the capability to provide a unified, real-time view of emerging risks. Similarly, needs assessments are often siloed and do not fully integrate the insights and input from local communities, especially marginalized and vulnerable groups. This results in interventions that may not be fully aligned with the actual needs on the ground. Undesired Effects: The primary undesired effect of these challenges is the increased likelihood of escalating tensions due to missed opportunities for early intervention. When emerging risks are not promptly or accurately identified, preventive actions cannot be taken, potentially leading to conflicts that could have been mitigated or avoided. Additionally, the lack of effective participatory needs assessments means that recovery and development efforts may not effectively address the most pressing community needs, leading to less efficient use of resources and reduced impact of interventions.

1. Innovative Approach: The Accelerator Lab brings a cutting-edge, data-driven methodology to tackle complex issues. By deploying Horizon 360, the Lab integrates AI and machine learning technologies to analyze and interpret vast amounts of data from diverse sources. This approach is unique within the UNDP framework and positions the Lab as a pioneer in harnessing technology for development and peacebuilding efforts. 2. Local and Global Network Synergy: The Accelerator Lab leverages both local knowledge and global innovations, enabling a cross-pollination of ideas and solutions that are culturally and contextually relevant. This dual approach ensures that solutions are not only imported but also adapted to meet the specific needs of Syrian communities, which may not be as effectively achieved by other actors. 3. Agile and Adaptive Development: Unlike more traditional parts of UNDP, the Accelerator Lab operates under principles of agility and continuous learning. This allows for rapid testing and scaling of innovations like Horizon 360 to adapt to the dynamic and evolving challenges in Syria. The Lab’s ability to iterate solutions based on real-time feedback and data positions it uniquely to refine and optimize interventions quickly. 4. Focus on Sustainable Impact: The Accelerator Lab’s commitment to sustainable and scalable solutions ensures that investments in tackling these challenges are not just about immediate outcomes but also about building long-term resilience and capabilities within local systems. This strategic focus supports the broader UNDP goal of sustainable development and peacebuilding. 5. Resource Optimization: By addressing these challenges, the Accelerator Lab helps optimize the allocation of resources within UNDP and among donor communities. Horizon 360’s data-driven insights enable more targeted interventions, efficient use of funds, and better reporting on impact, making it a worthwhile investment for donors seeking accountability and effectiveness.

“UNDP Syria’s Accelerator Lab is enhancing real-time monitoring of social tensions and boosting community-led needs assessments with Horizon 360, an AI-driven system aiming to proactively address conflicts and align interventions with real community needs. #InnovationForPeace”

“How can we effectively integrate and leverage AI and machine learning technologies within Horizon 360 to accurately predict and respond to social tensions, and how can we ensure that participatory needs assessments truly reflect the priorities and conditions of all community segments in Syria?”

1. Data Analysis: • Usage: Apply data analysis to both historical and real-time data collected through Horizon 360 to identify patterns and predictors of social tensions. Use statistical models and machine learning algorithms to analyze data from various sources such as social media, local reports, and field assessments. • Value: Enables the identification of key indicators of social tensions and the effectiveness of interventions. Data analysis provides empirical evidence to support decisions and improve the predictive capabilities of the early warning system. 2. Minimal Viable Product (MVP): • Usage: Develop an MVP of the Horizon 360 that focuses on core functionalities like real-time data collection, early warning alerts, and basic participatory needs assessment features. This MVP can then be tested in select communities to gauge its effectiveness and usability. • Value: Allows for rapid prototyping and iterative feedback from actual users, ensuring that the system is user-centric and meets the needs of all stakeholders. It also helps in managing resources efficiently by focusing on essential features before full-scale implementation. 3. Participatory Design: • Usage: Involve community members, local authorities, and UNDP field staff in the design process of Horizon 360 to ensure the system meets their needs. Conduct workshops and feedback sessions to iterate on the system design based on direct input from end-users. • Value: Enhances the relevance and acceptance of the system among users. Participatory design ensures that the system is not only about technology but also about usability and adaptability to local contexts. 4. Scaling: • Usage: Once the MVP has proven effective and after incorporating feedback from the participatory design phase, plan a scaling strategy to expand the system’s usage across other regions. This strategy should include technical scalability, training for new users, and integration with other data systems. • Value: Provides a roadmap for expanding the impact of Horizon 360, allowing more communities to benefit from real-time monitoring and participatory assessments. Scaling ensures that successful interventions are replicated and adapted across different regions, maximizing the reach and effectiveness of UNDP initiatives. 5. Social Network Analysis: • Usage: Use social network analysis to map and understand the relationships and influence patterns among community members. This can help identify key influencers and nodes within communities that can aid in the effective dissemination of information and mobilization of resources. • Value: Improves the strategic deployment of interventions and enhances community engagement. By understanding social networks, UNDP can tailor its communication and intervention strategies to leverage existing community structures and dynamics.

1. Citizen-generated Data: • Data Gaps Addressed: Often, official data collection methods miss nuanced, on-the-ground insights that can only be captured through direct citizen engagement. Citizen-generated data fills this gap by providing real-time, grassroots level information that may not be available through formal channels. • Value Added: Enhances the authenticity and relevance of the data used in monitoring and responding to social tensions and community needs, ensuring that interventions are directly informed by those most affected by the issues. 2. Deep Interviews: • Data Gaps Addressed: Surface-level surveys may not capture the depth of understanding needed to fully comprehend the complexities of social tensions and the underlying needs of communities. Deep interviews provide detailed qualitative insights that are crucial for comprehensive analysis. • Value Added: Offers a deeper understanding of the motivations, perceptions, and experiences of individuals, which is essential for designing interventions that are truly responsive to community dynamics. 3. Engagement with Local Stakeholders: • Data Gaps Addressed: There may be a lack of alignment between external interventions and the actual needs and priorities of local communities. Engaging with local stakeholders ensures that the data reflects local realities and the perspectives of those directly involved in or affected by the issues. • Value Added: Strengthens the legitimacy and acceptance of projects and initiatives, facilitating smoother implementation and better outcomes by aligning goals with local expectations and capacities. 4. Focus Group: • Data Gaps Addressed: Individual data points can miss broader community sentiments and shared experiences. Focus groups allow for the exploration of these communal perspectives and foster an understanding of common concerns and collective needs. • Value Added: Provides a platform for diverse community members to voice their opinions and concerns, ensuring that multiple viewpoints are considered in the decision-making process. 5. Social Network / Social Media Data: • Data Gaps Addressed: Traditional data collection methods might not capture dynamic and rapidly evolving social interactions. Social media and social network data provide insights into real-time public sentiments and social dynamics. • Value Added: Offers a vast amount of data that can be analyzed to identify trends, influencers, and the spread of information or misinformation, aiding in the timely and effective response to emerging social tensions. 6. Surveys: • Data Gaps Addressed: There may be a lack of quantitative data that can be statistically analyzed to generalize findings across larger populations. Surveys provide this quantitative framework to validate insights gathered through qualitative methods. • Value Added: Allows for the collection of data from a large number of individuals quickly and efficiently, providing a broad overview of community needs and perceptions that can be tracked over time. 7. Tracking Data: • Data Gaps Addressed: There is often a lack of continuous monitoring data that can track changes over time. Tracking data enables ongoing monitoring and evaluation of conditions and the impact of interventions. • Value Added: Essential for measuring the effectiveness of interventions and for making data-driven adjustments to strategies as situations evolve.

1. Government & Policy Makers • Who? Ministry of Local Administration, local government officials, municipal councils. • Role? Facilitate policy integration, provide legitimacy, and support data-driven governance. 2. Community & Civil Society • Who? Community leaders, CSOs, grassroots organizations. • Role? Ensure local ownership, advocate for participation, and facilitate data collection from the ground. 3. Technology & Research Partners • Who? Universities, research institutions, private sector tech firms. • Role? Support AI development, refine data models, and contribute to system scalability. 4. International Donors & Development Agencies • Who? UN agencies, EU, USAID, global NGOs. • Role? Provide funding, share best practices, and promote the model for potential replication in other regions.