I was delighted to join the SP.org Podcast this week to discuss one of the most transformative and pressing topics in our field: the role of Artificial Intelligence (AI) in social protection systems.
For those unfamiliar, socialprotection.org is a global online community that fosters knowledge-sharing and collaboration in the social protection space. It brings together policymakers, practitioners, and thought leaders to explore innovative solutions to social challenges. Their podcast series is a cornerstone of this mission, providing a platform for deep dives into the ideas shaping the future of social protection.
This episode focused on how AI is enabling smarter, more responsive programs while addressing the critical questions of ethics, equity, and human oversight. With my background in designing digital and AI-enhanced tools for humanitarian and social protection systems, it was a privilege to contribute to this important conversation.
Listen to the podcast episode here: Ep. 46 | Harnessing AI for Social Protection: opportunities and risks | socialprotection.org
Key Points from the Discussion
In this episode, we explore:
- AI’s Transformative Potential: From predictive tools like Kent’s OneView platform to Estonia’s OTT system, AI is enabling smarter targeting, proactive interventions, and cost savings across social protection systems.
- Ethics and Challenges: Addressing Data Privacy, Algorithmic Bias, and Human Oversight: The integration of AI raises important concerns around data privacy, algorithmic bias, and maintaining human oversight to ensure fairness and accountability.
- Real-World Applications: Insights from humanitarian settings, such as Turkey’s earthquake response and Syria’s displacement, where AI tools accelerated analysis and improved responsiveness.
- Future Opportunities: How AI can support adaptive social protection systems and better prepare for shocks while aligning humanitarian and governmental responses.
AI’s Transformative Potential: Smarter Targeting, Proactive Interventions, and Cost Savings
Artificial Intelligence (AI) is fundamentally altering how we approach social protection systems, transitioning from reactive to proactive models that deliver greater efficiency and equity. Two notable examples—Estonia’s OTT tool and Kent’s OneView platform—demonstrate how AI is reshaping service delivery by leveraging data-driven insights.
1. OTT: Revolutionizing Unemployment Services in Estonia
The OTT system, developed by the Estonian Unemployment Insurance Fund, illustrates the power of predictive analytics in social protection. Here’s how it transforms unemployment services:
- Data-Driven Insights: OTT analyzes five years of unemployment data, encompassing over 100,000 client records and more than 60 attributes, including jobseeker history, education, health constraints, and regional labor market conditions
- Precision Targeting: The system assigns risk scores to jobseekers, identifying those most likely to face long-term unemployment. This enables consultants to focus resources where they are needed most, tailoring interventions like upskilling or health-related accommodations
- Operational Efficiency: OTT’s dashboard allows consultants to prioritize their workload, evenly distributing cases and supporting inexperienced staff. This data-driven approach enhances service quality while preventing long-term unemployment, which reduces state expenditures by up to 3.8% annually for even a one-day reduction in unemployment duration.
By proactively addressing unemployment risks, OTT has not only enhanced service delivery but also won accolades, such as the Best Data-Based Digital Service award in Estonia’s public sector
2. OneView: Preventing Homelessness in Kent
In Kent, the OneView platform demonstrates AI’s potential to tackle complex social challenges like homelessness:
- Early Intervention: By integrating data from housing, social care, health, and education systems, OneView predicts households at risk of homelessness. Early-warning alerts enable caseworkers to provide timely, targeted support, such as financial counseling or housing assistance
- Resource Optimization: The platform’s predictive capabilities allow local authorities to allocate resources effectively, reducing intervention costs while improving outcomes. For example, pilot programs in Kent achieved a 40% reduction in homelessness and generated savings of over £225,000 within the first year
- Ethical Data Use: OneView employs stringent privacy protocols, including pseudonymization and role-based access, to ensure compliance with GDPR and maintain public trust
The Broader Impact
These systems exemplify how AI amplifies the capabilities of social protection frameworks:
- Enhanced Equity: AI ensures that resources reach those in greatest need by addressing systemic inequalities in service delivery.
- Cost Efficiency: From reducing unemployment to preventing homelessness, AI tools demonstrate that proactive interventions cost less and yield better social outcomes
- Policy Insights: Aggregated data enables policymakers to make informed decisions, designing more effective programs and interventions
However, as discussed in the podcast, the integration of AI also comes with challenges, including potential biases, data governance, and the need for human oversight. It is essential that we navigate these challenges responsibly to unlock AI’s full transformative potential.
Ethics and Challenges: Addressing Data Privacy, Algorithmic Bias, and Human Oversight
The integration of Artificial Intelligence (AI) in social protection systems brings transformative potential, but it also raises critical ethical and operational challenges. Ensuring these systems promote fairness, accountability, and dignity requires confronting risks tied to data privacy, algorithmic bias, and human oversight. Two prominent cases, the Dutch childcare benefits scandal and Australia’s Robodebt scheme, highlight these challenges.
Data Privacy and Security
AI systems in social protection rely on extensive personal and sensitive data, creating unique privacy risks:
- The ‘Nuclear Waste’ Paradox: Humanitarian and social protection programs often collect highly sensitive data from vulnerable populations. While vital for effective service delivery, this data can be weaponized if leaked or misused, especially in conflict zones.
- Informed Consent: Individuals in crisis situations may feel compelled to share personal information, raising concerns about whether their consent is truly voluntary.
Effective data governance is essential to address these concerns. Measures such as data minimization, robust encryption, and clear accountability mechanisms can safeguard against breaches while ensuring compliance with privacy regulations like GDPR.
Algorithmic Bias
AI systems are only as unbiased as the data and assumptions they are built upon. Without careful oversight, they can replicate or even exacerbate societal inequities:
- The Dutch Childcare Benefits Scandal: In the Netherlands, an algorithm intended to detect fraudulent childcare claims disproportionately targeted ethnic minorities and dual nationals. Thousands of families were wrongfully accused, leading to severe financial and emotional harm.
- Australia’s Robodebt Scheme: This initiative used automated data-matching to recover welfare overpayments. However, the flawed system falsely accused hundreds of thousands of welfare recipients of owing debts, causing undue distress and, in some cases, tragic outcomes. Following a Royal Commission, the program was condemned as a “cruel and crude mechanism,” leading to legal and political repercussions
These cases underscore the critical need for:
- Bias Monitoring and Correction: Regular audits and recalibration of algorithms to identify and mitigate discriminatory patterns.
- Ethical Algorithm Design: Incorporating fairness and accountability into system development to avoid perpetuating systemic biases.
Maintaining Human Oversight
AI should augment human judgment, not replace it:
- Human-in-the-Loop: Systems like Estonia’s OTT and Kent’s OneView empower social workers with data insights but leave final decisions in human hands, preserving empathy and contextual understanding.
- Transparency and Accountability: Beneficiaries must understand how decisions are made and have access to appeal mechanisms. Transparent communication fosters trust and ensures equitable outcomes
Striking the Right Balance
To harness AI responsibly, social protection systems must integrate these principles:
- Data Governance: Strong frameworks for secure, ethical data management.
- Accountability Mechanisms: Ensuring transparency and the ability to challenge decisions.
- Continuous Monitoring: Proactively addressing unintended consequences through oversight and recalibration.
AI in social protection offers unprecedented opportunities to improve efficiency and equity, but these tools must be wielded with care. By embedding fairness, accountability, and human dignity into every stage of AI development and deployment, we can create systems that serve humanity without compromising its values.
Future Opportunities: AI for Adaptive Social Protection and Shock Preparedness
As we advance into 2025, the possibilities for Artificial Intelligence (AI) in transforming social protection systems are vast. AI has proven its ability to support adaptive systems, enabling governments and humanitarian actors to anticipate and respond to shocks effectively. Here’s how AI can shape a future of more resilient, equitable, and impactful social protection.
Dynamic Risk Assessment
AI models can analyze real-time data from diverse sources—climate forecasts, economic trends, and health indicators—to proactively identify at-risk populations. Imagine a social protection dashboard that flags potential drought-affected areas based on weather patterns or predicts spikes in unemployment using real-time economic data. These systems could:
- Trigger early interventions, such as mobilizing food stocks or releasing cash transfers, well before crises escalate.
- Allow governments to reallocate resources dynamically, ensuring the most vulnerable communities receive support precisely when they need it.
Building on this, governments could create “early action funds” that deploy financial resources the moment AI identifies a looming crisis. This approach shifts social protection from reactive to anticipatory, providing a safety net before individuals fall into deeper vulnerability.
Integrated Data Systems
One of the greatest opportunities lies in breaking down silos between sectors. AI thrives on interconnected data systems, and by unifying data from health, education, and social welfare systems, governments can:
- Provide holistic support tailored to individuals. For instance, a mother seeking nutrition assistance could also be alerted to education stipends or housing support programs she qualifies for—all through a single interface.
- Optimize resource allocation by identifying overlaps or gaps across programs, ensuring no vulnerable group is left behind.
In my blog last week, I highlighted the need for robust inter-agency collaboration to make this vision a reality. AI tools can support this process, but they require standardized data protocols and agreements that ensure different agencies work together seamlessly. This collaborative model transforms fragmented social services into cohesive, people-centered systems.
Shock-Responsive Systems
The past year demonstrated the potential for AI to enhance shock preparedness:
- AI-driven early warning systems can predict emergencies, such as food insecurity, displacement, or public health crises. For example, analyzing market prices in Türkiye post-earthquake allowed responders to decide whether cash or in-kind support was more appropriate.
- Real-time monitoring tools help track program effectiveness, ensuring swift adjustments to meet evolving needs.
Governments and humanitarian organizations can further leverage AI to align their responses. Shared AI platforms, designed to unify data and insights across stakeholders, could streamline resource distribution, prevent duplication, and enhance accountability during crises.
Balancing Efficiency with Equity
While AI offers significant efficiency gains, ensuring equity remains a critical priority:
- Inclusive Access: Agencies must prioritize digital equity by addressing barriers like low connectivity, digital illiteracy, or lack of documentation.
- Ethical Oversight: As I’ve emphasized before, AI systems must keep humans in the loop. This ensures that data-driven decisions are refined with local context and human empathy.
- Scalability: AI tools must be adaptable to the needs of diverse populations, from urban centers to remote, underserved communities.
Implementing robust “equity audits” can help detect and address disparities in service delivery, ensuring no demographic is unintentionally excluded. Additionally, governments should invest in transparent grievance mechanisms to empower citizens to appeal unfair decisions and build trust in these systems.
A Vision for 2025 and Beyond
AI’s ability to revolutionize adaptive social protection lies in its capacity to predict and prevent shocks, integrate siloed systems, and provide timely, equitable support. As we embrace these tools, collaboration between governments, humanitarian actors, and the private sector will be essential to scale solutions responsibly.
The question is not whether we will use AI, but how thoughtfully we will wield its power. If we balance innovation with ethical principles and remain steadfast in keeping human needs at the center, AI can help us create a world where social protection systems not only react to crises but actively prevent them.
AidGPT.org
To further explore the transformative role of AI in social protection and humanitarian aid, I invite you to join the conversation at AidGPT.org. AidGPT is a collaborative platform where humanitarians, technologists, and researchers converge to leverage innovation in addressing the world’s most complex challenges.
Our forum, discuss.aidgpt.org, serves as a central hub for open dialogue on ethical AI applications in humanitarian and development contexts.
By participating, you can:
- Engage with Peers: Connect with a community of like-minded professionals and enthusiasts.
- Stay Informed: Keep up-to-date with the latest developments, projects, and best practices in AI for humanitarian aid.
- Contribute to Discussions: Share your insights, experiences, and questions to help shape the future of AI in our field.
Your insights and experiences are invaluable to this community.
Join us at AidGPT.org and become part of the movement to harness the power of AI for humanitarian causes.
Together, we can drive meaningful conversations and innovative solutions that make a difference.