The FAIR application was developed to centralize appeal workflows previously managed manually across multiple data collection tools. Its objectives include providing a unified dashboard for appeals, enforcing role-based access, synchronizing appeal data between ActivityInfo and SQL Server, maintaining audit trails, and enabling reporting and data export capabilities. Success criteria emphasize complete appeal lifecycle management within FAIR, role-specific data visibility, and on-demand data export. The project explicitly excludes replacing ActivityInfo as the source system and advanced analytics beyond operational reporting. FAIR aims to improve consistency, efficiency, automation, analytics, and trust in appeal management processes
Activity Type AI Tools/Solutions
UNHCR’s AI Approach provides a strategic framework for using artificial intelligence in humanitarian contexts.
Rooted in human rights and humanitarian principles, it aims to improve outcomes for forcibly displaced and stateless people through responsible, inclusive, and transparent AI deployment.
What safeguards are in place to ensure ethical AI use?
UNHCR’s AI Approach is a model for ethical innovation in humanitarian work. It ensures that technology serves people, not the other way around, delivering faster, fairer, and more effective support to those in need.
What safeguards are in place to ensure ethical AI use?
- Ethical and human rights-based. This foundation ensures that AI adoption strengthens protection outcomes while safeguarding the rights and dignity of displaced and stateless populations
- Embrace AI responsibility by design. Maintaining the integrity of AI-assisted processes is essential to upholding the trust placed in UNHCR and ensuring institutional accountability.
- Champion people-centred AI. Human centricity is being embedded into the core of all AI initiatives, through the testing of new products with communities, designing different human centered processes, a commitment to shifting power dynamics, or adapting proven approaches to fit local needs and realities.
- Ensure robust internal governance. UNHCR’s governance of AI is being built on existing institutional processes and established decision-making structures.
- Foster meaningful partnerships. UNHCR’s engagement in AI is driven by strong collaboration across a diverse range of partners, including governments, international institutions and other UN agencies.
How does UNHCR advocate and engage on responsible AI?
- UNHCR is actively engaging in global conversations to promote the ethical use of artificial intelligence in humanitarian contexts.
- The organization advocates for AI systems that are rights-based, inclusive, transparent and accountable.
UNHCR developed a Virtual Legal Assistant (VLA) powered by Retrieval Augmented Generation (RAG) into its Rights Mapping and Analysis Platform (RiMAP). This platform support UNHCR country editors by efficiently collecting, processing, and analyzing vast amounts of legal documents across all UN countries and territories. This enables legal research and analysis processes, including extraction, translation, summarization, and drafting.
Once data is manually collected and indexed in a library accessible to the AI assistant, a first draft of responses to questions can be generated. This draft is created by extracting relevant paragraphs, translating them, and summarizing the content to produce an accurate response with sources. This draft serves as the foundation for the legal analysis that country editors can verify and further edit.
The library of sources includes government publications, laws and regulations, policies, academic research, and UNHCR reports. By leveraging AI, the VLA allows UNHCR to significantly reduce the time spent on legal research and drafting, ensuring the timely and comprehensive completion of RiMAP within a reduced timeframe.
The VLA is an AI-powered chatbot that utilizes resources contained within RiMAP. This public-facing chatbot provides easily accessible and user-friendly information on the rights of forcibly displaced and stateless persons. This initiative marks a significant step towards making legal data more accessible to a diverse range of stakeholders, including universities, legal aid organizations, governments, development actors, civil society groups, and, most importantly, forcibly displaced and stateless persons themselves.
The Tillabéri region faces severe insecurity due to escalating violence by armed groups, causing mass displacement of over 300,000 persons including IDPs, asylum seekers, and refugees. Infrastructure destruction and logistical challenges limit humanitarian access. This initiative develops a predictive machine learning model using publicly available data (conflict records, displacement, food insecurity, weather) to assess protection risks remotely in inaccessible areas, overcoming barriers to traditional data collection.
Activity Type AI Tools/SolutionsResearch/Reports/Assessments