AIHAssa

AIHAssa, short for Artificial Intelligence for Humanitarian Assistance and Security Systems Assessment, is a proposed framework and set of best practices intended to guide the development and deployment of AI technologies in humanitarian and public safety contexts. The aim is to improve the efficiency and fairness of assistance, while ensuring accountability and safety.

The core components include data interoperability, model governance, human-in-the-loop oversight, explainability, risk assessment, and continuous monitoring. The framework emphasizes transparent data provenance, bias mitigation, robust cybersecurity, and audit-ready logging. It envisions modular components such as needs assessment tools, resource allocation simulators, and incident monitoring dashboards that can be integrated with existing humanitarian information systems.

Applications include prioritizing relief distribution, coordinating logistics, risk mapping in disaster zones, early warning for public safety, and post-disaster damage assessment. It is not prescriptive about specific algorithms, but recommends evaluation against social impact, privacy, and safety criteria before deployment.

Governance and status: AIHAssa is discussed in academic and NGO circles as an evolving standard; there is no universal mandate. Adoption varies by region and organization; pilot programs and open-source toolkits have been proposed to illustrate the approach.

Challenges: privacy, data ownership, bias, accountability, potential for amplification of harm, and the need for human oversight remain central concerns.

See also: AI ethics, humanitarian technology, explainable AI.