The United Nations Development Programme (UNDP) has launched an Artificial Intelligence-based (AI) tool to map vulnerabilities in Cambodia and accelerate poverty reduction and the achievement of the Sustainable Development Goals (SDGs).
Alissar Chaker, UNDP Cambodia's Resident Representative, said at Monday's launch ceremony that the UNDP and Spatial Informatics Group (SIG) have worked together during the past year to develop an interactive online tool to map multidimensional vulnerabilities using AI and big data technology. This has been widely consulted with government counterparts before being made available for Monday's training.
“Historically, it has been difficult to capture up-to-date, detailed information on the factors contributing to vulnerability and poverty,” Chaker said.
“This is particularly true in developing nations like Cambodia. Survey data collection is usually time-consuming and tedious. Fortunately, advances in machine learning and big data now allow for mapping at-risk areas within a geographic region in real-time and at an extremely low cost.”
The web-based Cambodian Vulnerability Mapping Tool will make vulnerability information more widely accessible in the country, she said, adding it is sophisticated, easy-to-use and allows users to toggle through maps that assess multiple deficiencies in key sectors contributing to vulnerability and poverty.
With this tool, users can explore multiple, overlapping vulnerabilities at the provincial, district, or commune/sangkat levels. Users can also explore specific vulnerability indicators, such as education, health, living standards, and monetary factors.
Citing recent official poverty figures, Chaker said 17.8 percent of Cambodia's population live below the national poverty line.
Such poverty incidence is usually correlated and can be explained by a wide array of vulnerability factors, including lack of access to quality education, clean water, improved roads, and solid waste management, Chaker said.
“Having data-driven ability to map these vulnerability factors in real-time is therefore instrumental to assisting an informed and efficient decision-making, directing to regions that need support the most,” Chaker said.