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Browsing: AI-powered algorithms
While the Organisation for Economic Co-operation and Development (OECD) reports US$300 billion of annual investments in developing countries, only 20 per cent of the implementing practitioners have the sufficient data required to successfully meet the needs of the communities they work with.
According to Rural Senses CEO Yau Ben-Or, this is because most projects are still built solely on quantitative data.
“Although necessary, quantitative data doesn’t reveal what success looks like for the local communities. Existing tools for the collection and analysis of qualitative data are time-consuming, costly and often introduce biases and ambiguous results,” Ben-Or notes.
As a result, important insights are missed, organisational learning is compromised, and projects’ sustainability is limited, he added.
