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Algorithms smarter than experts? AI methods applied to assessment of environmental risk of World Bank projects

Author

Listed:
  • Laurent Boinot
  • Jaime Diaz
  • Steffen Feuerpeil
  • David Manoury
  • Gayatri Rao

Abstract

Environmental and social risk assessment of investment projects can be enhanced using text analytics. For each project, the World Bank assesses environmental risks and prepares environmental and societal safeguards for mitigation before board approval. In this paper, we used data available at the time of board approval regarding the project objectives and project descriptions to predict the risk of failure. We demonstrate that a simple model of text analytics, which goes beyond regular assessment reports, unearths hidden patterns to improve the evaluation of environmental and social hazards. We recommend that the World Bank improves its non-financial risk assessment by adopting artificial intelligence techniques. We also propose that the World Bank integrates text analytics in its open data and artificial intelligence initiatives.

Suggested Citation

  • Laurent Boinot & Jaime Diaz & Steffen Feuerpeil & David Manoury & Gayatri Rao, 2023. "Algorithms smarter than experts? AI methods applied to assessment of environmental risk of World Bank projects," International Journal of Sustainable Development, Inderscience Enterprises Ltd, vol. 26(2), pages 71-85.
    • Handle: RePEc:ids:ijsusd:v:26:y:2023:i:2:p:71-85
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