ID: 1737
Presenting Author: Irfan Al Hasani
Session: 552 - Accelerating with Integrity: Strengthening Social Impact Assessment in the face of urgency and misinformation
Status: pending
Preliminary findings suggest that embedding AI analytics within impact assessment processes strengthens information integrity, mitigates the risks of misrepresentation, and improves stakeholder trust
In an era marked by urgent global development needs and the growing influence of multinational financial organisations (MFOs), ensuring the integrity and credibility of social impact assessments has become increasingly vital. Yet, conventional assessment frameworks are often undermined by fragmented data sources, subjective evaluations, and the spread of misinformation in financial and policy communications.
This paper introduces an Artificial Intelligence (AI)-driven approach designed to measure and “robustify” the social and economic impacts of MFOs while enhancing transparency and accountability. The proposed model integrates machine learning and natural language processing to analyze both quantitative indicators and narrative data from leading institutions such as the IMF, World Bank, and regional development banks. By detecting inconsistencies, verifying claims, and mapping misinformation patterns, the framework provides a more objective and reproducible assessment of institutional performance and community-level outcomes.
Preliminary findings suggest that embedding AI analytics within impact assessment processes strengthens information integrity, mitigates the risks of misrepresentation, and improves stakeholder trust in large-scale financial interventions. The paper concludes by recommending pathways for integrating AI-enabled validation mechanisms into international social impact assessment practices to ensure decisions remain credible, inclusive, and evidence-based—even amid increasing urgency for action.
Keywords: Artificial Intelligence, Social Impact Assessment,
Dr. Irfan Al Hasani’s career spans academia, research, training, and advisory work.
Coauthor 1: Wassan Naash