A Norm Optimisation Approach to SDGs: Tackling Poverty by Acting on Discrimination
Appeared In: Proceedings of the 31st International Joint Conference on Artificial Intelligence
Publication Date: July 2022
Policies that seek to mitigate poverty by acting on equal opportunity have been found to aggravate discrimination against the poor (aporophobia), since individuals are made responsible for not progressing in the social hierarchy. Only a minority of the poor benefit from meritocracy in this era of growing inequality, generating resentment among those who seek to escape their needy situations by trying to climb up the ladder. Through the formulation and development of an agent-based social simulation, this study aims to analyze the role of norms implementing equal opportunity and social solidarity principles as enhancers or mitigators of aporophobia, as well as the threshold of aporophobia that would facilitate the success of poverty-reduction policies. The ultimate goal is to guide a new generation of policy making for poverty reduction by acting on the discrimination against the poor.
Curto, G., Montes, N., Sierra, C., Osman, N., & Comim, F. A Norm Optimisation Approach to SDGs: Tackling Poverty by Acting on Discrimination. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22). Special Track AI for Good 6, 5228–5235 (2022). DOI: 10.24963/ijcai.2022/726