• Curto, G., Comim, F., (2023). SAF: Stakeholders' Agreement on Fairness in the Practice of Machine Learning Development. Science and Engineering Ethics. 

• Kiritchenko, S., Curto, G., Nejadgholi, I., Fraser, K. C., (2023). Aporophobia: An Overlooked Type of Toxic Language targeting the poor. ACL 2023 - Association of Computational Linguistics. 7th Workshop on Online Abuse and Harms (WOAH). Awarded Outstanding Paper 

• Curto, G., Kiritchenko, S., Nejadgholi, I., and Fraser, K. C., (2023). The Crime of Being Poor. (Under review in Proceedings of the National Academy of Sciences of the United States (PNAS Nexus)). Accessible through ArXiv. 

• Curto, G., & Arnaiz, A., Oliver, N. (2023). Algorithms for Social Justice: Affirmative Action in Social Networks. Accessible through ArXiv. 

• Montes, N., Curto, G., Osman, N., Sierra, C. (2023). An Agent-Based Model for Poverty and Discrimination Policy- Making. Proceedings of the AMPM 2022: 2nd Workshop in Agent-based Modeling & Policy-Making, JURIX. 

• Curto, G., Montes, N. Comim, F., Osman, N., Sierra, C. (2022). A norm Optimization Approach to SDGs: Tackling Poverty by Acting on Discrimination. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI'22). Track AI for Good (Best Project Award).

• Curto, G., Jojoa Acosta, M ., Comim, F., & Garcia-Zapirain, B. (2022). Are AI systems Biased Against the Poor? A Machine Learning Analysis Using Word2vec and GloVe Embeddings. AI and Society.

• Curto, G. (2002). Artificial Intelligence and Inclusion: An Analysis of Bias Against the Poor. Universitat Ramon Llull.

Under review: 

• Aguilera, A., Montes, N., Curto, G., Osman, N., Sierra, C. (2023). Can poverty be reduced by acting on discrimination? An agent-based model for policy making. 

Working papers: 

•  “110 Years of Bias against the Poor Tracked by Large Language Models”. With Yang, Y., Lale, J. & Abbasi, A. 

• “Poverty as an Aggravator of Xenophobia: an Analysis Using Machine Learning”. With Jojoa Acosta, M., Chaves, A., & Garcia-Zapirain, B.  

• Review of the book: Cortina, A. (2022), Aporophobia : why we reject the poor instead of helping them. Princeton University Press. For the journal International Review of Social History (IRSH), Springer.

• “Poverty policy making optimization by the use of agent-based models: case study for the city of Barcelona” With Montes, N., Osman, N., Sierra, C . 

• “Machine Learning-based indexes for the United Nations: accounting for public opinion in social networks and pre-labeling with ChatGPT”. With Kiritchenko, S., Nejadgholi, I., Fraser, K.C.