Ana Valdivia is Research Associate at the Department of War Studies working on the ERC Project led by Pr. Claudia Aradau: ‘SECURITY FLOWS: Enacting border security in the digital age: Political lives of data forms, flows and frictions’. In this transdisciplinary project, she is exploring how datafication technologies are transforming borders and migration governance. She is also developing digital methodologies to discover which algorithmic systems are implemented nowadays in the field of border security.

Ana received her PhD in Machine Learning and Natural Language Processing from Universidad de Granada (in February 2019), in which she explored the performance of computational methods developed to extract the expressed opinion of a given text. This work contributed to expose that emotional technologies show strong inconsistencies. Concerned about the impact that artificial intelligence (AI) can have on oppressed communities, her interest lies in investigating power relationships in algocracies and how governmental and non-governmental actors are fuelling the future with AI.

Before joining the Department of War Studies, she was a data scientist in the private sector. She conducted research in interdisciplinary teams made of data scientist, social scientist, and ethical and legal experts to design technological solutions that tackle complex social changes. She has also been a fellow of the Data Science for Social Good program at University of Chicago, where she partnered with the Ministry of Education of El Salvador.

She collaborates with the “Jevon’s Paradox” blog, where she examines science, knowledge and power relations. She is also a member of Algorights, a community created to raise awareness about the risks of AI.

 

Qualifications

• BSc Mathematics, Universitat Politècnica de Catalunya
• MSc Data Science and Computer Engineering, Universidad de Granada
• PhD Machine Learning and Natural Language Processing, Universidad de Granada

 

Research interests

• Artificial Intelligence, Power and Resistance
• Fairness, Accountability and Transparency in Machine Learning
• Natural Language Processing
• Data Feminism
• Design Justice

 

Recent publications

• Valdivia, A., Sánchez‐Monedero, J., & Casillas, J. (2021). How fair can we go in machine learning? Assessing the boundaries of accuracy and fairness. International Journal of Intelligent Systems, 36(4), 1619-1643.
• Valdivia, A., Martinez-Camara, E., Chaturvedi, I., Luzón, M. V., Cambria, E., Ong, Y. S., & Herrera, F. (2020). What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. Journal of Ambient Intelligence and Humanized Computing, 11(1), 39-52.
• Martínez-de-Albéniz, V., & Valdivia, A. (2019). Measuring and exploiting the impact of exhibition scheduling on museum attendance. Manufacturing & Service Operations Management, 21(4), 761-779.
• Zuheros, C., Tabik, S., Valdivia, A., Martínez-Cámara, E., & Herrera, F. (2019). Deep recurrent neural network for geographical entities disambiguation on social media data. Knowledge-Based Systems, 173, 117-127.
• López, M., Valdivia, A., Martínez-Cámara, E., Luzón, M. V., & Herrera, F. (2019). E2SAM: evolutionary ensemble of sentiment analysis methods for domain adaptation. Information Sciences, 480, 273-286.
• Valdivia, A., Hrabova, E., Chaturvedi, I., Luzón, M. V., Troiano, L., Cambria, E., & Herrera, F. (2019). Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods. Neurocomputing, 353, 3-16.
• Valdivia, A., Luzón, M. V., Cambria, E., & Herrera, F. (2018). Consensus vote models for detecting and filtering neutrality in sentiment analysis. Information Fusion, 44, 126-135.
• Valdivia, A., Luzón, M. V., & Herrera, F. (2017). Sentiment analysis in tripadvisor. IEEE Intelligent Systems, 32(4), 72-77.