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Hannah Devinney

Gender and Natural Language Processing. I work on methods for reducing algorithmic harms caused by biased language data. My pronouns are they/them in English.



Works at

Doctoral student at Department of Computing Science
MIT-huset, Umeå universitet, MIT.D.415 Umeå universitet, 901 87 Umeå
Affiliated as doctoral student at Umeå Centre for Gender Studies (UCGS)
Samhällsvetarhuset, Plan 4

We interact with Natural Language Processing technology every day, whether in forms we see (auto-correct, translation services, search results) or those we don't (social media algorithms, "suggested reading" for news articles). NLP also fuels other "AI" tools - such as sorting CVs or approving loan applications - which can have major effects on our lives.

"Machine learning" methods replicate patterns in human-produced data, but these patterns are often undesireable (stereotypes and other reflections of human prejudice are present both implicitly and explicitly in the language we "show" computers when training these systems). My research is on understanding these biases (with respect to structural power) in the language data used to train NLP models and developing methods to reduce the potential for these models to do harm. Currating training data to better represent marginalized groups is an important first step towards a justice-focused approach to developing and deploying algorithms.
You can read more about the EQUITBL project on its page (coming soon).

Dual association with Department of Computing Science and the Umeå Centre for Gender studies.

My pronouns are they/them in English (hen/hen i svenska).

FAccT '23: Proceedings of the 2023 ACM conference on fairness, accountability, and transparency, ACM Digital Library 2023 : 1014-1025
Aler Tubella, Andrea; Coelho Mollo, Dimitri; Dahlgren, Adam; et al.
Proceedings of the third workshop on language technology for equality, diversity, inclusion, The Association for Computational Linguistics 2023 : 54-61
Björklund, Henrik; Devinney, Hannah
International conference. Recent advances in natural language processing 2023, large language models for natural language processing: proceedings
Devinney, Hannah; Eklund, Anton; Ryazanov, Igor; et al.
Swedish Language Technology Conference 2022, Stockholm, Sweden, November 23-25, 2022
Björklund, Henrik; Devinney, Hannah
Proceedings of the fifth annual ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT'22)
Devinney, Hannah; Björklund, Jenny; Björklund, Henrik
Proceedings of the Second Workshop on Gender Bias in Natural Language Processing, Association for Computational Linguistics 2020 : 79-92
Devinney, Hannah; Björklund, Jenny; Björklund, Henrik
SLTC 2020 – The Eighth Swedish Language Technology Conference, 25–27 November 2020, Online
Devinney, Hannah; Björklund, Jenny; Björklund, Henrik

Research groups

Published: 14 Apr, 2024
Published: 24 Sep, 2020