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- Devinney, Hannah, 1995-
(author)
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Gender and representation : investigations of bias in natural language processing
- 2024
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Doctoral thesis (other academic/artistic)abstract
- Natural Language Processing (NLP) technologies are a part of our every day realities. They come in forms we can easily see as ‘language technologies’ (auto-correct, translation services, search results) as well as those that fly under our radar (social media algorithms, 'suggested reading' recommendations on news sites, spam filters). NLP fuels many other tools under the Artificial Intelligence umbrella – such as algorithms approving for loan applications – which can have major material effects on our lives. As large language models like ChatGPT have become popularized, we are also increasingly exposed to machine-generated texts.Machine Learning (ML) methods, which most modern NLP tools rely on, replicate patterns in their training data. Typically, these language data are generated by humans, and contain both overt and underlying patterns that we consider socially undesirable, comprising stereotypes and other reflections of human prejudice. Such patterns (often termed 'bias') are picked up and repeated, or even made more extreme, by ML systems. Thus, NLP technologies become a part of the linguistic landscapes in which we humans transmit stereotypes and act on our prejudices. They may participate in this transmission by, for example, translating nurses as women (and doctors as men) or systematically preferring to suggest promoting men over women. These technologies are tools in the construction of power asymmetries not only through the reinforcement of hegemony, but also through the distribution of material resources when they are included in decision-making processes such as screening job applications.This thesis explores gendered biases, trans and nonbinary inclusion, and queer representation within NLP through a feminist and intersectional lens. Three key areas are investigated: the ways in which “gender” is theorized and operationalized by researchers investigating gender bias in NLP; gendered associations within datasets used for training language technologies; and the representation of queer (particularly trans and nonbinary) identities in the output of both low-level NLP models and large language models (LLMs). The findings indicate that nonbinary people/genders are erased by both bias in NLP tools/datasets, and by research/ers attempting to address gender biases. Men and women are also held to cisheteronormative standards (and stereotypes), which is particularly problematic when considering the intersection of gender and sexuality. Although it is possible to mitigate some of these issues in particular circumstances, such as addressing erasure by adding more examples of nonbinary language to training data, the complex nature of the socio-technical landscape which NLP technologies are a part of means that simple fixes may not always be sufficient. Additionally, it is important that ways of measuring and mitigating 'bias' remain flexible, as our understandings of social categories, stereotypes and other undesirable norms, and 'bias' itself will shift across contexts such as time and linguistic setting.
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| 2. |
- Nilsson, Elina, 1984-
(author)
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Thai Surrogate Mothers’ Experiences of Transnational Commercial Surrogacy : Navigating Local Morality and Global Markets
- 2022
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Doctoral thesis (other academic/artistic)abstract
- Transnational commercial surrogacy is an arrangement where a woman gestates and delivers a child for intended parents from another country in exchange for money. This thesis explores the experiences of women who have acted as surrogate mothers in Thailand. Based on in-depth interviews with twelve former surrogate mothers, the thesis analyses their accounts in relation to gendered, local, and global dimensions of transnational commercial surrogacy. More specifically, it investigates how surrogacy has affected the women materially, socially, and personally; how they understand and negotiate family, kinship, and relationships in connection with their surrogacy experiences; but also how the global surrogacy market and local context interact in shaping the conditions for surrogacy in Thailand. The thesis engages in dialogue with research on commercial surrogacy in other settings, and draws upon theoretical frameworks of gender, motherhood and kinship, local moral economies, and precarious intimate labour. The analysis explores, first, how the women’s decisions to undertake surrogacy, and, for some, further involvement in surrogacy are enabled through women’s social networks and family relationships. Second, it investigates how, through the framing of surrogacy as primarily an opportunity to earn money for their own family but also as an act of making merit, the women draw upon material and religious rationalities as well as gender ideals that allow them to live up to their obligations as mothers and daughters. Third, it explores how their trajectories are marked by im/mobility and flexibility, taking shape in relation to the global reproductive market as well as local and national conditions. Finally, it demonstrates how the women use strategies of de/kinning that both align with and resist the idea that the surrogate mother is not related to the child. The results highlight the precariousness of these women’s labour and how surrogacy stretches into their lives beyond the nine months of pregnancy. Results also focus the women’s own decision-making and negotiations within the context of constrained but real agency. This thesis contributes knowledge about the situation of surrogate mothers post-pregnancy, and also in a context where surrogacy is illegal. It also contributes to the research fields of transnational reproduction, gendered and global division of intimate labour and feminist discussions on motherhood.
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