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- Devinney, Hannah, 1995-
(författare)
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Gender and representation : investigations of bias in natural language processing
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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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- Devinney, Hannah, 1995-, et al.
(författare)
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Theories of Gender in Natural Language Processing
- 2022
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Ingår i: Proceedings of the fifth annual ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT'22). - New York, NY, USA : ACM.
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Konferensbidrag (refereegranskat)abstract
- The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date there is no comprehensive analysis of how “gender” is theorized in the field. We survey nearly 200 articles concerning gender bias in NLP to discover how the field conceptualizes gender both explicitly (e.g. through definitions of terms) and implicitly (e.g. through how gender is operationalized in practice). In order to get a better idea of emerging trajectories of thought, we split these articles into two sections by time.We find that the majority of the articles do not make their theo- rization of gender explicit, even if they clearly define “bias.” Almost none use a model of gender that is intersectional or inclusive of non- binary genders; and many conflate sex characteristics, social gender, and linguistic gender in ways that disregard the existence and expe- rience of trans, nonbinary, and intersex people. There is an increase between the two time-sections in statements acknowledging that gender is a complicated reality, however, very few articles manage to put this acknowledgment into practice. In addition to analyzing these findings, we provide specific recommendations to facilitate interdisciplinary work, and to incorporate theory and methodol- ogy from Gender Studies. Our hope is that this will produce more inclusive gender bias research in NLP.
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- Devinney, Hannah, et al.
(författare)
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Theories of Gender in Natural Language Processing
- 2022
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Konferensbidrag (refereegranskat)abstract
- The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date there is no comprehensive analysis of how “gender” is theorized in the field. We survey nearly 200 articles concerning gender bias in NLP to discover how the field conceptualizes gender both explicitly (e.g. through definitions of terms) and implicitly (e.g. through how gender is operationalized in practice). In order to get a better idea of emerging trajectories of thought, we split these articles into two sections by time.We find that the majority of the articles do not make their theo- rization of gender explicit, even if they clearly define “bias.” Almost none use a model of gender that is intersectional or inclusive of non- binary genders; and many conflate sex characteristics, social gender, and linguistic gender in ways that disregard the existence and expe- rience of trans, nonbinary, and intersex people. There is an increase between the two time-sections in statements acknowledging that gender is a complicated reality, however, very few articles manage to put this acknowledgment into practice. In addition to analyzing these findings, we provide specific recommendations to facilitate interdisciplinary work, and to incorporate theory and methodol- ogy from Gender Studies. Our hope is that this will produce more inclusive gender bias research in NLP.
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"Någonstädes mellan sol och söder, mellan nord och natt" : Interdisciplinära studier tillägnade Torsten Pettersson
- 2015
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Torsten Petterssons forskning utmärks av en mångfald och ett djup med få motstycken i nutida svenskspråkig litteraturvetenskap. Under de senaste 40 åren har han rört sig obehindrat mellan litteratur på en rad olika språk och från flertalet epoker. Till den vetenskapliga gärningen ska också läggas Torstens skönlitterära författarskap som omfattar dikter, noveller och kriminalromaner.Med denna festskrift, som utges i samband med att Torsten fyller 60 år, vill vi hylla honom och hans insats inom litteraturvetenskapen. Bidragen tar fasta på Torstens förmåga att överskrida gränser mellan discipliner, teman och metoder, och är skrivna av svenska och internationella forskare från en rad olika forskningsområden. Texterna behandlar ämnen som tolkningsteori och empirisk läsforskning, svensk, finlandssvensk, engelskspråkig och tysk litteratur, teologi och livsåskådning samt Torstens egen insats både som forskare och som skönlitterär författare.
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40 år av genusforskning! : Festskrift till Centrum för genusvetenskap
- 2023
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Med denna Festskrift firar vi att Centrum för genusvetenskap i över fyrtio år har fungerat som en viktig mötesplats för kunskap och vetenskapande – en sådan plats som många uppfattar som absolut nödvändig för sin överlevnad i akademin. Genom att sätta genus i centrum på Centrum skapar vi kunskap över gränser mellan vetenskapsområden, fakulteter och forskningsfält.Centrum består i grund och botten av de människor som verkar där. Den här Festskriften är också en hyllning till alla dessa människor – deras arbete, engagemang, intelligens, uthållighet och inspirationsförmåga. Centrum existerar också tack vare de viktiga nationella och internationella nätverk inom forskning och utbildning som Centrum är del av. Med denna bok skickar vi alltså en hälsning och ett tack till alla våra kollegor inom fältet. Kapitlen i denna volym är en blandning som sträcker sig från essäer och personliga historieskrivningar om Centrum, till reflektioner om arbetslivet vid Centrum eller som genusforskare överlag, till forskningsartiklar om en rad mycket olika områden, vilka i sig också vittnar om den livliga och variationsrika forskningsmiljö som vi fortsätter att bygga tillsammans.
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