Feminist HCI

Bellini, Rosanna; Strohmayer, Angelika; Alabdulqader, Ebtisam; Ahmed, Alex A.; Spiel, Katta; Bardzell, Shaowen; Balaam, Madeline

doi:10.1145/3170427.3185370

Cited by 23 publications

(7 citation statements)

References 12 publications

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“…We are in no way criticizing these trajectories, which are essential for achieving the elimination of inequalities in NLP and HCI. In fact, we would argue that gender bias in NLP is becoming a core area of feminist HCI [4,5,9,25], given that VAs continue to be taken up as a focus of study and by endusers [28,95]. Nevertheless, fighting sexism and toxicity will require considering gender and language in a different way [84].…”

Section: Gender Biases and Debiasing In Nlpmentioning

confidence: 99%

Transcending the “Male Code”: Implicit Masculine Biases in NLP Contexts

Seaborn

Chandra

Fabre

2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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Critical scholarship has elevated the problem of gender bias in data sets used to train virtual assistants (VAs). Most work has focused on explicit biases in language, especially against women, girls, femme-identifying people, and genderqueer folk; implicit associations through word embeddings; and limited models of gender and masculinities, especially toxic masculinities, conflation of sex and gender, and a sex/gender binary framing of the masculine as diametric to the feminine. Yet, we must also interrogate how masculinities are "coded" into language and the assumption of "male" as the linguistic default: implicit masculine biases. To this end, we examined two natural language processing (NLP) data sets. We found that when gendered language was present, so were gender biases and especially masculine biases. Moreover, these biases related in nuanced ways to the NLP context. We offer a new dictionary called AVA that covers ambiguous associations between gendered language and the language of VAs.

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Section: Gender Biases and Debiasing In Nlpmentioning

confidence: 99%

Transcending the “Male Code”: Implicit Masculine Biases in NLP Contexts

Seaborn

Chandra

Fabre

2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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“…Gender is often framed as femininity and masculinity, but a wealth of work across time and cultures has challenged this "binary" model [60,95,96,145,178,188,198], including in HCI [178,188,191]. Indeed, HCI has a history of developing, studying, and critiquing technologies for gender inclusion and anti-sexism [12,15,165]. Feminist and intersectional HCI [178] projects have appeared alongside social movements like #MeToo and organizational changes, notably the Critical Computing, Sustainability, and Social Justice subcommittee 2 at CHI [38].…”

Section: Introductionmentioning

confidence: 99%

Interacting with Masculinities: A Scoping Review

Seaborn

2023

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

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Gender is a hot topic in the field of human-computer interaction (HCI). Work has run the gamut, from assessing how we embed gender in our computational creations to correcting systemic sexism, online and off. While gender is often framed around women and femininities, we must recognize the genderful nature of humanity, acknowledge the evasiveness of men and masculinities, and avoid burdening women and genderful folk as the central actors and targets of change. Indeed, critical voices have called for a shift in focus to masculinities, not only in terms of privilege, power, and patriarchal harms, but also participation, plurality, and transformation. To this end, I present a 30-year history of masculinities in HCI work through a scoping review of 126 papers published to the ACM Human Factors in Computing Systems (CHI) conference proceedings. I offer a primer and agenda grounded in the CHI and extant literatures to direct future work.

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“…Alongside these developments, ACM members have also developed a variety of SIGs, workshops, and panels in the past to address specific issues related to feminisms [4], intersectionality [11], justice [10], or self-established communities [2,3,5,16], while others have worked in less institutional ways to develop grassroots action towards more inclusive spaces at CHI directly [18]. We wholeheartedly welcome these developments, and hope to see more of these in the future, but at the same time appreciate that we as a community have work to do before calling ourselves a truly inclusive space.…”

Section: Introductionmentioning

confidence: 99%

CHInclusion

Strohmayer

MacArthur

Spors

et al. 2019

Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

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HCI has a growing body of work regarding important social and community issues, as well as various grassroots communities working to make CHI more international and inclusive. In this workshop, Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Feminist HCI

Cited by 23 publications

References 12 publications

Transcending the “Male Code”: Implicit Masculine Biases in NLP Contexts

Transcending the “Male Code”: Implicit Masculine Biases in NLP Contexts

Interacting with Masculinities: A Scoping Review

CHInclusion

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