I'd blush if I could: closing gender divides in digital skills through education

By M. West, Rebecca Kraut, Han Ei Chew. 2019

361 citations recorded by the source corpus.

Subfields: Education, Information Systems, Sociology and Political Science, AI Ethics, Fairness & Society, Social Sciences & Humanities

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Citations in the corpus

Ethical and social risks of harm from Language Models (2021, background): “Gender For example, commercially available voice assistants are overwhelmingly represented as submissive and female (Cercas Curry et al., 2020; West et al., 2019).”
Guiding the Release of Safer E2E Conversational AI through Value Sensitive Design (2022, background): “A recent report by UNESCO points out that the inability to respond appropriately to system-directed abuse may reinforce negative gender stereotypes (West et al., 2019), especially paired with their anthropomorphic and feminised design cues (cf. Abercrombie et al. (2021)).”
Taxonomy of Risks posed by Language Models (2022, background): “The commonplace gendering of CAs as female has been argued to promote the objectification of women, reinforcing ‘the idea that women are tools, fetishized instruments to be used in the service of accomplishing users’ goals’ [36, 195, 202].”
SafetyKit: First Aid for Measuring Safety in Open-domain Conversational Systems (2022, background): “For example, West et al. (2019) point out that “tol-erant, unassertive and subservient” responses by female-gendered systems to user abuse can reinforce negative gender stereotypes.”
A Crowd-based Evaluation of Abuse Response Strategies in Conversational Agents (2019, background): “As highlighted by a recent UNESCO report (West et al., 2019), appropriate responses to abusive queries are vital to prevent harmful gender biases: the often submissive and flirty responses by the femalegendered systems reinforce ideas of women as subservient.”
Consumers and Artificial Intelligence: An Experiential Perspective (2020, neutral): “…in this narrative, AI companies that strive for greater human touch cannot ignore that AI products and services modeled as “obliging, docile, and eager-to-please [human] helpers” often contribute to the social alienation of particular groups in society (West, Kraut, and Chew 2019, p. 104).”
ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AI (2021, background): “UNESCO calls for systems to appropriately address abusive users (West et al., 2019) but the effectiveness of abuse mitigation strategies is dependent on a good detection module that is both reliable and sufficiently fine-grained in terms of classification.”
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era (2022, background): “One particular example is that of voice assistants: as criticized in recent a UNESCO report [182], the initial design of several voice assistants was to show submissiveness, even in the face of blatant abuse, reinforcing notions of outdated “female servility.””
Sex and gender analysis improves science and engineering (2019, background): “It has previously been shown that gender stereotypes—for example, men are more likely to be computer scientists—are manifested in the feature vectors of the corresponding words 64 .”
Conversational Assistants and Gender Stereotypes: Public Perceptions and Desiderata for Voice Personas (2020, background): “On the second day, we introduced the issue of gendered technology, and got two experts presenting their views, including one of the authors of the UNESCO report and a UX Voice designer from the BBC.”
Adhering, Steering, and Queering: Treatment of Gender in Natural Language Generation (2020, background): “Kai is designed with a quirky bot personality that redirects gendered questions back to its distinctiveness as an algorithmically-generated text-based sys-tem, using humour and respectful dialogue [70].”
Alexa, Google, Siri: What are Your Pronouns? Gender and Anthropomorphism in the Design and Perception of Conversational Assistants (2021, background): “In March 2021, Apple announced that, in future, users would select a voice option on set-up,6 following a recommendation of West et al. (2019)’s UNESCO report.”
Conversational AI: Social and Ethical Considerations (2019, background): “Many publicly available agents present as female, including popular assistants such as Siri, Alexa, Cortana and the default female voice for Google Assistant [50].”