Fighting Hate Speech, Silencing Drag Queens? Artificial Intelligence in Content Moderation and Risks to LGBTQ Voices Online.
Companies operating internet platforms are developing artificial intelligence tools for content moderation purposes. This paper discusses technologies developed to measure the 'toxicity' of text-based content. The research builds upon queer linguistic studies that have indicated the use of 'mock imp...
| Publicado en: | Sexuality & Culture Vol. 25; no. 2; pp. 700 - 733 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Apr2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=149026012&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 149026012 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 10955143 DZ0 jtl: Sexuality & Culture issn: 10955143 maglogo: N pubinfo: dt: Apr2021 vid: 25 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 149026012 10.1007/s12119-020-09790-w ppf: 700 ppct: 33 formats: fmt: @attributes: type: P size: 2.9MB tig: atl: Fighting Hate Speech, Silencing Drag Queens? Artificial Intelligence in Content Moderation and Risks to LGBTQ Voices Online. aug: au: Dias Oliva, Thiago Antonialli, Dennys Marcelo Gomes, Alessandra affil: University of São Paulo, São Paulo, Brazil InternetLab, São Paulo, Brazil University of São Paulo Law School, São Paulo, Brazil Stanford Law School, Stanford, USA Bucerius Law School, Hamburg, Germany WHU Otto Von Beisheim School of Management, Vallendar, Germany State University of Campinas (UNICAMP), Campinas, Brazil Federal University of Pará (UFPA), Belém, Brazil su: LGBTQ+ people Linguistics Artificial intelligence Hate speech Drag queens sug: subj: LGBTQ+ people Linguistics Artificial intelligence Hate speech Drag queens keyword: Content moderation Queer linguistics Toxicity ab: Companies operating internet platforms are developing artificial intelligence tools for content moderation purposes. This paper discusses technologies developed to measure the 'toxicity' of text-based content. The research builds upon queer linguistic studies that have indicated the use of 'mock impoliteness' as a form of interaction employed by LGBTQ people to cope with hostility. Automated analyses that disregard such a pro-social function may, contrary to their intended design, actually reinforce harmful biases. This paper uses 'Perspective', an AI technology developed by Jigsaw (formerly Google Ideas), to measure the levels of toxicity of tweets from prominent drag queens in the United States. The research indicated that Perspective considered a significant number of drag queen Twitter accounts to have higher levels of toxicity than white nationalists. The qualitative analysis revealed that Perspective was not able to properly consider social context when measuring toxicity levels and failed to recognize cases in which words, that might conventionally be seen as offensive, conveyed different meanings in LGBTQ speech. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Sexuality & Culture is a copyright of Springer, 2021. All Rights Reserved. item: Sexuality & Culture holder: Springer Nature dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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