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Gender a moc (či bezmocnost) ĆŸen v digitĂĄlnĂ­ éƙe: Kdo programuje umělou inteligenci? 📚 Zdroje
Gender a moc (či bezmocnost) ĆŸen v digitĂĄlnĂ­ éƙe: Kdo programuje umělou inteligenci?
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ÚVOD
Úvod
Video - 0:32 mins
KAPITOLA 1: POHLAVÍ A TECHNOLOGIE: PƘEHLED MOCENSKÉ DYNAMIKY
📖 Část 1: Úvod do problematiky pohlaví v technologii
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📖 Část 2: Role ĆŸen v programovĂĄnĂ­ a vĂœvoji AI
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📖 Část 3: Genderová zaujatost v AI a algoritmech
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đŸ€” Úkol pro vĂĄs
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💡 Inspirace pro vás
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📚 Zdroje
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KAPITOLA 2: VLIV AI NA SPOLEČENSKÉ MOCENSKÉ STRUKTURY
📖 Část 1: AI a genderová dynamika moci
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📖 Část 2: Etika AI v genderovĂ©m kontextu
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📖 Část 3: Strategie pro posĂ­lenĂ­ postavenĂ­ ĆŸen prostƙednictvĂ­m technologiĂ­
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đŸ€” Úkol pro vĂĄs
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💡 Inspirace pro vás
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📚 Zdroje
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KAPITOLA 3: ALTERNATIVY K MOCENSKÝM STRUKTURÁM V PROGRAMOVÁNÍ AI
📖 Část 1: VytváƙenĂ­ inkluzivnĂ­ch technologickĂœch prostorĆŻ
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📖 Část 2: Změny politik pro genderovou rovnost v technologiích
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📖 Část 3: BudoucĂ­ směry: Ćœeny vedoucĂ­ změnu v AI
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đŸ€” Úkol pro vĂĄs
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💡 Inspirace pro vás
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📚 Zdroje
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QUIZ
QUIZ
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Announcements Course Info
  • UNESCO. UNESCO Women for Ethical AI: Outlook Study on Artificial Intelligence and Gender. UNESCO, 2024. https://unesdoc.unesco.org/ark:/48223/pf0000391719 
  • Straza, Tiffany. Changing the Equation: Securing STEM Futures for Women. UNESCO, 2024. https://unesdoc.unesco.org/ark:/48223/pf0000391384
  • Criado Perez, Caroline. Invisible Women: Exposing Data Bias in a World Designed for Men. Abrams Press, 2019.
  • Wajcman, Judy. TechnoFeminism. Polity Press, 2004.
  • Lovelace, Ada King, Countess of. Ada, the Enchantress of Numbers: A Selection from the Letters of Lord Byron’s Daughter and Her Description of the First Computer. Narrated and edited by Betty A. Toole, Strawberry Press, 1992.
  • Beyer, Kurt W. Grace Hopper and the Invention of the Information Age. MIT Press, 2009. MIT Press
  • Light, Jennifer S. “When Computers Were Women.” Technology and Culture, vol. 40, no. 3, 1999, pp. 455–483. https://doi.org/10.1353/tech.1999.0128
  • Buolamwini, Joy. “How I’m Fighting Bias in Algorithms.” TEDxBeaconStreet, Nov. 2016. https://www.ted.com/talks/joy_buolamwini_how_i_m_fighting_bias_in_algorithms
  • “Defrag: The Feminist Internet Digital Clinic.” Somerset House. https://www.somersethouse.org.uk/whats-on/defrag-feminist-internet-digital-clinic
  • Buolamwini, Joy, and Timnit Gebru. “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.” Proceedings of Machine Learning Research, vol. 81, 2018, pp. 1–15. https://proceedings.mlr.press/v81/buolamwini18a.html
  • Dastin, Jeffrey. “Amazon Scraps Secret AI Recruiting Tool That Showed Bias against Women.” Reuters, 10 Oct. 2018. Direct Link
  • O’Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown, 2016.
  • de Miguel Beriain, Iñigo, et al. Auditing the Quality of Datasets Used in Algorithmic Decision-Making Systems. European Parliamentary Research Service, 2022. https://www.europarl.europa.eu/thinktank/en/document/EPRS_STU(2022)729541
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