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  • Home
  • A+ Alliance
    • About A+ Alliance
    • Our Ecosystem
    • A+ Advisory Board
    • A+ Declaration
  • Feminist AI
    • Gender & AI Innovation Collective
    • fa+ir Executive Summary
    • About fA+Ir 2021-2024
    • Feminist Artificial Intelligence
  • Global Directory
  • News
  • A+ Events
  • Resources
    • Feminist AI Network Papers
    • Feminist AI PubPub
    • Webinars
    • Fa+ir Global Webinars
    • Algorithms 101 Webinars
    • AI4D Knowledge Synthesis Webinars
  • Join Us
  • 2026 Call for Applications | GAIC
3 events found.

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  • November 2024

  • Tue 12

    Open Studio: AI & Health, thinking through maintenance, repair and response-ability | Amina Soulimani

    Featured 12 November, 2024 @ 4:00 pm - 5:00 pm

    This open studio will focus on exploring the multiple ways through which we can understand the entanglement of repair and maintenance with visionary aspirations around smart hospitals. By revisiting earlier and contemporary Feminist STS texts, new materialism, phenomenology and leaning on insights from the field, Amina will share insights emerging from her ongoing PhD research. Presenting Morocco as a case study, this talk shall explore further the dimensions that waiting takes in environments that run through foreign software in local hospitals. 

  • Mon 18

    Open Studio: Much Distress and Little Relief | Jamie Fuller

    Featured 18 November, 2024 @ 4:00 pm - 5:00 pm

    Earlier this year, predictive optimization was introduced into South Africa's social grant system to detect and counter fraud. As a result, thousands (and counting) of the country’s most financially vulnerable have been mistakenly excluded from receiving their grant payment. This open studio unpacks the case study, explaining what went wrong and reflecting on a more productive use of AI. While AI may be most alluring in the resource-constrained realities of developing countries, it is precisely in such contexts that it poses the greatest threat.

  • December 2024

  • Mon 2

    Open Studio: Can Bias in LLMs Be Used for Good? | Francesca Lucchini Wortzman

    Featured 2 December, 2024 @ 4:00 pm - 5:00 pm

    It is a well-known fact that LLMs express harmful biases in their predictions. The main source comes from the training datasets, which are too large and expensive to check thoroughly. In this open studio, Francesca Lucchini will explore how we can leverage the bias in LLMs and use them to examine massive datasets, discovering starting points for a data audit.

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