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SUMMARY:Testing AI Safety: Why Current Guardrails Fail to Stop Social Bias with Anna-Maria Gueorgiueva | AI & Equality Pub-Talk
DESCRIPTION:Access paper: https://arxiv.org/abs/2512.19238 \nHow do large language models understand the lived experiences of stigmatized groups\, and when does this understanding differ from the human perspective? Can this lead to bias\, and if so\, do our existing safety tools help mitigate such bias? This work investigated open-source language models for bias against 93 stigmatized groups\, identifying that specific types of biases (especially those deemed by humans to be ‘threatening’ such as having HIV or a criminal record) experience significantly more bias than other types of stigmatized identities. To attempt to remedy this\, we test guardrail models\, models from leading technology companies that are meant to identify discriminatory or bias-eliciting inputs and mitigate harmful outputs. This talk will report on our findings\, identifying where existing guardrail models fail and discussing technical and legal solutions. \nAbout the speaker:\nAnna-Maria Gueorguieva is a PhD student at the University of Washington Information School and holds B.A. in Data Science and Legal Studies from UC Berkeley. Her research focuses on AI evaluations for social and political impacts and AI regulation. Her work lies at the intersection of empirical methods to investigate AI usage and behavior in combination with the necessary AI regulations needed to limit and remedy harm.\n\n\n\n\n\n\n\n\n\n\n\nRegister here via our community on Circle
URL:https://aiequalitytoolbox.com/event/testing-ai-safety-why-current-guardrails-fail-to-stop-social-bias-with-anna-maria-gueorgiueva-ai-equality-pub-talk/
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DTSTART;TZID=Europe/London:20260630T150000
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SUMMARY:Moving Beyond Big Tech: Blueprints for Community-Led Language AI with Claudia Pozo | AI & Equality Pub-Talk
DESCRIPTION:Paper: TBD (available in June) \nThe digital world suffers from a profound linguistic disparity\, particularly in Africa where a lack of local language content and traditional\, Global North-led language technology models fail to meet community needs\, often resulting in data extraction and inequitable solutions. In an 18-month research project\, in collaboration with the Distributed AI Research Institute (DAIR)\, we highlight a powerful alternative: a growing grassroots movement of community-based language technology initiatives across Africa that adopt a bottoms-up approach\, prioritizing local needs and incorporating indigenous philosophies. This approach centers technology as an act of collective creation and community survival\, yet it faces significant challenges\, including a heavy reliance on Global North funding that can conflict with goals for self-determination and critical concerns around data governance and ownership in regions with underdeveloped legal frameworks. Ultimately\, the research advocates for a fundamental shift in technological practice to support these community-centered development models\, providing blueprints for the Global Majority to decolonize AI. \nAbout the speaker:\nClaudia Pozo is Language Justice Co-Lead at Whose Knowledge? She’s a South American brown feminist\, multifaceted activist\, researcher\, social scientist and strategist\, whose work is grounded in knowledge and language justice. She holds an MPhil in Development Studies and a BA in Communications. \n\n\nRegister here via our community on Circle
URL:https://aiequalitytoolbox.com/event/moving-beyond-big-tech-blueprints-for-community-led-language-ai-with-claudia-pozo-ai-equality-pub-talk/
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