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Explore strategies to combat algorithmic bias and digital discrimination in the Southern US, drawing insights from real-world experiences and community-driven initiatives.
Explore cross-cultural perspectives on AI, examining diverse viewpoints and ethical considerations to broaden understanding and foster inclusive technological development.
Learn to leverage technical skills in combating public benefit cuts and austerity policies through the Benefits Tech Advocacy Hub, empowering you to make a tangible social impact.
Explore theories of change in responsible AI, examining approaches to ethical development and implementation of artificial intelligence technologies.
Explore San José's real-world implementation of AI governance in public agencies, gaining insights into challenges, strategies, and practical approaches for responsible AI deployment.
Explore cutting-edge research on participatory AI, examining how humans and machines can collaborate effectively in various domains and applications.
Explore cutting-edge research on computing in workplace environments, examining technological innovations and their impact on professional settings and productivity.
Explore the impact of technology on criminal legal and immigration systems, examining real-world experiences and critical perspectives on reform efforts and their consequences.
Explore cutting-edge techniques and methodologies for evaluating machine learning models in this comprehensive session on model assessment and performance analysis.
Explore cutting-edge research on computing applications in healthcare, covering innovative technologies and solutions to improve patient care and medical outcomes.
Hands-on exploration of large language models for researchers studying fairness, accountability, and transparency in AI systems.
Explore market-based approaches in computing through research presentations, examining innovative strategies and their impact on technology and business landscapes.
Explore participatory methods across computer science, political science, and design, examining their practices, limitations, and interdisciplinary applications for effective stakeholder engagement and collaborative problem-solving.
Explore the intersection of machine learning fairness and sociology of statistics, examining how ML evolves scientifically by moving away from metrological realism.
Explore research on measuring biases in language generation models, focusing on transgender and non-binary perspectives to promote inclusivity in AI development.
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