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Explore all talks and presentations from ACM FAccT Conference. Dive deep into the latest insights, research, and trends from the world's leading experts.
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 future of NLP with Pascale Fung as she discusses the importance of integrating ethical values and human-centric approaches in developing advanced language technologies.
Explore algorithmic amplification's impact on news ranking, misinformation, and fact-checking. Learn about South Korea's COVID-19 misinformation response and the Facts Before Rumors campaign.
Explore the emergence of hypersocial AI and its implications for global security and peace with insights from a former California Supreme Court justice and international policy expert.
Explore digital culture, algorithmic sociality, and the impact of networked technologies on Black everyday lives with André Brock's insightful analysis of Western technoculture and Black cybercultures.
Explore the nature and justification of power in political philosophy, examining key concepts and theories that shape our understanding of political authority and legitimacy.
Explore fairness in AI and its societal implications with experts from NYU and STOP. Gain insights into ethical considerations and practical approaches for responsible AI development.
Explore the legal implications of fairness metrics in machine learning under EU non-discrimination law, examining bias preservation and its impact on algorithmic decision-making.
Explore the limitations and potential pitfalls of explainable machine learning, focusing on when to be cautious about trusting ML explanations in real-world applications.
Explore sociocultural diversity in machine learning through insights from philosophy, psychology, and organizational science. Gain valuable lessons for creating more inclusive and effective AI systems.
Explore AI model monitoring in healthcare, focusing on practical implementation, ethical considerations, and real-world challenges faced by industry professionals.
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