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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.
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.
Explore techniques for balancing transparency and accuracy in predictive decision-making, focusing on strategic prediction methods for ethical and effective data-driven solutions.
Explore the legal implications of fairness metrics in machine learning under EU non-discrimination law, focusing on bias preservation and its impact on algorithmic decision-making.
Explore fairness in AI and its societal implications through expert insights on ethical considerations, surveillance technology, and responsible data practices.
Crash course on integrating ethical thinking in tech education, covering motivation, support, and expansion strategies for educators to foster responsible innovation.
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