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Sociocultural Diversity in Machine Learning - Lessons from Philosophy, Psychology, and Organizational Science

Association for Computing Machinery (ACM) via YouTube

Overview

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Explore the critical intersection of sociocultural diversity and machine learning in this comprehensive tutorial presented at FAccT 2021. Delve into valuable insights drawn from philosophy, psychology, and organizational science to understand the impact of diversity on AI systems. Learn from experts Sina Fazelpour (CMU) and Maria De-Arteaga (U of Texas, Austin) as they guide you through key concepts and practical applications. Gain a deeper understanding of how sociocultural factors influence machine learning algorithms and their outcomes. Discover strategies for promoting inclusivity and mitigating biases in AI development. Engage with cutting-edge research and real-world examples that highlight the importance of diversity in shaping ethical and effective machine learning systems. Enhance your knowledge and skills to create more equitable and robust AI solutions that consider the complexities of human diversity.

Syllabus

Translation Tutorial: Sociocultural diversity in machine learning:

Taught by

ACM FAccT Conference

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