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Explore how ordinary people can collectively combat bias in artificial intelligence systems through this 21-minute conference talk from TDF 2025. Learn the fundamentals of machine learning and understand how AI systems can develop unfair treatment patterns, particularly affecting underrepresented groups in critical decisions like job applications, loan approvals, and content curation. Discover why existing fairness solutions developed by researchers remain largely unused by companies due to performance concerns and limited legal requirements. Examine the potential for coordinated collective action by users whose data feeds these AI systems, and review initial research findings demonstrating how small, organized minorities can influence AI behavior toward more equitable outcomes. Gain insights into the intersection of technology, social justice, and grassroots activism in addressing algorithmic bias.
