August 13-15, 2025
Toyota Technological Institute at Chicago
https://sites.google.com/ttic.edu/incentivesdatasharing/home
Submission deadline: July 31, 2025
Registration deadline: July 31, 2025
Machine Learning (ML) has achieved remarkable milestones in recent years, but its future hinges on a robust, ethically grounded, and well-incentivized data infrastructure. The next era of AI innovation requires specialized data that is scarce, proprietary, or sensitive (e.g., medical records, autonomous vehicle data, pharmaceutical test results). Collecting such data is cost and labor-intensive and subject to strict privacy and legal constraints. Simultaneously, the era of “free” or lightly regulated data (e.g., scraped from the public internet) is drawing to a close as copyright and user consent concerns rise — evidenced by legal challenges to large generative models and platform restrictions on web scraping. Taken together, these developments underscore the need for a new AI paradigm — one in which data rights are respected, data owners receive fair compensation, and valuable datasets are shared and reused to unlock novel applications. This raises the central question we want to address in our workshop: “How can we design incentive mechanisms to promote data sharing while safeguarding privacy, fairness, and intellectual property?”
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