Dartmouth Events

Abstract: The rapid growth of artificial intelligence (AI) has created a complex ecosystem where competing interests—governments, creators, AI companies, and users—intersect. This power dynamic has sparked tension between innovation, regulation, and individual rights. Balancing and accommodating the power tussle among stakeholders is essential for the sustainable development of AI. Today, the current ecosystem concentrates most power and control in the hands of a few entities, resulting in unintended harms and suboptimal development. 

My research tackles these challenges by developing technical solutions to mitigate the harms of AI misuse and restore power balance among stakeholders. I will begin by discussing my research on protecting creators from unauthorized style mimicry. Then, I will present a proactive data protection system that employs clean-label data poisoning techniques to prevent unwanted data scraping. Finally, I will discuss maximizing external impact of my work and my vision for building a more collaborative AI ecosystem.

Speaker’s Bio: 

Shawn Shan is a PhD candidate in Computer Science at University of Chicago, advised by Ben Zhao and Heather Zheng. His research lies at the intersections of security and machine learning with a focus on safeguarding AI systems and addressing the harms from AI misuse. He is a recipient of MIT Tech Review Innovator of the Year, MIT Tech Review 35 Under 35, Forbes 30 Under 30, USENIX Internet Defense Prize, and Distinguished Paper Awards at USENIX Security and ACM CCS.