Large language models and AI tools offer transformative potential, but their use for social good brings significant privacy and security challenges. Allocators, implementers, and governments need more tools to balance impact, privacy, and transparency.

This interactive workshop will delve into real-world case studies showcasing diverse strategies for managing privacy risks like aggregation, inference, and disclosure. We'll explore organizational strategies to safeguard concerns, comply with legal requirements, and maximize social impact through AI and data science. Participants will leave with a solid understanding of how to future-proof their social impact initiatives against privacy risks in the AI era.