Privacy Issue

Privacy concerns are increasingly central to the development and deployment of artificial intelligence, particularly in machine learning models. Current research focuses on identifying and mitigating vulnerabilities in various model architectures, including federated learning, large language models, and recommender systems, through techniques like data obfuscation, differential privacy, and secure aggregation protocols. This work is crucial for ensuring responsible AI development and deployment, balancing the benefits of advanced technologies with the fundamental right to privacy, and informing the creation of effective privacy regulations.