Privacy-Accountable Large Language Model-Integrated System
The proliferation of large language model-integrated systems (LLMSs) e.g., healthcare chatbots or personal virtual assistants) has ushered in a new era of technological advancements and transformations across numerous aspects of our daily lives. These LLMSs, equipped with sophisticated algorithms and vast datasets, are instrumental in powering innovative solutions across diverse domains, from healthcare and finance to entertainment and communications. These systems have a remarkable capacity to understand and generate human-like text for tasks ranging from language translation to content generation. However, this rapid integration of large language model (LLMSs) into our lives has not occurred without raising important concerns, most notably in the realm of privacy. In this project, Liao argues that a privacy-accountable LLMS is the solution to implement proactive privacy-enhancing measures, continuously enforce privacy accountability, as well as fostering responsible data usage and privacy protection.
The Luddy Faculty Fellows program, funded as part of a transformative, $60 million gift from Fred Luddy in 2019, is designed to support excellence in research that is—or promises to be—important, imaginative, or timely.