Assessments of the Privacy Compliance in Commercial Large Language Models

The increasing deployment of artificial intelligence systems in various applications has intensified concerns regarding their compliance with stringent privacy regulations. Addressing the critical need for robust privacy mechanisms, this research offers a novel and comprehensive evaluation of privacy compliance in two commercial large language models, ChatGPT and Claude, emphasizing automated testing, benchmarking against key privacy standards, and simulated data scenarios. Results indicate that Claude outperforms ChatGPT in several dimensions of privacy compliance, particularly in data protection, transparency, and user rights management. Detailed analysis reveals Claude's stronger alignment with regulatory requirements, facilitated through clear and accessible privacy policies and effective data anonymization practices. The study highlights areas where ChatGPT requires significant improvements, especially in data retention and user consent mechanisms, to achieve better compliance and enhance user trust. These findings demonsrate the importance of continuous monitoring and refinement of privacy practices in large language models to ensure adherence to evolving privacy standards and the safeguarding of user information.