Privacy issues arise prominently during the inappropriate transmission of information between entities. Existing research primarily studies privacy by exploring various privacy attacks, defenses, and evaluations within narrowly predefined patterns, while neglecting that privacy is not an isolated, context-free concept limited to traditionally sensitive data (e.g., social security numbers), but intertwined with intricate social contexts that complicate the identification and analysis of potential privacy violations. The advent of Large Language Models (LLMs) offers unprecedented opportunities for incorporating the nuanced scenarios outlined in privacy laws to tackle these complex privacy issues. However, the scarcity of open-source relevant case studies restricts the efficiency of LLMs in aligning with specific legal statutes. To address this challenge, we introduce a novel framework, GoldCoin, designed to efficiently ground LLMs in privacy laws for judicial assessing privacy violations. Our framework leverages the theory of contextual integrity as a bridge, creating numerous synthetic scenarios grounded in relevant privacy statutes (e.g., HIPAA), to assist LLMs in comprehending the complex contexts for identifying privacy risks in the real world. Extensive experimental results demonstrate that GoldCoin markedly enhances LLMs' capabilities in recognizing privacy risks across real court cases, surpassing the baselines on different judicial tasks.

The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances. AI generally refers to computers' ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not. But AI in medicine also raises significant legal and ethical challenges.

The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances. AI generally refers to computers' ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not. But AI in medicine also raises significant legal and ethical challenges.

The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances. AI generally refers to computers' ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not. But AI in medicine also raises significant legal and ethical challenges.

The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances. AI generally refers to computers' ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not. But AI in medicine also raises significant legal and ethical challenges.

The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances. AI generally refers to computers' ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not. But AI in medicine also raises significant legal and ethical challenges.

The use of artificial intelligence in medicine is generating great excitement and hope for treatment advances. AI generally refers to computers' ability to mimic human intelligence and to learn. For example, by using machine learning, scientists are working to develop algorithms that will help them make decisions about cancer treatment. They hope that computers will be able to analyze radiological images and discern which cancerous tumors will respond well to chemotherapy and which will not. But AI in medicine also raises significant legal and ethical challenges.