This study explores the analysis of unethical text data in Korean using generative AI, particularly ChatGPT. It emphasizes the importance of constructing and understanding Korean unethical text data for AI data ethics. The research investigates the categorization of unethical text using Korean news and hate comments, employing methods like frequency analysis and topic modeling for objectivity. It also assesses ChatGPT’s ability to handle Korean unethical text, highlighting difficulties with contextspecific unethicality and new or unique Korean terms. The findings indicate the necessity for context-rich unethical text data to improve AI’s ethical responses, especially in subtle but malicious scenarios. Overall, the study underscores the significance of recognizing and addressing unethicality in the Korean language. This understanding is crucial for enhancing AI tools like ChatGPT and developing AI systems for detecting unethical behavior and verifying ethics, particularly in the Korean linguistic context.