This study evaluates how three AI models—ChatGPT, DeepSeek, and Clova X—detect and respond to gender-biased expressions in Korean. Clova X exhibited the highest accuracy in identifying discriminatory language, followed by ChatGPT, while DeepSeek performed the poorest. While terms like “kimchi girl” and “doenjang girl” were correctly recognized, phrases such as “female doctor” and “maiden work” were often misinterpreted. ChatGPT and DeepSeek occasionally provided inaccurate definitions, raising concerns about misinformation. Interestingly, DeepSeek performed best when interpreting sexist proverbs, although the overall differences across models were minor. All three models generally succeeded in recognizing biased expressions in conversational contexts, but DeepSeek struggled with non-standard sentence formats, leading to delays or missing responses. These results reveal current limitations in generative AI’s ability to process culturally specific and nuanced language. This study emphasized the need to incorporate more diverse Korean language data and up-to-date linguistic research in AI training. As generative AI tools become more integrated into everyday communication, improving their ability to detect and respond to gender biases is crucial for fostering fair and responsible language technologies.

Abstract
1. 머리말
2. 성차별 단어의 인식과 뜻풀이
3. 성차별 속담의 인식과 대응
4. 성차별 관용구 사용에 대한 인식과 대응
5. 맺음말
참고문헌

• 이정복(Professor, Division of Culture & Arts, Daegu University, 201 Daegudae-ro, Gyeongsan-si, Gyeongsangbuk-do 38453 Korea) | Jeongbok Lee