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Register a new userGender and Representation Bias in GPT-3 Generated Stories
انحياز الجنس والتمثيل في القصص GPT-3 الناتجة
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باستخدام شكل النمذجة ومشابه الكلمة القائمة على المعجم، نجد أن القصص الناتجة عن GPT-3 تظهر العديد من الصور النمطية الجنسانية المعروفة.قصص تم إنشاؤها تصور مواضيع وأوصاف مختلفة اعتمادا على الجنس المتصور GPT-3 من الشخصية في موجه، مع أحرف أنثوية أكثر عرضة للأسرة والمظهر، ووصف بأنه أقل قوة من أحرف الذكورية، حتى عند الاقتراح بأفعال عالية الطاقةفي موجه.تجمع دراستنا أسئلة حول كيف يمكن للمرء تجنب التحيزات الاجتماعية غير المقصودة عند استخدام نماذج لغة كبيرة لرواية القصص.
Using topic modeling and lexicon-based word similarity, we find that stories generated by GPT-3 exhibit many known gender stereotypes. Generated stories depict different topics and descriptions depending on GPT-3's perceived gender of the character in a prompt, with feminine characters more likely to be associated with family and appearance, and described as less powerful than masculine characters, even when associated with high power verbs in a prompt. Our study raises questions on how one can avoid unintended social biases when using large language models for storytelling.
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