ركز العمل الحديث في معالجة اللغة الطبيعية (NLP) على التحديات الأخلاقية مثل الفهم والتخفيف من التحيز في البيانات والخوارزميات؛تحديد المحتوى المرفترض مثل خطاب الكراهية والقوالب النمطية واللغة المسيئة؛وبناء أطر من أجل تحسين تصميم النظام وممارسات معالجة البيانات.ومع ذلك، لم يكن هناك قليل من النقاش حول المؤسسات الأخلاقية التي تكمن وراء هذه الجهود.في هذا العمل، ندرس نظرية أخلاقية واحدة، وهي أخلاقيات غير نائبة، من منظور NLP.على وجه الخصوص، نركز على مبدأ التعميم واحترام الحكم الذاتي من خلال الموافقة المستنيرة.نحن نقدم أربع دراسات حالات لإظهار كيفية استخدام هذه المبادئ مع أنظمة NLP.نوصي أيضا بالتوجيهات لتجنب القضايا الأخلاقية في هذه الأنظمة.
Recent work in natural language processing (NLP) has focused on ethical challenges such as understanding and mitigating bias in data and algorithms; identifying objectionable content like hate speech, stereotypes and offensive language; and building frameworks for better system design and data handling practices. However, there has been little discussion about the ethical foundations that underlie these efforts. In this work, we study one ethical theory, namely deontological ethics, from the perspective of NLP. In particular, we focus on the generalization principle and the respect for autonomy through informed consent. We provide four case studies to demonstrate how these principles can be used with NLP systems. We also recommend directions to avoid the ethical issues in these systems.
References used
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