Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation

التفاصيل البيبلوغرافية
العنوان: Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation
المؤلفون: Lai, Vivian, Carton, Samuel, Bhatnagar, Rajat, Liao, Q. Vera, Zhang, Yunfeng, Tan, Chenhao
سنة النشر: 2022
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
الوصف: Despite impressive performance in many benchmark datasets, AI models can still make mistakes, especially among out-of-distribution examples. It remains an open question how such imperfect models can be used effectively in collaboration with humans. Prior work has focused on AI assistance that helps people make individual high-stakes decisions, which is not scalable for a large amount of relatively low-stakes decisions, e.g., moderating social media comments. Instead, we propose conditional delegation as an alternative paradigm for human-AI collaboration where humans create rules to indicate trustworthy regions of a model. Using content moderation as a testbed, we develop novel interfaces to assist humans in creating conditional delegation rules and conduct a randomized experiment with two datasets to simulate in-distribution and out-of-distribution scenarios. Our study demonstrates the promise of conditional delegation in improving model performance and provides insights into design for this novel paradigm, including the effect of AI explanations.
Comment: 18 pages, 44 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2204.11788
رقم الأكسشن: edsarx.2204.11788
قاعدة البيانات: arXiv