تقرير
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
| العنوان: | Effective Human-AI Teams via Learned Natural Language Rules and Onboarding |
|---|---|
| المؤلفون: | Mozannar, Hussein, Lee, Jimin J, Wei, Dennis, Sattigeri, Prasanna, Das, Subhro, Sontag, David |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction |
| الوصف: | People are relying on AI agents to assist them with various tasks. The human must know when to rely on the agent, collaborate with the agent, or ignore its suggestions. In this work, we propose to learn rules, grounded in data regions and described in natural language, that illustrate how the human should collaborate with the AI. Our novel region discovery algorithm finds local regions in the data as neighborhoods in an embedding space where prior human behavior should be corrected. Each region is then described using a large language model in an iterative and contrastive procedure. We then teach these rules to the human via an onboarding stage. Through user studies on object detection and question-answering tasks, we show that our method can lead to more accurate human-AI teams. We also evaluate our region discovery and description algorithms separately. Comment: NeurIPS 2023 Spotlight |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2311.01007 |
| رقم الأكسشن: | edsarx.2311.01007 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |