arXiv：cs.AI· Alisa Frik, Julia Bernd, Amitis Karami, Mohammad Tahaei·· 5 小时前AI 评分30
如何为生成式 AI 设计用户反馈机制：eBay 与学术团队的原型研究
Designing the Future of User Feedback for Generative AI
AI 导读
学术研究者与 eBay 合作开展多阶段研究，评估当前业界生成式 AI 用户反馈方案，发现普遍存在反馈入口难发现、术语不清、忽视用户价值等问题。基于此，团队提出最佳实践建议，并设计测试了一款反馈收集原型工具，旨在让用户高效灵活地给出反馈，同时为产品团队提供可用格式的性能与潜在问题数据。
正文
Abstract:Post-deployment feedback from users can be a cost-effective, scalable, and representative means to monitor and improve generative AI systems and features. When implemented effectively, giving such feedback can increase users' engagement with and trust in GenAI systems. Government regulations and industry guidelines call for post-deployment user engagement, but there is little guidance on designing mechanisms that are usable for consumers and provide actionable input for product teams. We conducted a multi-phase study as a collaboration between academic researchers and eBay. Our benchmark evaluation of current industry approaches identified common issues including lack of discoverability, unclear terminology, and inattention to user value. Based on these findings, we developed best-practice recommendations and designed and tested a prototype feedback-collection tool. The tool aimed to provide users with an efficient, flexible, and positive feedback-giving experience, and provide product teams with rich data on performance and potential problems in a usable format.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.02631 [cs.AI] |
| (or arXiv:2610.02631v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.02631 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Mohammad Tahaei [view email]
[v1]
Fri, 2 Oct 2026 00:39:58 UTC (7,655 KB)
来源：arXiv：cs.AI · arxiv.org