AI solutions seem to appear in any and all application domains. As AI becomes more pervasive, the importance of quality assurance increases. Unfortunately, there is no consensus on what artificial intelligence means and interpretations range from simple statistical analysis to sentient humanoid robots. On top of that, quality is a notoriously hard concept to pinpoint. What does this mean for AI quality? In this paper, we share our working definition and a pragmatic approach to address the corresponding quality assurance with a focus on testing. Finally, we present our ongoing work on establishing the AIQ Meta-Testbed.

中文翻译：

---

AIQ 元测试平台：务实地连接学术 AI 测试和工业 Q 需求

AI 解决方案似乎出现在任何和所有应用领域。随着人工智能变得越来越普遍，质量保证的重要性也越来越高。不幸的是，对于人工智能的含义和解释范围从简单的统计分析到有知觉的人形机器人，还没有达成共识。最重要的是，质量是一个众所周知的难以确定的概念。这对 AI 质量意味着什么？在本文中，我们分享了我们的工作定义和务实的方法，以解决相应的质量保证，重点是测试。最后，我们介绍了我们正在进行的建立 AIQ 元测试平台的工作。