Power to the People: The Role of Humans in Interactive Machine Learning
Power to the People: The Role of Humans in Interactive Machine Learning
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DOI：
10.1609/aimag.v35i4.2513
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发表时间：
2014-12-01
期刊：
影响因子：
0.9
通讯作者：
Kulesza, Todd
中科院分区：
文献类型：
--
作者：
Amershi, Saleema;Cakmak, Maya;Kulesza, Todd
可以从最终用户中互动学习的系统正在迅速变得广泛。直到最近，这一进步主要是由于机器学习的进步所推动的。但是，越来越多的研究人员意识到研究这些系统用户的重要性。在本文中，我们促进了这种方法，并演示了它如何导致更好的用户体验和更有效的学习系统。我们提出了许多案例研究，这些案例研究表明了交互性如何导致系统与用户之间的紧密耦合，例如某些现有系统无法解释用户的方式，并探索学习系统与用户交互的新方法。在瞥见了迄今为止取得的进步之后，我们讨论了我们在向前迈进的一些挑战。
Systems that can learn interactively from their end-users are quickly becoming widespread. Until recently, this progress has been fueled mostly by advances in machine learning; however, more and more researchers are realizing the importance of studying users of these systems. In this article we promote this approach and demonstrate how it can result in better user experiences and more effective learning systems. We present a number of case studies that demonstrate how interactivity results in a tight coupling between the system and the user, exemplify ways in which some existing systems fail to account for the user, and explore new ways for learning systems to interact with their users. After giving a glimpse of the progress that has been made thus far, we discuss some of the challenges we face in moving the field forward.