Intelligent systems have become ubiquitous in modern life and increasingly shift the performance of tasks away from humans (Davenport and Kirby 2016). Although this development has many advantages, the interplay between intelligent systems and humans remains a societal and technological challenge (Maedche et al. 2019; Seeber et al. 2020). Taking humans out of the loop may lead to ‘‘mindless’’ ways of working and cause a range of errors due to unforeseen task complexities. Furthermore, human capabilities cannot always cope with intelligent systems’ functionalities (Brynjolfsson and McAfee 2016). In sum, intelligent systems have increased their capabilities and functionalities with a rapid pace and thereby widened the gap to the humans’ (cognitive) capabilities to comprehend and utilize these systems. One way to support humans in the usage of intelligent systems is providing user assistance that can be instantiated in many different forms such as conversational agents, guidance systems, recommendation agents, robo-advisors, and virtual assistants. Many contemporary user assistant systems rely on some form of either speech-based or textbased conversational user interface, both for receiving input from and delivering output to users using natural language processing (Maedche et al. 2019). Recent assistance functionalities in the private life context (e.g., navigation and mobility assistants or smart home assistants) have demonstrated their usefulness. Furthermore, technology giants (e.g., Amazon, Google, and Microsoft) have announced to release even smarter digital assistants to the market. In an organizational context, recent assistance functionalities support users in semi-automatic invoice processing and intelligent calendar management. In light of these increasingly powerful assistance functionalities, the role of user assistance for interactive intelligent systems deserves more research. Following earlier works by Benyon (2014) and Maedche et al. (2016), we suggest the following definition.

中文翻译：

---

智能系统的用户协助

智能系统在现代生活中无处不在，并且越来越多地将任务的表现从人类转移出去（Davenport 和 Kirby 2016）。尽管这种发展具有许多优势，但智能系统与人类之间的相互作用仍然是一个社会和技术挑战（Maedche 等人，2019 年；Seeber 等人，2020 年）。将人类排除在循环之外可能会导致“无意识”的工作方式，并由于不可预见的任务复杂性而导致一系列错误。此外，人类的能力并不总是能够应对智能系统的功能（Brynjolfsson 和 McAfee 2016）。总而言之，智能系统以快速的速度增加了它们的能力和功能，从而扩大了人类理解和利用这些系统的（认知）能力的差距。支持人类使用智能系统的一种方法是提供可以以多种不同形式实例化的用户帮助，例如对话代理、指导系统、推荐代理、机器人顾问和虚拟助手。许多当代用户助理系统依赖于某种形式的基于语音或基于文本的对话用户界面，用于使用自然语言处理接收来自用户的输入并向用户提供输出（Maedche 等人，2019 年）。最近在私人生活环境中的辅助功能（例如，导航和移动助手或智能家居助手）已经证明了它们的实用性。此外，科技巨头（例如亚马逊、谷歌和微软）已经宣布向市场发布更智能的数字助理。在组织环境中，最近的辅助功能支持用户进行半自动发票处理和智能日历管理。鉴于这些日益强大的辅助功能，用户辅助在交互式智能系统中的作用值得更多研究。遵循 Benyon (2014) 和 Maedche 等人的早期作品。（2016），我们建议以下定义。