{"id":1551,"date":"2018-10-16T11:12:25","date_gmt":"2018-10-16T09:12:25","guid":{"rendered":"http:\/\/www.bise-journal.com\/?p=1551"},"modified":"2018-10-16T11:12:25","modified_gmt":"2018-10-16T09:12:25","slug":"06-2020-user-assistance-for-intelligent-systems","status":"publish","type":"post","link":"https:\/\/bise-journal.com\/?p=1551","title":{"rendered":"03\/2020 \u2013 User Assistance for Intelligent Systems"},"content":{"rendered":"

Special Issue<\/strong><\/p>\n

Intelligent systems have become ubiquitous in modern life and increasingly shift the performance of tasks away from humans (Davenport und Kirby 2016). Although this development has many advantages, the interplay between intelligent systems and humans remains a societal and technological challenge. On the one hand, taking humans out of the loop may lead to \u201cmindless\u201d ways of working and cause a range of errors due to unforeseen task complexities. On the other hand, human capabilities cannot always cope with intelligent systems\u2019 functionalities (Brynjolfsson und McAfee 2016). In sum, intelligent systems have increased their capabilities and functionalities with a rapid pace and thereby widened the gap to the humans\u2019 (cognitive) capabilities to comprehend and utilize these systems.<\/p>\n

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 decision aids, recommendation agents, virtual assistants, guidance systems, task-support systems, conversational agents, chatbots, or robo-advisors. 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<\/em>, Google<\/em>, and Microsoft<\/em>) 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 available assistance functionalities, the role of user assistance for interactive intelligent systems deserves more research.<\/p>\n

We define user assistance as a specific capability of intelligent systems that support users in performing their tasks better. Thereby, user assistance results in a human-, task-, and context-dependent augmentation of task performance. It bridges the gap between the system\u2019s functionalities and the human\u2019s individual capabilities with the goal of positively influencing task outcomes (Benyon 2014; Maedche et al. 2016). User assistance for intelligent systems can be classified along two dimensions: (1) the degree of interactivity enabled by user assistance, and (2) the degree of intelligence of user assistance. The degree of interactivity characterizes the assistance systems capability to support humans in an ongoing reciprocal and activating dialog using, potentially, different channels. Highly interactive systems are able to provide feedback and reference earlier points in communication. They furthermore allow the user to control and influence the communication process (Kiousis 2002). The degree of intelligence describes a system\u2019s capability to provide assistance to the user based on the person, the context, and the current activity. It covers aspects of artificial intelligence such as the intention to create machines with minds (Haugeland 1987) and emotional intelligence, i.e. the capabilities to manage, understand, use, and perceive emotions (Mayer et al. 2001).<\/p>\n

This special issue welcomes a diversity of submissions and is hence open for conceptual, empirical, and\/or theoretical research focusing on user assistance for intelligent systems. Thereby, we seek for manuscripts that include, but are not limited to, the following topics:<\/p>\n