Collaboration with Automation: Machines as Teammates
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ItemConceptualization of the Human-Machine Symbiosis – A Literature Review( 2020-01-07)The vision of a symbiotic partnership between humans and machines has existed since the 1960s. With this paper we provide the first conceptualization of the human-machine symbiosis (HMS) and make three important contributions: we present the fundamentals of HMS by focusing on objectives, requirements, and boundaries; we propose a framework for the design of HMS; and we review HMS research and, specifically, what the literature says with respect to whether HMS has already been achieved.
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ItemPractice Makes Perfect: Lesson Learned from Five Years of Trial and Error Building Context-Aware Systems( 2020-01-07)Recent advances in artificial intelligence have demonstrated that the future of work will be defined by collaborative human-machine teams. In order to be effective, human-machine teams will rely on context-aware systems to enable collaboration. In this paper, we present three lessons learned from the past five years of developing context-aware systems that we believe will improve future system design. First, that semantic activity must captured, modeled, and analyzed to enable reasoning across missions, actors, and content. Second, that context-aware systems require multiple, federated data stores to optimize system and team performance. Finally, that real-time inter-actor communications are the essential feature enabling adaptation. We close with a discussion of the influences and implications that these lessons have on human-machine teaming, and outline future research activities that will be necessary before operationalizing these systems.
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ItemThe Power of Computer-Mediated Communication Theories in Explaining the Effect of Chatbot Introduction on User Experience( 2020-01-07)Chatbots have increasingly penetrated our lives as their behavior growingly imitates a human interlocutor. This paper examines the effect of different methods of self-presentation of a chatbot on the end-user experience. An interlocutor in a computer-mediated communication (CMC) environment can either introduce itself as a chatbot, a human being, or choose not to identify itself. We conducted an experiment to compare these three methods in terms of end-user experience that comprises of social presence, perceived humanness, and service encounter satisfaction. Our data demonstrate that a chatbot that discloses its virtual identity is scored significantly lower for social presence and perceived humanness than other two choices of self-presentation. Key findings and the associated implications are discussed.
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ItemSPAM – A Process Model for Developing Smart Personal Assistants( 2020-01-07)Information technology capabilities are growing at an impressive pace and increasingly overstrain the cognitive abilities of users. User assistance systems such as online manuals try to help the user in handling these systems. However, there is strong evidence that traditional user assistance systems are not as effective as intended. With the rise of smart personal assistants, such as Amazon’s Alexa, user assistance systems are becoming more sophisticated by offering a higher degree of interaction and intelligence. This study proposes a process model to develop Smart Personal Assistants. Using a design science research approach, we first gather requirements from Smart Personal Assistant designers and theory, and later evaluate the process model with developing an Amazon Alexa Skill for a Smart Home system. This paper contributes to the existing user assistance literature by offering a new process model on how to design Smart Personal Assistants for intelligent systems.
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