Abstract

Human collaboration is an indispensable part of knowledge-intensive work and has long been object of analysis and design for information systems research. Collaboration describes the work of at least two individuals on shared material that is aligned to a common group goal. In order to achieve the group goal, communication, coordination and cooperation are necessary. More complex value creation systems and growing potentials of intelligent systems and agents allow an expansion of the design space towards completely new work and collaboration scenarios. IT-supported human collaboration is being expanded by human-machine collaboration, in which non-human agents act more as autonomous collaboration partners. This paradigm shift brings diverse socio-technical design challenges, ranging from specific solutions for different human-machine scenarios to a need for rethinking the methods of collaboration research and engineering. which are discussed in this article. First, the redistribution of work, due to new intelligent systems, is critically discussed and the design field in the continuum of human-machine collaboration is described by using a taxonomy. Second, various application cases are outlined, and their challenges and potentials discussed. These include i.) the use of language-based agents to facilitate the individual submission of ideas on a platform; (ii) the use of non-voice-based human-machine collaboration in autonomous driving; iii.) the use of language-based assistance systems in university teaching and learning. The article concludes with a discussion of implications for human-machine collaboration design that is relevant for designers of new collaboration scenarios with a focus on trends for advancing existing collaborative engineering methods.

Traumer F, Oeste-Reiß S, Leimeister JM (2017) Towards a future reallocation of work between humans and machines taxonomy of tasks and interaction types in the context of machine learning. International Conference on Information Systems (ICIS).CrossRefGoogle Scholar