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Mensch-Maschine-Kollaboration: Grundlagen, Gestaltungsherausforderungen und Potenziale für verschiedene Anwendungsdomänen

Human-Machine Collaboration: Foundations, Design Challenges and Potentials for Multiple Areas of Application

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Zusammenfassung

Menschliche Zusammenarbeit ist ein unverzichtbarer Bestandteil wissensintensiver Arbeit und längst Analyse- und Gestaltungsgegenstand wirtschaftsinformatischer Forschung. Kollaboration als Form menschlicher Zusammenarbeit, beschreibt die Arbeit von mindestens zwei Individuen an gemeinsamem Material, die auf ein gemeinsames Gruppenziel ausgerichtet ist. Zur Erreichung des Gruppenziels sind Kommunikation, Koordination und Kooperation notwendig. Zunehmend wird menschliche durch Mensch-Maschine-Kollaboration erweitert, in der nicht-menschliche Agenten als autonom handelnde Kollaborationspartner auftreten, wodurch sich neuartige Arbeits- und Kollaborationsszenarien ergeben. Dieser Paradigmenwandel bringt vielfältige sozio-technische Gestaltungsherausforderungen mit sich. Diese reichen von konkreten Anwendungen für Mensch-Maschine-Konstellationen bis hin zur Weiterentwicklung des Methodenkanons der Kollaborationsforschung und insbesondere des sog. Collaboration Engineering, die in diesem Beitrag diskutiert werden. Zunächst wird kritisch die Neuverteilung von Arbeit diskutiert, die durch intelligente Systeme möglich wird und anhand einer Taxonomie das Gestaltungsfeld im Kontinuum Mensch-Maschine-Kollaboration aufgezeigt. Anschließend werden verschiedene Anwendungsfälle skizziert sowie deren Herausforderungen und Potenziale diskutiert. Die Anwendungsfälle umfassen i.) sprachbasierte Agenten zur Facilitation von vormals individueller Ideengenerierung; ii.) nicht-sprachbasierte Mensch-Maschine-Kollaboration im Bereich des autonomen Fahrens; iii.) sprachbasierte Assistenzsysteme im universitären Lehren und Lernen. Der Artikel schließt mit einer für Designer neuer Kollaborationsszenarien relevanten Diskussion von Implikationen für die Gestaltung der Mensch-Maschine-Kollaboration mit Fokus auf Trends hinsichtlich der Weiterentwicklung existierender Methoden des Collaboration Engineerings.

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.

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Correspondence to Eva A. C. Bittner.

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Bittner, E.A.C., Oeste-Reiß, S., Ebel, P.A. et al. Mensch-Maschine-Kollaboration: Grundlagen, Gestaltungsherausforderungen und Potenziale für verschiedene Anwendungsdomänen. HMD 56, 34–49 (2019). https://doi.org/10.1365/s40702-018-00487-1

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