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  4. The Future of Human-AI Collaboration: A Taxonomy of Design Knowledge for Hybrid Intelligence Systems
 
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The Future of Human-AI Collaboration: A Taxonomy of Design Knowledge for Hybrid Intelligence Systems

Journal
Hawaii International Conference on System Sciences (HICSS)
Type
conference paper
Date Issued
2019
Author(s)
Dellermann, Dominik
Calma, Adrian
Lipusch, Nikolaus
Weber, Thorsten
Weigel, Sascha
Ebel, Philipp  
Research Team
IWI 6
Abstract (De)
Recent technological advances, especially in the field of machine learning, provide astonishing progress on the road towards artificial general intelligence. However, tasks in current real-world business applications cannot yet be solved by machines alone. We, therefore, identify the need for developing socio-technological ensembles of humans and machines. Such systems possess the ability to accomplish complex goals by combining human and artificial intelligence to collectively achieve superior results and continuously improve by learning from each other. Thus, the need for structured design knowledge for those systems arises. Following a taxonomy development method, this article provides three main contributions: First, we present a structured overview of interdisciplinary research on the role of humans in the machine learning pipeline. Second, we envision hybrid intelligence systems and conceptualize the relevant dimensions for system design for the first time. Finally, we offer useful guidance for system developers during the implementation of such applications.
Language
English
Keywords
artificial intelligence
human-ai interaction
human-in-the-loop
hybrid intelligence
machine learning
HSG Classification
contribution to practical use / society
Event Title
Hawaii International Conference on System Sciences (HICSS)
Event Location
Maui, Hawaii, USA
Event Date
07.01.2019-12.01.2019
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/99162
Subject(s)

other research area

information managemen...

business studies

Division(s)

IWI - Institute of In...

Eprints ID
254994
File(s)
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Thumbnail Image

open.access

Name

JML_706.pdf

Size

802.21 KB

Format

Adobe PDF

Checksum (MD5)

bbb5f3d7287fe7bed7058e755e334604

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