Finding the Unicorn: Predicting Early Stage Startup Success through a Hybrid Intelligence Method
Type
conference paper
Date Issued
2017
Author(s)
Research Team
IWI6
Abstract
Artificial intelligence is an emerging topic and will soon be able to perform decisions better than humans. In more complex and creative contexts such as innovation, however, the question remains whether machines are superior to humans. Machines fail in two kinds of situations: processing and interpreting “soft” information (information that cannot be quantified) and making predictions in “unknowable risk” situations of extreme uncertainty. In such situations, the machine does not have representative information for a certain outcome. Thereby, humans are still the “gold standard” for assessing “soft” signals and make use intuition. To predict the success of startups, we, thus, combine the complementary capabilities of humans and machines in a Hybrid Intelligence method. To reach our aim, we follow a design science research approach to develop a Hybrid Intelligence method that combines the strength of both machine and collective intelligence to demonstrate its utility for predictions under extreme uncertainty.
Language
English
Keywords
Uncertainty
wisdom of the crowd
machine learning
design science
decision making/makers
hybrid intelligence
HSG Classification
contribution to practical use / society
Event Title
International Conference on Information Systems (ICIS)
Event Location
Seoul, South Korea
Event Date
10-13 Dec 2017
Division(s)
Eprints ID
252034
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Name
JML_669.pdf
Size
591.82 KB
Format
Adobe PDF
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