2021/05/07 by Dominik Dellermann, Nikolaus Lipusch, Dellermann, Dominik +7 · 4 citations
Business, Management and Accounting · Decision Sciences · Social Sciences · #Artificial Intelligence (cs.AI) #Big Data and Business Intelligence #Complex Systems and Decision Making #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Innovation, Sustainability, Human-Machine Systems
paper · pdf · doi:10.48550/arxiv.2105.03360
openalex publication_date 2021/05/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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 of 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.