Repository logo
  • English
  • Deutsch
Log In
or
  1. Home
  2. HSG CRIS
  3. HSG Publications
  4. Opening the Black Box of Music Royalties with the Help of Hybrid Intelligence
 
  • Details

Opening the Black Box of Music Royalties with the Help of Hybrid Intelligence

Journal
Hawaii International Conference on System Sciences (HICSS)
Type
conference paper
Date Issued
2021-01
Author(s)
Elshan, Edona  
Engel, Christian  
Ebel, Philipp  
DOI
10.24251/HICSS.2021.671
Research Team
IWI6
Abstract
The ever-increasing complexity of the music industry and the intensified resentment of artists towards collecting societies call for a transformation and a change of behavior within the music ecosystem. This article introduces a hybrid intelligence system, that ameliorates the current situation by combining the intelligence of humans and machines. This study proposes design requirements for hybrid intelligence systems in the music industry. Using a design science research approach, we identify design requirements both inductively from expert interviews and deductively from theory and present a first prototypical instantiation of a respective hybrid intelligence system. Overall, this shall enrich the body of knowledge of hybrid intelligence research by transferring its concepts into a new context. Furthermore, the identified design requirements shall serve as a foundation for researchers and practitioners to further explore and design hybrid intelligence in the music industry and beyond.
Language
English
Keywords
hybrind intelligence
music industry
blackbox
artificial intelligence
HSG Classification
contribution to scientific community
Publisher place
Kauai, USA
Event Title
Hawaii International Conference on System Sciences (HICSS)
Event Location
Kauai, USA
Event Date
5-8 Jan 2021
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/110755
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

Eprints ID
263195
File(s)
Loading...
Thumbnail Image

open.access

Name

JML_827.pdf

Size

579.18 KB

Format

Adobe PDF

Checksum (MD5)

0c321786460dcd897b492eb10414dc0f

here you can find instructions and news.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback