Challenges of Adopting Human-Centered Intelligent Systems: An organizational learning approach

Fons Wijnhoven*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Clinical decision support systems (CDSSs) are human-centered intelligent systems (HCISs) that use codified medical expertise or large data sets for medical decision recommendations. Most analytical CDSS that exploit the opportunities of large data sets and analytic technique remain within a research and development environment and lack adoptions in clinical contexts. To understand this, we analyse CDSS adoption as an organizational learning process. We apply a model of organizational learning on the case of an analytical CDSS implementation which analyses medical data to predict the probability on sepsis for prematurely born babies to support the physicians’ decision-making on ministering antibiotics. In our discussion, we next compare our case findings with possible organizational learning challenges for the adoption of other (medical) HCISs and we draw consequences for projects of HCIS adoption in organizations.
Original languageEnglish
Title of host publicationHuman Centred Intelligent Systems
Subtitle of host publicationProceedings of KES-HCIS 2020 Conference
EditorsA. Zimmerman, R. Howlett, L. Jain
Place of PublicationSingapore
PublisherSpringer
Pages13-25
Number of pages13
ISBN (Electronic)978-981-15-5784-2
ISBN (Print)978-981-15-5783-5
DOIs
Publication statusPublished - 2021
EventKES International Conference on Human Centred Intelligent Systems, KES-HCIS 2020 - Radisson Blu Resort, Split, Croatia
Duration: 17 Jun 202019 Jun 2020
http://hcis-20.kesinternational.org/

Publication series

NameSmart Innovation, Systems and Technologies
PublisherSpringer
Volume189

Conference

ConferenceKES International Conference on Human Centred Intelligent Systems, KES-HCIS 2020
Abbreviated titleKES-HCIS 2020
CountryCroatia
CitySplit
Period17/06/2019/06/20
OtherVirtual conference
Internet address

Keywords

  • Analytics
  • Clinical decision support system
  • Artificial intelligence adoption

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