Enhancing non-expert understanding of Artificial Intelligence solutions through an ontology-based approach
No Thumbnail Available
Authors
Author (Corporation)
Publication date
2024
Typ of student thesis
Master
Course of study
Collections
Type
11 - Student thesis
Editors
Editor (Corporation)
Supervisor
Parent work
Special issue
DOI of the original publication
Link
Series
Series number
Volume
Issue / Number
Pages / Duration
Patent number
Publisher / Publishing institution
Hochschule für Wirtschaft FHNW
Place of publication / Event location
Olten
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
To drive AI understanding and adoption, the vast terms, concepts, and definitions around the many different dimensions and aspects of AI must be demystified for a broader non-tech-focused audience. Such as professionals with higher education who work in a digitalized business environment but have no education in computer science or similar fields. These in this context, called “non-experts” of AI, who are decision-makers and contributors in various industries, could profit from an easy, manageable, and trustworthy way to level up their own knowledge of the AI field. Specifically in the context of relevant business challenges and terms.
Keywords
Subject (DDC)
330 - Wirtschaft
Event
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Review
Open access category
License
Citation
CASTRATORI, Sarah Graziella, 2024. Enhancing non-expert understanding of Artificial Intelligence solutions through an ontology-based approach. Olten: Hochschule für Wirtschaft FHNW. Verfügbar unter: https://irf.fhnw.ch/handle/11654/49263