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  4. Avoiding a Data Science Winter by Keeping the Expectations Low
 

Avoiding a Data Science Winter by Keeping the Expectations Low

URI
https://arbor.bfh.ch/handle/arbor/41886
Version
Published
Date Issued
2020-12-15
Author(s)
Hofstetter, Matthias  
Koumpis, Adamantios  
Chatzidimitriou, Kyriakos
Type
Article
Language
English
Subjects

data science

Artificial Intelligen...

Machine Learning

Abstract
In this paper we present and discuss some aspects related to what we consider as some of the most important corporate challenges of Data Science, AI and Machine Learning regarding both human talents and business. We examine the case of a discussion that took place over Quora and in particular we focus on an answer we have selected as indicative of a potentially threatening situation for the sustainable development of the Data Science, AI and Machine Learning disciplines as well as the growth of the respective demand and supply sides and the corresponding ecosystem these form. We then make an attempt to examine the setting by means of analyzing the case, using as our guide the provided narrative.
Subjects
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
DOI
10.24451/arbor.13901
https://doi.org/10.24451/arbor.13901
Publisher DOI
10.3991/ijac.v13i4.16933
Journal
International Journal: Advanced Corporate Learning
ISSN
1867-5565
Publisher URL
https://doi.org/10.3991/ijac.v13i4.16933
Organization
Institut Digital Enabling (IDE)  
Institut Digital Technology Management  
Volume
13
Issue
4
Publisher
International Association of Online Engineering (IAOE)
Submitter
KoumpisA
Citation apa
Hofstetter, M., Koumpis, A., & Chatzidimitriou, K. (2020). Avoiding a Data Science Winter by Keeping the Expectations Low. In International Journal: Advanced Corporate Learning (Vol. 13, Issue 4). International Association of Online Engineering (IAOE). https://doi.org/10.24451/arbor.13901
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Name

AI Winter - Hofstetter et al 16933-61939-1-PB.pdf

License
Attribution 4.0 International
Version
published
Size

818.77 KB

Format

Adobe PDF

Checksum (MD5)

2dc085b3c8f8eb55f3bba76260bfc52f

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