Avoiding a Data Science Winter by Keeping the Expectations Low - Hofstetter, Matthias; Koumpis, Adamantios; Chatzidimitriou, Kyriakos (International Journal of Advanced Corporate Learning (iJAC), 2020)
In the 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.