Act Now: A Call to Action for Scholarly Preparation in Mathematics Among Nurse Scientists - Claire Su-Yeon Park (Journal of Learning and Teaching in Digital Age, 2018)
“Data science”—an interdisciplinary science encompassing statistics, mathematics, engineering, computer science, informatics, and/or decision science to elicit evidence-based informed shared decision-making rationales among parties (O’Connor, 2018; Park, 2018a, 2018b)—has grown by leaps and bounds since 2016 when Google DeepMind’s AlphaGo revealed its exceptional performance beyond human capability. Further, “data science” is now evolving bi-exponentially all around the world. The leading Industry-University Collaboration initiatives for Artificial Intelligence (AI)-centered research include the institutions of (1) Google and University of Toronto (the Vector Institute), (2) Google DeepMind and University of Alberta, (3) IBM and Massachusetts Institute of Technology, and (4) Microsoft and University of Montreal and are expected to promote AI’s high-speed development (Bushey, 2017), improving the process of scientific discovery and the quality of decision-making given unpredictable conditions and advancing a data‐driven economy (Ahalt et al., 2014; Park & Glenn, 2017). Such a consortium heralds that academic, economic, and sociological innovation/transformation would ensue sequentially and concurrently. Dare we dream how far science can go?