Artificial Intelligence is a fascinating discipline and application that I have been studying over the last year and recently began to investigate adapting and applying to my research projects. The discipline can be segmented into subdisciplines to include Machine Learning (e.g., Supervised Learning, Unsupervised Learning, Semi-Supervised Learning), Neural Networks, Deep Learning, etc. Artificial Intelligence emerged out of the Computer Science discipline and is applicable to all sectors and disciplines. In one of my Artificial Intelligence Foundations courses, it was surprising to learn that Dr. Herbert Simon who is revered in Public Administration, Psychology, and Economics is also revered in Computer Science. He was one of the first scholars to contribute to Artificial Intelligence before Artificial Intelligence was formerly characterized. He wrote “The Sciences of the Artificial” book which is on my reading list for the summer.

Artificial Intelligence including the subdisciplines is not a private club of the Computer Science discipline and the knowledge, skills, and tools can be adapted by other disciplines (e.g., Social Sciences). The adaptation of the knowledge, skills, and tools (e.g., programming languages, models) to other disciplines is not easy but achievable. Artificial Intelligence is a disruption and there are jobs that are negatively impacted but there are millions of jobs created by Artificial Intelligence and other STEM disciplines (e.g., Data Science) which requires human resources. There is a global human resource shortage for the continuing newly created jobs. Google hired its first Chief Decision Scientist integrating Data Science and Artificial Intelligence less than two years ago. A couple of months ago, I was listening to an episode of SuperDataScience podcast hosted by Kirill Eremenko and learned about Chief Algorithms Officer positions.

The global human resource shortage is so dire that organizations across sectors are willing to hire individuals and pay for their training to develop the skills that are needed for the organization. I have always believed in retooling, reskilling, and expanding my arsenal throughout my overall career. I have adapted the philosophy of either get on board or get left behind. It is not enough to know about Thomas Hobbes, John Locke, Jean Jacque Rousseau, and the Social Contract theory. My arsenal includes Data Science and R programming language and I am investigating how I can adapt and apply Machine Learning algorithms (e.g., k-nearest neighbors, Bayes theorem, decision trees, random forests) to my research projects. Machine Learning can be done in R contrary to the popular belief it can only be done in the Python programming language. Yes, there is the R ecosystem vs the Python ecosystem. The arsenal described is underrepresented in the Social Sciences but can solve complex Social Science problems.