Cyril S. Ku, Thomas J. Marlowe, Joseph R. Laracy, Jin-A Choi

Proceedings of the 26th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2022, Vol. I, pp. 47-52 (2022); https://doi.org/10.54808/WMSCI2022.01.47

Cyril S. Ku
Department of Computer Science, William Paterson University, Wayne, New Jersey, United States

Thomas J. Marlowe
Department of Mathematics and Computer Science, Seton Hall University, South Orange, New Jersey, United States

Joseph R. Laracy
Department of Systematic Theology, Department of Mathematics and Computer Science, Seton Hall University, South Orange, New Jersey, United States

Jin-A Choi
Department of Communication, William Paterson University, Wayne, New Jersey, United States

Cite this paper as:
Ku, C. S., Marlowe, T. J., Laracy, J. R., Choi, J. (2022). A Cybernetics Perspective on Data Science: Macro and Micro Views. In N. Callaos, N. Lace, B. Sánchez, M. Savoie (Eds.), Proceedings of the 26th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2022, Vol. I, pp. 47-52. International Institute of Informatics and Cybernetics. https://doi.org/10.54808/WMSCI2022.01.47

In this paper, data science is considered from a cybernetic perspective in two viewpoints. After a brief review of cybernetics, a partial conceptual view of a data science framework is provided. Several layers are identified, working from the software engineering life cycle macro perspective of a data analysis system, through production of a machine learning model to mine knowledge and predict business and product trends, to the micro perspective of a specific analysis, in this case using an artificial neural network. How the layers fit, individually and collectively, into a cybernetic system, identifying feedback loops and their interactions are described. Finally, the advantages and disadvantages of understanding the modern data science life cycle from the cybernetics perspective, and insights to be gained from this perspective are discussed.