Data Science and Ethics

Abstract

Data Science today profoundly influences how business is done in fields as diverse as the life sciences, smart cities, and transportation. Ethics in this study is defined as shared values that has helped humanity differentiate right from wrong; and data science is narrated as an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structured and unstructured data. Data ethics have really become a real issue since different organizations have different working operational standards and rules guiding resourceful data. Also, due to the spark increase in data, majority of the organizations do not understand the importance of data they produce regularly. Hence, the purpose of this study paved way to establish general acceptable and basic guidelines for the use of data amongst data scientists and data practitioners. To establish these guidelines, a systematic literature review approach was used to review some related literatures. Six (6) professional parastatals were examined, in which Four (4) of these professional parastatals were discovered to have similar guidelines with the basic guidelines established in this study. We scrutinized the existing similar guidelines and perceive the need to present it in our study. This was based on the discovery of similar guidelines from the sampled data science parastatals; the approximation of 67% similarity guidelines was observed which passes a threshold of what we termed to be an accepted guideline. The established guidelines can be used by organizations and data-related professions to develop explicit internal policies, procedures, guidelines and best practices for data ethics.

Keywords: Algorithms, Artificial intelligence, Blockchain, Data science, Ethics, Microtargeting.

DOI: 10.7176/CEIS/11-5-02

Publication date:September 30^th 2020