ABSTRACT. Despite the relevance of big data for automated algorithmic decision-making processes, only limited research has been conducted on this topic. Using and replicating data from Deloitte, Pew Research Center, and Statista, we performed analyses and made estimates regarding % of social media users who say it is acceptable for social media sites to use data about them and their online activities to recommend events in their area/recommend someone they might want to know/show them ads for products and services/show them messages from political campaigns (by age group), % of Internet users worldwide who believe that selected algorithms are unbiased, and % of U.S. adults who say that it is possible for computer programs to make decisions without human bias/computer programs will always reflect bias of designers (by age group). The results of a study based on data collected from 5,600 respondents provide support for our research model. Using the structural equation modeling and employing the probability sampling technique, we gathered and analyzed data through a self-administrated questionnaire.

Keywords: big data governance; automation; algorithmic decision-making process

How to cite: Kovacova, Maria, Tomas Kliestik, Aurel Pera, Iulia Grecu, and Gheorghe Grecu (2019). “Big Data Governance of Automated Algorithmic Decision-Making Processes,” Review of Contemporary Philosophy 18: 126–132. doi:10.22381/RCP1820196

Received 11 March 2019 • Received in revised form 12 July 2019
Accepted 14 July 2019 • Available online 29 July 2019