Big Data: Social Processes and Ethical Issues

Aim

After completion of the course, the student should at an advanced level be able to:

• identify and examine ethical issues involved in the use of large data troves in commercial and non-commercial settings
• analyse the social tensions and mutual benefits arising between those who contribute big data observations, organizations who collect data, and social actors using data to inform decision making
• formulate models of social behaviours that lead to the production of large data archives and engagement with digital platforms that generate these data
• design ethical methodological frameworks for collection, usage, and analysis of data
• critizise the use of digital data in social analysis in terms of bias, external validity, representativeness, and related issues
• analyse case studies exploring contemporary issues of big data collection, use, and analysis

Content

The course is about ethical issues related to the use of big data. It also considers social processes involving diverse actors who interact with digital platforms, produce and store big data, and analyse those data. Issues related to individual privacy, anonymity, and confidentiality are discussed. Unique ethical concerns that arise from the production of big data are scrutinized, including representativeness, sample selection, non-human and bad faith actors, and the reproduction of social biases through AI and machine learning. Social research and organizational decision-making processes that rely on big data are critiqued on this basis. The course also investigates the motivations, of organizations collecting and making use of big data directly or indirectly for profit and decision-making. These issues are explored through contemporary case studies.