ABSTRACT
This chapter starts by setting forth the promise of data analytics for social science, public policy, and related domains. It then discusses research design issues such as pseudo-objectivity, algorithmic bias and subjectivity, and exaggerated claims of ‘true believers’. The danger that ‘big data’ equates to ‘big noise’ is discussed, along with limitations of leading data science dissemination models. Next, social and ethical issues in data analytics are explored, including bias towards the privileged, discrimination, diversity issues, distortion of democratic processes, undermining of professional ethics, and issues related to privacy, profiling, and surveillance. The chapter concludes with a discussion of the transparency issue in the context of technology and power.
