Research Ethics in Digital Social Sciences

Since last decade, digital technologies have revolutionized the social science research, due to un-limited access to large-scale behavioral data, computational modelling, and analysis using AI. However, moral issues of privacy, monitoring, algorithmic prejudice, assent, and data breach have emerged simultaneously. Current study explores the relationship between technology ethics, and digital social science, suggesting that methodological innovation in social science is inextricably linked with normative ethical issues. The study explores surveillance capitalism, data ethics, and algorithmic accountability to examine the technological and ethical shifts towards reshaping digital social science. Digital social science can focus pattern recognition over meaningful explanation if it’s does not use a strong theoretical foundation and methodological reflexivity. The study highlights that research ethics boards and regulations, needs to be adjusted to computational research environments. An ethically-centered digital social science, needs transparency, collaborative data stewardship and responsible use of AI. The future of digital social science hinges on combining technological innovation with ethical considerations, with the aim of not sacrificing social responsibility or scientific integrity for the sake of computational power.