Paper short abstract:

This paper provides a notion of big data and an account on its adoption in several social sciences, with an emphasis on Anthropology and a focus on methodological challenges, debates, controversies and epistemological issues on analysing information through AI and producing digital ethnographies.

Paper long abstract:

This paper introduces the notion of big data and provides an account on its progressive adoption in several social sciences since 2010, with an emphasis on Anthropology. In this sense, the methodological challenges of these new ways of information understanding, processing and representation are approached, as well as the debates and controversies it has risen within the traditional quantitative/qualitative question of these disciplines in particular. That drives towards epistemological issues on analysing information, in which statistical procedures such as machine learning and other types of Artificial Intelligence are crucial for answering questions and solving problems through big data and, therefore, towards one of the characteristics of Anthropology: interdisciplinarity.

Moreover, the paper frames this phenomenon within the practices of digital ethnography from a critical point of view which considers human experiences, practices, things, relations, social worlds, localities and events as its objects of study. Consequently, the central but unequal role of Internet and the digital in modern-day societies demands more and more the ethnographer to displace and to expand his/her interests and methods towards multi-sited approaches, as well as towards multiple types of sources beyond text such as visual, film, audio or mapping ones. Since the integration of them into any analytical process is complex, big data and AI are becoming fundamental means to apprehend human individuals, societies and cultures more widely, as well as their diversity, so it may be stated that they deserve a place within anthropological research and, therefore, into the teaching and learning of the discipline.