Locating ethic in different human contexts: just another integration problem?

• In Event: Critical Data Studies: Ethics and Human Contexts of Data Science I

Abstract

In recent years, the ubiquity and omnipresence of data have forced us to think through the epistemic and methodological challenges of working with heterogeneous data in interdisciplinary collaborations, where experts and non-experts, scientists and data analysts need to re-imagine the condition of knowledge making. In this context, the role of the embedded social scientist has also evolved, often being more integrated into teams and tasked to reflect, advise and sometimes act on the many social dimensions that surround the scientific workflow.

Drawing from insights from recent fieldwork, the paper reflects on the question of integration of heterogeneous human contexts and ethical frameworks. Looking back at what had started as a classic STS research project among environmental scientists and local communities developing a data science infrastructure aimed to facilitate ecological and cultural knowledge conservation, we’ll try to unpack the challenging experience of navigating uneven expectations and often antinomic normative and ethical considerations.

Following a symmetrical anthropology approach drawing from Michel Callon (1986), the paper will try to account for the human contexts can challenge the situated and often ethnocentric understanding of what is considered ethical. Finally, the paper will open the discussion on the potential (or the lack of thereof) of computational science tools, practices and interfaces as a new “place” for situated narratives, political engagement and ethical practices within academia and beyond.

Author

• Charlotte Mazel-Cabasse, UC Berkeley