Academic Institutions in Multilateral Data Governance: Emerging Arrangements for Negotiating Risk, Value and Ethics in the Big Data Economy

TL;DR

This paper examines how academic institutions navigate emerging multilateral data governance arrangements, balancing risk, ethics, and profit in the evolving big data economy through case studies and new governance models.

Contribution

It introduces the concepts of combinatorial and experimental data governance, analyzing their roles in managing ethics and risk in academic data partnerships.

Findings

Ethics instrumentation supports profit-driven data infrastructure.

Combinatorial governance mitigates reputational and societal risks.

Experimental governance offers innovative but limited ethical frameworks.

Abstract

Data sharing partnerships are increasingly an imperative for research institutions and, at the same time, a challenge for established models of data governance and ethical research oversight. We analyse four cases of data partnership involving academic institutions and examine the role afforded to the research partner in negotiating the relationship between risk, value, trust and ethics. Within this terrain, far from being a restraint on financialisation, the instrumentation of ethics forms part of the wider mobilisation of infrastructure for the realisation of profit in the big data economy. Under what we term `combinatorial data governance' academic structures for the management of research ethics are instrumentalised as organisational functions that serve to mitigate reputational damage and societal distrust. In the alternative model of `experimental data governance' researchers propose frameworks and instruments for the rethinking of data ethics and the risks associated with it - a model that is promising but limited in its practical application.