Data for Good: Unlocking Privately-Held Data to the Benefit of the Many
9 European Journal of Risk Regulation 2 (2018)
11 Pages Posted: 12 Jun 2018 Last revised: 13 Jun 2018
Date Written: June 11, 2018
It is almost a truism to argue that data holds a great promise of transformative resources for social good, by helping to address a complex range of societal issues, ranging from saving lives in the aftermath of a natural disaster to predicting teen suicides. Yet it is not public authorities who hold this real-time data, but private entities, such as mobile network operators and business card companies, and - with even greater detail - tech firms such as Google through its globally-dominant search engine, and, in particular, social media platforms, such as Facebook and Twitter. Besides a few isolated and self-proclaimed ‘data philanthropy’ initiatives and other corporate data-sharing collaborations, data-rich companies have historically shown resistance to not only share this data for the public good, but also to identify its inherent social, non-commercial benefit. How to explain to citizens across the world that their own data – which has been aggressively harvested over time – can’t be used, and not even in emergency situations? Responding to this unsettling question entails a fascinating research journey for anyone interested in how the promises of big data could deliver for society as a whole. In the absence of a plausible solution, the number of societal problems that won’t be solved unless firms like Facebook, Google and Apple start coughing up more data-based evidence will increase exponentially, as well as societal rejection of their underlying business models.
This article identifies the major challenges of unlocking private-held data to the benefit of society and sketches a research agenda for scholars interested in collaborative and regulatory solutions aimed at unlocking privately-held data for good.
Keywords: Big data, data, data governance, data sharing, data risk, data invisible, risk governance, philanthropy,
JEL Classification: K23, K32, K40, I18
Suggested Citation: Suggested Citation