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Data for Good: Unlocking Privately-Held Data to the Benefit of the Many

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  • Alemanno, Alberto

Abstract

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.

Suggested Citation

  • Alemanno, Alberto, 2018. "Data for Good: Unlocking Privately-Held Data to the Benefit of the Many," HEC Research Papers Series 1280, HEC Paris.
  • Handle: RePEc:ebg:heccah:1280
    DOI: 10.2139/ssrn.3194040
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    Citations

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    Cited by:

    1. MARTENS Bertin & DUCH BROWN Nestor, 2020. "The economics of Business-to-Government data sharing," JRC Working Papers on Digital Economy 2020-04, Joint Research Centre.
    2. Zygmuntowski, Jan J. & Zoboli, Laura & Nemitz, Paul, 2021. "Embedding European values in data governance: A case for public data commons," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 10(3), pages 1-29.
    3. Julien Mercille, 2021. "Inclusive Smart Cities: Beyond Voluntary Corporate Data Sharing," Sustainability, MDPI, vol. 13(15), pages 1-13, July.

    More about this item

    Keywords

    Big data; data; data governance; data sharing; data risk; data invisible; risk governance; philanthropy;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • K23 - Law and Economics - - Regulation and Business Law - - - Regulated Industries and Administrative Law
    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General

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