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The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good

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Transparent Data Mining for Big and Small Data

Part of the book series: Studies in Big Data ((SBD,volume 32))

Abstract

The unprecedented availability of large-scale human behavioral data is profoundly changing the world we live in. Researchers, companies, governments, financial institutions, non-governmental organizations and also citizen groups are actively experimenting, innovating and adapting algorithmic decision-making tools to understand global patterns of human behavior and provide decision support to tackle problems of societal importance. In this chapter, we focus our attention on social good decision-making algorithms, that is algorithms strongly influencing decision-making and resource optimization of public goods, such as public health, safety, access to finance and fair employment. Through an analysis of specific use cases and approaches, we highlight both the positive opportunities that are created through data-driven algorithmic decision-making, and the potential negative consequences that practitioners should be aware of and address in order to truly realize the potential of this emergent field. We elaborate on the need for these algorithms to provide transparency and accountability, preserve privacy and be tested and evaluated in context, by means of living lab approaches involving citizens. Finally, we turn to the requirements which would make it possible to leverage the predictive power of data-driven human behavior analysis while ensuring transparency, accountability, and civic participation.

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Notes

  1. 1.

    http://www.undatarevolution.org/report/.

  2. 2.

    http://cignifi.com/.

  3. 3.

    https://www.lenddo.com/.

  4. 4.

    http://tala.co/.

  5. 5.

    https://www.zestfinance.com/.

  6. 6.

    http://www.who.int/topics/mental_health/en/.

  7. 7.

    Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) http://eur-lex.europa.eu/eli/reg/2016/679/oj.

  8. 8.

    http://www.datatransparencylab.org/.

  9. 9.

    http://www.darpa.mil/program/explainable-artificial-intelligence.

  10. 10.

    http://www.law.nyu.edu/centers/ili/algorithmsconference.

  11. 11.

    https://www.whitehouse.gov/blog/2016/05/03/preparing-future-artificial-intelligence.

  12. 12.

    See, for instance, http://www.chicagotribune.com/business/ct-background-check-penalties-1030-biz-20151029-story.html.

  13. 13.

    As a social phenomenon, the concept of stigma has received significant attention by sociologists, who under different frames highlighted and categorized the various factors leading individuals or groups to be discriminated against by society, the countermoves often adopted by the stigmatized, and analyzed dynamics of reactions and evolution of stigma. We refer the interested reader to the review provided by Major and O’Brian [51].

  14. 14.

    http://datapopalliance.org/open-algorithms-a-new-paradigm-for-using-private-data-for-social-good/.

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Authors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Bruno Lepri

  2. Fortia Financial Solutions, Paris, France

    Jacopo Staiano

  3. Data-Pop Alliance, New York, NY, USA

    David Sangokoya, Emmanuel Letouzé & Nuria Oliver

  4. MIT Media Lab, Cambridge, MA, USA

    Emmanuel Letouzé

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  1. Bruno Lepri
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  3. David Sangokoya
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  4. Emmanuel Letouzé
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  5. Nuria Oliver
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Correspondence to Bruno Lepri .

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Editors and Affiliations

  1. Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy

    Tania Cerquitelli

  2. Bell Laboratories, Cambridge, United Kingdom

    Daniele Quercia

  3. Carey School of Law, University of Maryland, Baltimore, Maryland, USA

    Frank Pasquale

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Lepri, B., Staiano, J., Sangokoya, D., Letouzé, E., Oliver, N. (2017). The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good. In: Cerquitelli, T., Quercia, D., Pasquale, F. (eds) Transparent Data Mining for Big and Small Data. Studies in Big Data, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-319-54024-5_1

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