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Algorithmic Discrimination: Big Data Analytics and the Future of the Internet

In: The Future Internet

Author

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  • Jenifer Winter

    (University of Hawai‘i at Mānoa)

Abstract

This chapter discusses several technical changes related to the Internet—the social semantic web and linked data, the instrumentation of natural and social processes, big data and graphing analytics, and cloud-based facial recognition—and focuses on several threats resulting from these developments. As billions, or trillions, of everyday objects, including the human body itself, are equipped with sensors, a variety of new types of data will be collected, aggregated, and linked to other personally identifiable records. These changes transgress personal privacy boundaries and lead to unjust algorithmic discrimination and loss of anonymity, resulting in undemocratic shifts in power. Three alternative scenarios for the future Internet are presented as contrasting possibilities to explore key uncertainties about the future for the year 2045. Because the framework for the future Internet is already developed and numerous aspects of it are already appearing around us, it is essential that we critically examine these systems and associated narratives in order to stimulate meaningful discussion and design policies and systems that respect citizen concerns. By examining and testing alternative visions of the future Internet, we can more closely align its development with ethical, human-centered insight.

Suggested Citation

  • Jenifer Winter, 2015. "Algorithmic Discrimination: Big Data Analytics and the Future of the Internet," Public Administration and Information Technology, in: Jenifer Winter & Ryota Ono (ed.), The Future Internet, edition 1, chapter 0, pages 125-140, Springer.
    • Handle: RePEc:spr:paitcp:978-3-319-22994-2_8
    DOI: 10.1007/978-3-319-22994-2_8
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    Citations

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    Cited by:

    1. Ghosh, Dipayan, 2021. "The commercialization of bias in cashless India," Telecommunications Policy, Elsevier, vol. 45(5).
    2. Ingrid Poncin & Wafa Hammedi & Caroline Lancelot-Miltgen, 2022. "Technologies, expériences, services et au-delà ! Plaidoyer pour développer la recherche sur les technologies, les expériences et les services," Post-Print hal-03818050, HAL.
    3. Edward Simpson & David Bradley & John Palfreyman & Roger White, 2022. "Sustainable Society: Wellbeing and Technology—3 Case Studies in Decision Making," Sustainability, MDPI, vol. 14(20), pages 1-30, October.
    4. Matthew Tenney & Renee Sieber, 2016. "Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control," Urban Planning, Cogitatio Press, vol. 1(2), pages 101-113.
    5. Drago? BÃŽGU & Mihail-Valentin CERNEA, 2019. "Algorithmic Bias In Current Hiring Practices: An Ethical Examination," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 13(1), pages 1068-1073, November.

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