IDEAS home Printed from https://ideas.repec.org/a/zbw/iprjir/245346.html
   My bibliography  Save this article

Beyond the individual: Governing AI's societal harm

Author

Listed:
  • Smuha, Nathalie A.

Abstract

In this paper, I distinguish three types of harm that can arise in the context of artificial intelligence (AI): individual harm, collective harm and societal harm. Societal harm is often overlooked, yet not reducible to the two former types of harm. Moreover, mechanisms to tackle individual and collective harm raised by AI are not always suitable to counter societal harm. As a result, policymakers' gap analysis of the current legal framework for AI not only risks being incomplete, but proposals for new legislation to bridge these gaps may also inadequately protect societal interests that are adversely impacted by AI. By conceptualising AI's societal harm, I argue that a shift in perspective is needed beyond the individual, towards a regulatory approach of AI that addresses its effects on society at large. Drawing on a legal domain specifically aimed at protecting a societal interest-environmental law-I identify three "societal" mechanisms that EU policymakers should consider in the context of AI. These concern (1) public oversight mechanisms to increase accountability, including mandatory impact assessments with the opportunity to provide societal feedback; (2) public monitoring mechanisms to ensure independent information gathering and dissemination about AI's societal impact; and (3) the introduction of procedural rights with a societal dimension, including a right to access to information, access to justice, and participation in public decision-making on AI, regardless of the demonstration of individual harm. Finally, I consider to what extent the European Commission's new proposal for an AI regulation takes these mechanisms into consideration, before offering concluding remarks.

Suggested Citation

  • Smuha, Nathalie A., 2021. "Beyond the individual: Governing AI's societal harm," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 10(3), pages 1-32.
  • Handle: RePEc:zbw:iprjir:245346
    DOI: 10.14763/2021.3.1574
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/245346/1/1775703568.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.14763/2021.3.1574?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hasselbalch, Gry, 2019. "Making sense of data ethics. The powers behind the data ethics debate in European policymaking," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 8(2), pages 1-19.
    2. Irving Fisher Committee, 2017. "Big Data," IFC Bulletins, Bank for International Settlements, number 44, July.
    3. Geert Van Calster & Leonie Reins, 2017. "EU Environmental Law," Books, Edward Elgar Publishing, number 15513.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlsson, Vanja & Rönnblom, Malin, 2022. "From politics to ethics: Transformations in EU policies on digital technology," Technology in Society, Elsevier, vol. 71(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arnold, René & Hildebrandt, Christian & Taş, Serpil, 2020. "Europäische Datenökonomie: Zwischen Wettbewerb und Regulierung. Endbericht," Study Series, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH, number 251537.
    2. Ms. Longmei Zhang & Ms. Sally Chen, 2019. "China’s Digital Economy: Opportunities and Risks," IMF Working Papers 2019/016, International Monetary Fund.
    3. Daniel H. Weinberg & John M. Abowd & Robert F. Belli & Noel Cressie & David C. Folch & Scott H. Holan & Margaret C. Levenstein & Kristen M. Olson & Jerome P. Reiter & Matthew D. Shapiro & Jolene Smyth, 2017. "Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System?," Working Papers 17-59r, Center for Economic Studies, U.S. Census Bureau.
    4. Xiangjie Kong & Huizhen Jiang & Wei Wang & Teshome Megersa Bekele & Zhenzhen Xu & Meng Wang, 2017. "Exploring dynamic research interest and academic influence for scientific collaborator recommendation," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 369-385, October.
    5. Harwood, Stephen & Eaves, Sally, 2020. "Conceptualising technology, its development and future: The six genres of technology," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    6. Chih-Hung Hsu & Ming-Ge Li & Ting-Yi Zhang & An-Yuan Chang & Shu-Zhen Shangguan & Wan-Ling Liu, 2022. "Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework," Mathematics, MDPI, vol. 10(8), pages 1-35, April.
    7. Claudia Buch, 2019. "Building pathways for policy making with big data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    8. Yaniv Mordecai, 2019. "Model‐based protocol specification," Systems Engineering, John Wiley & Sons, vol. 22(2), pages 188-210, March.
    9. Rafael J. P. Damaceno & Luciano Rossi & Rogério Mugnaini & Jesús P. Mena-Chalco, 2019. "The Brazilian academic genealogy: evidence of advisor–advisee relationships through quantitative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 303-333, April.
    10. de Streel, Alexandre & Sibony, Anne-Lise, 2017. "Towards Smarter Consumer Protection Rules for Digital Services," 28th European Regional ITS Conference, Passau 2017 169509, International Telecommunications Society (ITS).
    11. Georgios Georgiadis & Geert Poels, 2021. "Enterprise architecture management as a solution for addressing general data protection regulation requirements in a big data context: a systematic mapping study," Information Systems and e-Business Management, Springer, vol. 19(1), pages 313-362, March.
    12. Tractenberg, Rochelle E., 2020. "Concordance of professional ethical practice standards for the domain of Data Science: A white paper," SocArXiv p7rj2, Center for Open Science.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:iprjir:245346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://policyreview.info/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.