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Certification systems for machine learning: Lessons from sustainability

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  • Kira J.M. Matus
  • Michael Veale

Abstract

Concerns around machine learning’s societal impacts have led to proposals to certify some systems. While prominent governance efforts to date center around networking standards bodies such as the Institute of Electrical and Electronics Engineers (IEEE), we argue that machine learning certification should build on structures from the sustainability domain. Policy challenges of machine learning and sustainability share significant structural similarities, including difficult to observe credence properties, such as data collection characteristics or carbon emissions from model training, and value chain concerns, including core‐periphery inequalities, networks of labor, and fragmented and modular value creation. While networking‐style standards typically draw their adoption and enforcement from functional needs to conform to enable network participation, machine learning, despite its digital nature, does not benefit from this dynamic. We therefore apply research on certification systems in sustainability, particularly of commodities, to generate lessons across both areas, informing emerging proposals such as the EU’s AI Act.

Suggested Citation

  • Kira J.M. Matus & Michael Veale, 2022. "Certification systems for machine learning: Lessons from sustainability," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 177-196, January.
    • Handle: RePEc:wly:reggov:v:16:y:2022:i:1:p:177-196
    DOI: 10.1111/rego.12417
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    1. Graeme Auld & Lars H. Gulbrandsen, 2010. "Transparency in Nonstate Certification: Consequences for Accountability and Legitimacy," Global Environmental Politics, MIT Press, vol. 10(3), pages 97-119, August.
    2. Graeme Auld & Stefan Renckens, 2017. "Rule-Making Feedbacks through Intermediation and Evaluation in Transnational Private Governance," The ANNALS of the American Academy of Political and Social Science, , vol. 670(1), pages 93-111, March.
    3. Michael J. Lenox, 2006. "The Role of Private Decentralized Institutions in Sustaining Industry Self-Regulation," Organization Science, INFORMS, vol. 17(6), pages 677-690, December.
    4. Arthur P. J. Mol & Peter Oosterveer, 2015. "Certification of Markets, Markets of Certificates: Tracing Sustainability in Global Agro-Food Value Chains," Sustainability, MDPI, vol. 7(9), pages 1-21, September.
    5. McCluskey, Jill J. & Loureiro, Maria L., 2005. "Reputation and Production Standards," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 30(1), pages 1-11, April.
    6. Hood, Christopher & Rothstein, Henry & Baldwin, Robert, 2004. "The Government of Risk: Understanding Risk Regulation Regimes," OUP Catalogue, Oxford University Press, number 9780199270019, Decembrie.
    7. Edmond Awad & Sohan Dsouza & Richard Kim & Jonathan Schulz & Joseph Henrich & Azim Shariff & Jean-François Bonnefon & Iyad Rahwan, 2018. "The Moral Machine experiment," Nature, Nature, vol. 563(7729), pages 59-64, November.
    8. Kenneth W. Abbott & David Levi-Faur & Duncan Snidal, 2017. "Introducing Regulatory Intermediaries," The ANNALS of the American Academy of Political and Social Science, , vol. 670(1), pages 6-13, March.
    9. Veale, Michael & Binns, Reuben, 2017. "Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data," SocArXiv ustxg, Center for Open Science.
    10. Christine Parker & Rachel Carey & Josephine De Costa & Gyorgy Scrinis, 2017. "Can the hidden hand of the market be an effective and legitimate regulator? The case of animal welfare under a labeling for consumer choice policy approach," Regulation & Governance, John Wiley & Sons, vol. 11(4), pages 368-387, December.
    11. Edwards, Lilian & Veale, Michael, 2017. "Slave to the Algorithm? Why a 'right to an explanation' is probably not the remedy you are looking for," LawArXiv 97upg, Center for Open Science.
    12. Baldwin, Robert & Cave, Martin & Lodge, Martin (ed.), 2010. "The Oxford Handbook of Regulation," OUP Catalogue, Oxford University Press, number 9780199560219, Decembrie.
    13. Darby, Michael R & Karni, Edi, 1973. "Free Competition and the Optimal Amount of Fraud," Journal of Law and Economics, University of Chicago Press, vol. 16(1), pages 67-88, April.
    14. Eleni Kosta, 2022. "Algorithmic state surveillance: Challenging the notion of agency in human rights," Regulation & Governance, John Wiley & Sons, vol. 16(1), pages 212-224, January.
    15. Lars H. Gulbrandsen, 2004. "Overlapping Public and Private Governance: Can Forest Certification Fill the Gaps in the Global Forest Regime?," Global Environmental Politics, MIT Press, vol. 4(2), pages 75-99, May.
    16. Bennett, Elizabeth A., 2017. "Who Governs Socially-Oriented Voluntary Sustainability Standards? Not the Producers of Certified Products," World Development, Elsevier, vol. 91(C), pages 53-69.
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    1. Cobbe, Jennifer & Veale, Michael & Singh, Jatinder, 2023. "Understanding Accountability in Algorithmic Supply Chains," SocArXiv p4sey, Center for Open Science.

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