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Democratising the Digital Revolution: The Role of Data Governance

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Reflections on Artificial Intelligence for Humanity

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12600))

Abstract

Data is at the heart of today’s AI. As AI technologies advance at a rapid pace, action is needed today to develop and implement governance structures to ensure that the benefits of AI are shared across society.

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References

  1. The Academy of Medical Sciences and the Royal Society: AI in health and care: from bench to bedside, note of discussions at a workshop on 29 March 2019 (2019). https://acmedsci.ac.uk/policy/policy-projects/artificial--intelligence-and-health

  2. European Parliament: Artificial intelligence in transport, briefing from the members’ research service (2019). https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/635609/EPRS_BRI(2019)635609_EN.pdf

  3. See work by Climate Change AI (2020). https://www.climatechange.ai/

  4. Lawrence, N.: From data subject to data citizen (2019). https://inverseprobability.com/talks/notes/from-data-subject-to-data-citizen.html

  5. AI Now: Annual report (2019). https://ainowinstitute.org/AI_Now_2019_Report.pdf

  6. HM Treasury: The economic value of data: a discussion paper (2018). https://www.gov.uk/government/publications/the-economic-value-of-data-discussion-paper

  7. Zheleva, E., Getoor, L.: To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles. In: Proceedings of the 18th International Conference on World Wide Web, April 2009, pp. 531–540 (2009)

    Google Scholar 

  8. Kosinski, M., Stillwell, D., Graepel, T.: Private traits and attributes are predictable from digital records of human behaviours. PNAS 110, 5802–5805 (2013)

    Article  Google Scholar 

  9. Datta, A., Tschantz, M., Datta, A.: (2015) Automated experiments on ad privacy settings. Proc. Priv. Enhanc. Technol. 1, 92–112 (2015)

    Google Scholar 

  10. MIT Tech Review: AI is sending people to jail – and getting it wrong (2019). https://www.technologyreview.com/s/612775/algorithms-criminal-justice-ai/

  11. BBC: Amazon scrapped ‘sexist AI’ tool (2018). https://www.bbc.co.uk/news/technology-45809919

  12. The Guardian: Cambridge analytica scandal ‘highlights need for AI regulation’ (2018). https://www.theguardian.com/technology/2018/apr/16/cambridge-analytica-scandal-highlights-need-for-ai-regulation

  13. CDEI: Review of online targeting (2020). https://www.gov.uk/government/publications/cdei-review-of-online-targeting

  14. Ipsos MORI: Public views of machine learning: findings from public research and engagement (2017). www.royalsociety.org/machine-learning

  15. Pasquale, F.: The automated public sphere, University of Maryland Legal Studies Research Paper No. 2017-31 (2017). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3067552

  16. Barlow, J.P.: A Declaration of the Independence of Cyberspace (2018). https://www.weforum.org/agenda/2018/02/a-declaration-of-the-independence-of-cyberspace/

  17. Daten Ethik Komission (2019). https://www.bmjv.de/DE/Themen/FokusThemen/Datenethikkommission/Datenethikkommission_EN_node.html

  18. The Centre for Data Ethics and Innovation. https://www.gov.uk/government/organisations/centre-for-data-ethics-and-innovation/about

  19. See: https://uk.ambafrance.org/France-s-AI-strategy

  20. European Commission: A European strategy for data and AI: a European approach to excellence and trust (2020). https://ec.europa.eu/

  21. Lawrence, N.: Personal data trusts (2020). https://inverseprobability.com/talks/notes/personal-data-trusts.html

  22. European Commission: A European strategy for data (2020). https://ec.europa.eu/digital-single-market/en/policies/building-european-data-economy

  23. FTC: FTC imposes $5 billion penalty and sweeping new privacy restrictions on Facebook (2019). https://www.ftc.gov/news-events/press-releases/2019/07/ftc-imposes-5-billion-penalty-sweeping-new-privacy-restrictions

  24. FTC: FTC brings first case against developers of stalking apps (2019). https://www.ftc.gov/news-events/press-releases/2019/10/ftc-brings-first-case-against-developers-stalking-apps

  25. FTC: FTC’s Bureau of Competition launches task force to monitor technology markets (2019). https://www.ftc.gov/news-events/press-releases/2019/02/ftcs-bureau-competition-launches-task-force-monitor-technology

  26. HM Treasury: Budget 2020 (2020). https://www.gov.uk/government/publications/budget-2020-documents/budget-2020

  27. Linking AI Principles (2019). https://uk.ambafrance.org/France-s-AI-strategy

  28. Binns, R., Lyngs, U., Van Kleek, M., Zhao, J., Libert, T., Shadbolt, N.: Third party tracking in the mobile ecosystem. In: Proceedings of the 10th International ACM Web Science Conference (2018)

    Google Scholar 

  29. Financial Times: How smartphone apps track users and share data (2019). https://ig.ft.com/mobile-app-data-trackers/

  30. British Academy, TechUK and Royal Society: Data ownership, rights and controls: reaching a common understanding (2018). https://royalsociety.org/-/media/policy/projects/data-governance/data-ownership-rights-and-controls-October-2018.pdf

  31. Financial Times: Letter: legal instruments exist to empower us, the data subjects. From Sylvie Delacroix and Neil Lawrence, The Alan Turing Institute (2019). https://www.ft.com/content/33926828-16c0-11ea-9ee4-11f260415385

  32. Chambers, R.: Distrust: our fear of trusts in the commercial world. Curr. Leg. Probl. 63, 631 (2010)

    Article  Google Scholar 

  33. Delacroix, S., Lawrence, N.: Bottom-up data trusts: disturbing the ‘one size fits all’ approach to data governance. Int. Data Priv. Law 9, 236–252 (2018)

    Google Scholar 

  34. In the EU, Article 80(1) of the GDPR makes provision for such mandates to be put in place, but in only limited circumstances

    Google Scholar 

  35. A legal basis for the ability to move data between trusts could be found in the EU in the GDPR’s provisions on data portability and data erasure (Articles 20 and 17)

    Google Scholar 

  36. Lawrence, N.: Data trusts could allay our privacy fears. The Guardian (2016). https://www.theguardian.com/media-network/2016/jun/03/data-trusts-privacy-fears-feudalism-democracy

  37. UK Government Hall-Pesenti Review: Growing the artificial intelligence industry in the UK (2017). https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/652097/Growing_the_artificial_intelligence_industry_in_the_UK.pdf

  38. Government of Canada: Strengthening privacy for the digital age (2019). https://www.ic.gc.ca/eic/site/062.nsf/eng/h_00107.html

  39. Daten Ethik Komission: Opinion of the data ethics commission (2019). https://www.bmjv.de/

  40. Delacroix, S., Lawrence, N., Montgomery, J.: Selecting a data sharing structure: a value-based choice (2020). https://datatrusts.uk/blogs/selectingdatastructures

  41. Open Data Institute: Data trusts: lessons from three pilots (report) (2019). https://theodi.org/article/odi-data-trusts-report/

  42. Royal Society and Ipsos MORI: Machine learning – what do the public think? (2017). www.royalsociety.org/machine-learning

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Author information

Authors and Affiliations

  1. University of Birmingham, Birmingham, B15 2TT, UK

    Sylvie Delacroix & Jessica Montgomery

  2. The Alan Turing Institute, London, W1 2DB, UK

    Sylvie Delacroix

  3. McGill University, Quebec, H3A0G4, Canada

    Joelle Pineau

Authors
  1. Sylvie Delacroix
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  2. Joelle Pineau
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  3. Jessica Montgomery
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Corresponding author

Correspondence to Sylvie Delacroix .

Editor information

Editors and Affiliations

  1. Inria, Le Chesnay, France

    Bertrand Braunschweig

  2. LAAS-CNRS, Toulouse, France

    Malik Ghallab

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Delacroix, S., Pineau, J., Montgomery, J. (2021). Democratising the Digital Revolution: The Role of Data Governance. In: Braunschweig, B., Ghallab, M. (eds) Reflections on Artificial Intelligence for Humanity. Lecture Notes in Computer Science(), vol 12600. Springer, Cham. https://doi.org/10.1007/978-3-030-69128-8_3

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  • DOI: https://doi.org/10.1007/978-3-030-69128-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69127-1

  • Online ISBN: 978-3-030-69128-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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