Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-25T17:17:49.142Z Has data issue: false hasContentIssue false
  • English
  • Français

A Critical Take on the Policy Recommendations of the EU High-Level Expert Group on Artificial Intelligence

Published online by Cambridge University Press:  23 January 2020

Michael VEALE Open the ORCID record for Michael VEALE [Opens in a new window]
Michael VEALE*
Affiliation:
Faculty of Laws, University College London and the Alan Turing Institute; email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

The European Commission recently published the policy recommendations of its “High-Level Expert Group on Artificial Intelligence”: a heavily anticipated document, particularly in the context of the stated ambition of the new Commission President to regulate in that area. This article argues that these recommendations have significant deficits in a range of areas. It analyses a selection of the Group’s proposals in context of the governance of artificial intelligence more broadly, focusing on issues of framing, representation and expertise, and on the lack of acknowledgement of key issues of power and infrastructure underpinning modern information economies and practices of optimisation.

Type
Reports
Information
European Journal of Risk Regulation , Volume 11 , Issue 1 , March 2020 , e1
Copyright
© Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Thank you to Seda Gürses for her responsive term “low-level experts”, and for thinking through many of these issues in relation to our joint consultation response to the earlier HLEG-AI guidance. Thank you to the anonymous reviewer whose input improved this work. The author was supported by the Alan Turing Institute under EPSRC grant EP/N510129/1.

References

1 Department of Digital, Culture, Media and Sport, Centre for Data Ethics and Innovation: Government Response to Consultation (UK Government 2018).

2 “Leading Experts Appointed to AI Council to Supercharge the UK’s Artificial Intelligence Sector” (GOV.UK, 16 May 2019) <www.gov.uk/government/news/leading-experts-appointed-to-ai-council-to-supercharge-the-uks-artificial-intelligence-sector> accessed 10 November 2019.

3 Office for Artificial Intelligence, “About Us” (GOV.UK, 2019) <www.gov.uk/government/organisations/office-for-artificial-intelligence/about> accessed 10 November 2019.

4 House of Lords, “AI in the UK: Ready, Willing and Able?” (HL Paper 100, 16 April 2018).

5 House of Commons, “Algorithms in Decision-Making” (HC 351, 23 May 2018).

6 Health and Social Care (National Data Guardian) Act 2018.

7 HM Government, “Online Harms White Paper” (CP 57, April 2019).

8 Department of Digital, Culture, Media and Sport, “Data Ethics Framework” (GOV.UK, 30 August 2018) <www.gov.uk/government/publications/data-ethics-framework/data-ethics-framework> accessed 10 November 2019.

9 Digital Catapult, “Ethics Framework – Responsible AI” (MI Garage, no date) <www.migarage.ai/ethics-framework/> accessed 10 November 2019.

10 HM Government, “PM Announces New Independent Organisation to Tackle Deep-Rooted Injustices in Society” (GOV.UK, 12 July 2019) <www.gov.uk/government/news/pm-announces-new-independent-organisation-to-tackle-deep-rooted-injustices-in-society> accessed 10 November 2019.

11 Department for Business Energy & Industrial Strategy, “Regulation for the Fourth Industrial Revolution” (CP 111, June 2019).

12 HM Government, supra, note 7.

13 T Donnelly and S Roberts, “Introducing NHSX’s New National Artificial Intelligence Laboratory” (Technology in the NHS (Department of Health & Social Care Blog), 8 August 2019) <healthtech.blog.gov.uk/2019/08/08/introducing-nhsxs-new-national-artificial-intelligence-laboratory/> accessed 10 November 2019.

14 HL Deb 5 June 2019, WA HL8200.

15 Government Office for Science, “Artificial Intelligence: Opportunities and Implications for the Future of Decision Making” (GO Science Report, 2016).

16 Office for National Statistics, “About Us: Data Science Campus” (no date) <datasciencecampus.ons.gov.uk/about-us/> accessed 10 November 2019.

17 Department of Health & Social Care, “Code of Conduct for Data-Driven Health and Care Technology” (GOV.UK, no date) <www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology/initial-code-of-conduct-for-data-driven-health-and-care-technology> accessed 10 November 2019.

18 This arose from an earlier communication, see European Commission, “Artificial Intelligence for Europe” (Communication from the Commission (SWD(2018) 137 final), April 2018).

19 High-Level Expert Group on Artificial Intelligence, “Ethics Guidelines for Trustworthy AI” (April 2019).

20 T Metzinger, “Ethics Washing Made in Europe”, Der Tagesspiegel (18 April 2019) <www.tagesspiegel.de/politik/eu-guidelines-ethics-washing-made-in-europe/24195496.html> accessed 10 November 2019; “Dialogue Seminar on Artificial Intelligence: Ethical Concerns” (19 March 2019) <www.europarl.europa.eu/streaming/?event=20190319-1500-SPECIAL-SEMINAR1&start=2019-03-19T15:44:53Z&end=2019-03-19T15:56:00Z&language=en> accessed 10 November 2019.

21 High-Level Expert Group on Artificial Intelligence, “Policy and Investment Recommendations for Trustworthy AI” (26 June 2019).

22 European Commission, “Europe in May 2019: Preparing for a More United, Stronger and More Democratic Union in an Increasingly Uncertain World” (Contribution to the informal EU27 leaders’ meeting in Sibiu (Romania) on 9 May 2019, 9 May 2019) 33.

23 U von der Leyen, “A Union that Strives for More: My Agenda for Europe” (Political Guidelines for the Next European Commission 2019–2024, 2019) 13.

24 See generally Bardach, E, A Practical Guide for Policy Analysis: The Eightfold Path to More Effective Problem Solving (Sage 2012) (on the policy process).Google Scholar

25 High-Level Expert Group on Artificial Intelligence, supra, note 21, 12.

26 See generally Hoppe, R, The Governance of Problems: Puzzling, Powering and Participation (Policy Press 2010)CrossRefGoogle Scholar (on the nature of unstructured problems and their management by the policy process).

27 On the limitations of machine-legible approaches to complex problems, see generally Scott, JC, Seeing like a State: How Certain Schemes to Improve the Human Condition Have Failed (Yale University Press 1998)Google Scholar; Engle Merry, S, The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking (University of Chicago Press 2016).CrossRefGoogle Scholar

28 Hoppe, supra, note 26.

29 Green, B, The Smart Enough City (MIT Press 2019).CrossRefGoogle Scholar

30 High-Level Expert Group on Artificial Intelligence, supra, note 21, 24.

31 S Peña Gangadharan and J Niklas, “Decentering Technology in Discourse on Discrimination” (2019) 22 Information, Communication & Society 882.

32 See generally the chapters (and works cited therein) in the collection Mitchell, RB et al, Global Environmental Assessments (MIT Press 2006).CrossRefGoogle Scholar

33 RB Mitchell et al, “Information and Influence” in Mitchell et al, supra, note 32, 321.

34 These are representatives from Access Now, a digital rights organisation, and BEUC, an umbrella body for consumer rights groups.

35 Z Yu et al, “Tracking the Trackers” in Proceedings of the 25th International Conference on World Wide Web (WWW ’16, Republic and Canton of Geneva, Switzerland, International World Wide Web Conferences Steering Committee 2016).

36 R Binns et al, “Third Party Tracking in the Mobile Ecosystem” in Proceedings of the 10th ACM Conference on Web Science (WebSci ’18, New York, ACM 2018).

37 Gürses, S and van Hoboken, J, “Privacy after the Agile Turn” in Selinger, E et al (eds), The Cambridge Handbook of Consumer Privacy (1st edn, Cambridge University Press 2018).Google Scholar

38 Information Commissioner’s Office, “Information Commissioner’s Annual Report and Financial Statements 2018–2019” (Report presented to Parliament (HC 2299), 8 July 2019) 98.

39 Ofcom, “The Office of Communications Annual Report & Accounts for the Period 1 April 2018 to 31 March 2019” (Report presented to Parliament (HC 2321), 2019) 103.

40 European Data Protection Board, “First Overview on the Implementation of the GDPR and the Roles and Means of the National Supervisory Authorities” (Report presented to the European Parliament’s Civil Liberties, Justice and Home Affairs Committee (LIBE), 26 February 2019).

41 Information Commissioner’s Office, “Update Report into Adtech and Real Time Bidding” (20 June 2019).

42 Directive (EU) 2019/1024 of the European Parliament and of the Council of 20 June 2019 on open data and the re-use of public sector information OJ L 172/56 (2019) Art 5(2).

43 High-Level Expert Group on Artificial Intelligence, supra, note 21, 19–20.

44 ibid, 29–30.

45 See eg Brown, I and Marsden, CT, “Holistic Regulation of the Interoperable Internet” in Regulating Code: Good Governance and Better Regulation in the Information Age (The MIT Press 2013).CrossRefGoogle Scholar

46 See the effort by Facebook, Google, Microsoft, Apple and Twitter: Data Transfer Project, “Data Transfer Project Overview and Fundamentals” (White Paper, 20 July 2018).

47 High-Level Expert Group on Artificial Intelligence, supra, note 21, 39.

48 Gürses, S et al, “Stirring the POTs: Protective Optimization Technologies” in Bayamlıoğlu, E et al (eds), Being Profiled:Cogitas Ergo Sum (Amsterdam University Press 2018).Google Scholar

49 C Bowden, “The US Surveillance Programmes and Their Impact on EU Citizens’ Fundamental Rights” (Report for the European Parliament’s Committee on Civil Liberties, Justice and Home Affairs 2013).

50 K Stephan, “Apple Versus the Feds: How a Smartphone Stymied the FBI” (2017) 6 IEEE Consumer Electronics Mag 103.

51 See generally Domingo-Ferrer, J et al, Privacy and Data Protection by Design–from Policy to Engineering (ENISA 2014)Google Scholar; The Royal Society, Protecting Privacy in Practice: The Current Use, Development and Limits of Privacy Enhancing Technologies in Data Analysis (The Royal Society 2019).

52 Gürses et al, supra, note 48.

53 See eg K Yeung, “‘Hypernudge’: Big Data as a Mode of Regulation by Design” (2017) 20 Information, Communication & Society 118.