Advertisement

Deciding How to Decide: Six Key Questions for Reducing AI’s Democratic Deficit

Chapter
First Online:
Part of the Digital Ethics Lab Yearbook book series (DELY)

Abstract

Through its power to “rationalise”, artificial intelligence (AI) is rapidly changing the relationship between people and the state. But to echo Max Weber’s warnings from one hundred years ago about the increasingly rational bureaucratic state, the “reducing” power of AI systems seems to pose a threat to democracy—unless such systems are developed with public preferences, perspectives and priorities in mind. In other words, we must move beyond minimal legal compliance and faith in free markets to consider public opinion as constitutive of legitimising the use of AI in society. In this chapter I pose six questions regarding how public opinion about AI ought to be sought: what we should ask the public about AI; how we should ask; where and when we should ask; why we should ask; and who is the “we” doing the asking. I conclude by contending that while the messiness of politics may preclude clear answers about the use of AI, this is preferable to the “coolly rational” yet democratically deficient AI systems of today.

Keywords

Artificial intelligence Max Weber Legitimacy Bureaucracy Public opinion Digital ethics 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

Josh Cowls is the recipient of a doctoral scholarship from The Alan Turing Institute.

References

  1. Ada Lovelace Institute. 2018. About Us. Retrieved 8 April 2019. https://www.adalovelaceinstitute.org/about-us/.
  2. ———. n.d. Ada Lovelace Institute. Retrieved 8 April 2019. https://www.adalovelaceinstitute.org/.
  3. Angwin, Julia, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016. Machine Bias. ProPublica. Retrieved 8 April 2019. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing.
  4. Asilomar AI Principles. 2017. Principles Developed in Conjunction with the 2017 Asilomar Conference [Benevolent AI 2017].Google Scholar
  5. Awad, Edmond, Sohan Dsouza, Richard Kim, Jonathan Schulz, Joseph Henrich, Azim Shariff, Jean-François Bonnefon, and Iyad Rahwan. 2018. The Moral Machine Experiment. Nature 563 (7729): 59.CrossRefGoogle Scholar
  6. Balaram, Brhmie. 2017. The Role of Citizens in Developing Ethical AI – RSA. Retrieved 8 April 2019. https://www.thersa.org/discover/publications-and-articles/rsa-blogs/2017/10/the-role-of-citizens-in-developing-ethical-ai.
  7. Binns, Reuben. 2018. Algorithmic Accountability and Public Reason. Philosophy & Technology 31 (4): 543–556.CrossRefGoogle Scholar
  8. Binns, Reuben, Max Van Kleek, Michael Veale, Ulrik Lyngs, Jun Zhao, and Nigel Shadbolt. 2018. “It’s Reducing a Human Being to a Percentage”; Perceptions of Justice in Algorithmic Decisions.Google Scholar
  9. Bourdieu, Pierre. 1979. Public Opinion Does Not Exist. Communication and Class Struggle 1: 124–130.Google Scholar
  10. Brandom, Russell. 2018. Is Google’s $5 Billion Antitrust Fine a Microsoft Moment? The Verge. Retrieved 8 April 2019. https://www.theverge.com/2018/7/18/17587620/google-european-commission-billion-fine-microsoft-antitrust.
  11. Burr, Christopher, and Nello Cristianini. 2019. Can Machines Read Our Minds? Minds and Machines.Google Scholar
  12. Collins, Randall. 1998. Democratization in World-Historical Perspective. In Max Weber, Democracy and Modernization, 14–31. Secaucus: Springer.CrossRefGoogle Scholar
  13. Cowls, Josh. 2017. AI’s “Trolley Problem” Problem. The Alan Turing Institute. Retrieved 8 April 2019. https://www.turing.ac.uk/blog/ais-trolley-problem-problem.
  14. Cowls, Josh, Thomas King, Mariarosaria Taddeo, and Luciano Floridi. 2019. Designing AI for Social Good: Seven Essential Factors. SSRN Scholarly Paper. ID 3388669. Rochester: Social Science Research Network.Google Scholar
  15. Crawford, Kate. 2016. Can an Algorithm Be Agonistic? Ten Scenes from Life in Calculated Publics. Science, Technology, & Human Values 41 (1): 77–92.CrossRefGoogle Scholar
  16. Crawford, Kate, and Vladan Joler. 2018. Anatomy of an AI System.Google Scholar
  17. Dargan, Richard. 2019. Artificial Intelligence Boosts Efficiency and Quality in Radiology Practice. Radiological Society of North America. Retrieved 10 June 2019. https://www.rsna.org/en/news/2019/March/Artificial-Intelligence-Boosts-Efficiency.
  18. Delacroix, Sylvie. 2017. Taking Turing by Surprise? Designing Autonomous Systems for Morally-Loaded Contexts. . SSRN Scholarly Paper. ID 3025626. Rochester: Social Science Research Network.Google Scholar
  19. Delcker, Janosch. 2019. Europe’s Silver Bullet in Global AI Battle: Ethics. POLITICO. Retrieved 8 April 2019. https://www.politico.eu/article/europe-silver-bullet-global-ai-battle-ethics/.
  20. Department for Digital, Culture, Media and Sport. 2019. Centre for Data Ethics (CDEI) 2 Year Strategy. GOV.UK. Retrieved 8 April 2019. https://www.gov.uk/government/publications/the-centre-for-data-ethics-and-innovation-cdei-2-year-strategy/centre-for-data-ethics-cdei-2-year-strategy.
  21. Dodd, Vikram. 2017. Met Police to Use Facial Recognition Software at Notting Hill Carnival. The Guardian, August 5.Google Scholar
  22. European Commission. 2019. Ethics Guidelines for Trustworthy AI. Digital Single Market – European Commission. Retrieved 8 April 2019. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai.
  23. Floridi, Luciano. 1999. Information Ethics: On the Philosophical Foundation of Computer Ethics. Ethics and Information Technology 1 (1): 33–52.CrossRefGoogle Scholar
  24. ———. 2014. The Rise of the MASs. In Protection of Information and the Right to Privacy – A New Equilibrium?, Law, Governance and Technology Series, ed. L. Floridi, 95–122. Cham: Springer International Publishing.CrossRefGoogle Scholar
  25. ———. 2019. Translating Principles into Practices of Digital Ethics: Five Risks of Being Unethical. Philosophy & Technology 32 (2): 185–193.CrossRefGoogle Scholar
  26. Floridi, Luciano, and Cowls, Josh. 2019. A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review.Google Scholar
  27. Franklin, Mark N., and Christopher Wlezien. 1997. The Responsive Public: Issue Salience, Policy Change, and Preferences for European Unification. Journal of Theoretical Politics 9 (3): 347–363.CrossRefGoogle Scholar
  28. Fraser, Nancy. 1990. Rethinking the Public Sphere: A Contribution to the Critique of Actually Existing Democracy. Social Text (25/26): 56–80.Google Scholar
  29. Gellner, Ernest. 2008. Nations and Nationalism. Santa Barbara: Cornell University Press.Google Scholar
  30. Golbeck, Jennifer. 2013. Facebook Wants to Know Why You’re Self-Censoring Your Posts. Slate Magazine. Retrieved 8 April 2019. https://slate.com/technology/2013/12/facebook-self-censorship-what-happens-to-the-posts-you-dont-publish.html.
  31. Habermas, J. 1989. The Structural Transformation of the Public Shere. Boston: MIT Press.Google Scholar
  32. Hall, Wendy, and Jérôme Pesenti. 2017. Growing the Artificial Intelligence Industry in the UK. Department for Digital, Culture, Media & Sport and Department for Business, Energy & Industrial Strategy. Part of the Industrial Strategy UK and the Commonwealth.Google Scholar
  33. Harwell, Drew. 2018. Amazon Met with ICE Officials over Facial-Recognition System That Could Identify Immigrants. Washington Post. Retrieved 8 April 2019. https://www.washingtonpost.com/technology/2018/10/23/amazon-met-with-ice-officials-over-facial-recognition-system-that-could-identify-immigrants/.
  34. Hitrova, Christina. 2019. Turing’s Data Ethics Group Supports the Development of the NHS Code of Conduct for Data-Driven Health and Care Technology. The Alan Turing Institute. Retrieved 8 April 2019. https://www.turing.ac.uk/blog/turings-data-ethics-group-supports-development-nhs-code-conduct-data-driven-health-and-care.
  35. Hubbard, Alex. 2019. When It Comes to Explaining AI Decisions, Context Matters. Information Commissioner’s Office. Retrieved 10 June 2019. https://ai-auditingframework.blogspot.com/2019/06/when-it-comes-to-explaining-ai.html.
  36. Hvistendahl, Mara. 2017. In China, a Three-Digit Score Could Dictate Your Place in Society. Wired, December 14.Google Scholar
  37. International Conference of Data Protection and Privacy Commissioners. 2018. Ethics and Data Protection in Artificial Intelligence. Retrieved 8 April 2019. https://icdppc.org/public-consultation-ethics-and-data-protection-in-artificial-intelligence-continuing-the-debate/.
  38. Kobie, Nicole. 2019. The Complicated Truth about China’s Social Credit System. Wired UK, January 21.Google Scholar
  39. Lassman, Peter, and Ronald Speirs. 1994. Weber: Political Writings. Cambridge: Cambridge University Press.Google Scholar
  40. Lax, Jeffrey R., and Justin H. Phillips. 2009. Gay Rights in the States: Public Opinion and Policy Responsiveness. American Political Science Review 103 (3): 367–386.CrossRefGoogle Scholar
  41. Leslie, David. 2019. Understanding Artificial Intelligence Ethics and Safety.Google Scholar
  42. Levinson, Sanford. 2006. How the United States Constitution Contributes to the Democratic Deficit in America. Drake L Review 55: 859.Google Scholar
  43. Loder, John, and Lydia Nicholas. 2018. Confronting Dr Robot. Nesta. Retrieved 8 April 2019. https://www.nesta.org.uk/report/confronting-dr-robot/.
  44. McCarthy, J., M. L. Minsky, N. Rochester, and C. E. Shannon. 1955. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence.Google Scholar
  45. Miles, Tom. 2018. U.N. Investigators Cite Facebook Role in Myanmar Crisis. Reuters, March 12.Google Scholar
  46. Montreal Declaration for a Responsible Development of Artificial Intelligence. 2017. Montreal Declaration for a Responsible Development of Artificial Intelligence. Announced at the Conclusion of the Forum on the Socially Responsible Development of AI.Google Scholar
  47. Moor, James. 2006. The Dartmouth College Artificial Intelligence Conference: The next Fifty Years. AI Magazine 27 (4): 87–87.Google Scholar
  48. Mouffe, Chantal. 2005. The Return of the Political. Vol. 8. London: Verso.Google Scholar
  49. Noble, Safiya Umoja. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. New York: NYU Press.CrossRefGoogle Scholar
  50. O’Connor, Dan. 2018. Can AI Improve Health for Everyone? We Want to Fund Research to Find out | Wellcome. Retrieved 8 April 2019. https://wellcome.ac.uk/news/can-ai-improve-health-everyone-we-want-fund-research-find-out.
  51. Patel, Reema. 2019. Public Deliberation Could Help Address AI’s Legitimacy Problem in 2019. Retrieved 8 April 2019. https://www.adalovelaceinstitute.org/public-deliberation-could-help-address-ais-legitimacy-problem-in-2019/.
  52. Penn, Jonnie. 2018. AI Thinks like a Corporation—and That’s Worrying – Open Voices. The Economist. Retrieved 8 April 2019. https://www.economist.com/open-future/2018/11/26/ai-thinks-like-a-corporation-and-thats-worrying.
  53. Pew Research Center. 2016. Top Voting Issues in 2016 Election. Retrieved 8 April 2019. https://www.people-press.org/2016/07/07/4-top-voting-issues-in-2016-election/.
  54. Rawls, John. 2009. A Theory of Justice. Cambridge: Harvard University Press.CrossRefGoogle Scholar
  55. Schroeder, Ralph. 1998. From Weber’s Political Sociology to Contemporary Liberal Democracy. In Max Weber, Democracy and Modernization, 79–92. Secaucus: Springer.CrossRefGoogle Scholar
  56. Scott, James C. 1998. Seeing like a State: How Certain Schemes to Improve the Human Condition Have Failed. New Haven: Yale University Press.Google Scholar
  57. Sen, Amartya Kumar. 2009. The Idea of Justice. Cambridge: Harvard University Press.CrossRefGoogle Scholar
  58. Snow, Jackie. 2019. How Africa Is Seizing an AI Opportunity. Fast Company. Retrieved 8 April 2019. https://www.fastcompany.com/90308114/how-africa-is-seizing-an-ai-opportunity.
  59. Solon, Olivia. 2017. “It’s Digital Colonialism”: How Facebook’s Free Internet Service Has Failed Its Users. The Guardian, July 27.Google Scholar
  60. Squires, Catherine R. 2002. Rethinking the Black Public Sphere: An Alternative Vocabulary for Multiple Public Spheres. Communication Theory 12 (4): 446–468.CrossRefGoogle Scholar
  62. Taylor, Linnet, and Dennis Broeders. 2015. In the Name of Development: Power, Profit and the Datafication of the Global South. Geoforum 64: 229–237.CrossRefGoogle Scholar
  63. The IEEE Initiative on Ethics of Autonomous and Intelligent Systems. 2017. Ethically Aligned Design, V2.Google Scholar
  64. Tufekci, Zeynep. 2018. YouTube, the Great Radicalizer. The New York Times, June 8.Google Scholar
  65. Wachter, Sandra, Brent Mittelstadt, and Luciano Floridi. 2016. Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation . SSRN Scholarly Paper. ID 2903469. Rochester: Social Science Research Network.CrossRefGoogle Scholar
  66. Webb, Amy. 2019. Build Democracy into AI. POLITICO. Retrieved 8 April 2019. https://www.politico.eu/article/build-democracy-into-ai-combat-china/.
  67. Weber, Max. 1994. Weber: Political Writings. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  68. Whimster, Sam. 1998. The Nation-State, the Protestant Ethic and Modernization. In Max Weber, Democracy and Modernization, 61–78. New York: Springer.CrossRefGoogle Scholar
  69. Whittaker, Meredith, Kate Crawford, Roel Dobbe, Genevieve Fried, Elizabeth Kaziunas, Varoon Mathur, Sarah Mysers West, Rashida Richardson, Jason Schultz, and Oscar Schwartz. 2018. AI Now Report 2018. AI Now Institute at New York University.Google Scholar
  70. Wilson, Clare. 2018. Trolley Problem Tested in Real Life for First Time with Mice. New Scientist. Retrieved 8 April 2019. https://www.newscientist.com/article/2168648-trolley-problem-tested-in-real-life-for-first-time-with-mice/.
  71. Wiredu, Kwasi. 2001. Democracy by Consensus: Some Conceptual Considerations. Philosophical Papers 30 (3): 227–244.CrossRefGoogle Scholar
  72. Wong, Pak-Hang. 2012. Dao, Harmony and Personhood: Towards a Confucian Ethics of Technology. Philosophy & Technology 25 (1): 67–86.CrossRefGoogle Scholar
  73. Wood, Alex J., Mark Graham, Vili Lehdonvirta, and Isis Hjorth. 2019. Good Gig, Bad Gig: Autonomy and Algorithmic Control in the Global Gig Economy. Work, Employment and Society 33 (1): 56–75.CrossRefGoogle Scholar
  74. Zuboff, Shoshana. 2019. The Age of Surveillance Capitalism: The Fight for the Future at the New Frontier of Power. New York: Profile Books.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Oxford Internet InstituteUniversity of OxfordOxfordUK
  2. 2.The Alan Turing InstituteLondonUK

Personalised recommendations

Cite chapter

Buy options