Making Sense of AI. Anthony Elliott

of opportunity and risk which now characterizes social, economic, cultural and political life as a result of such technological innovations. Above all, we have to bring lifestyle change, personal life and the self into the heart of our understanding of AI, and the perspective that I shall develop in the remaining chapters of this book is intended as a contribution to this task. But there are also important considerations to bear in mind when we consider what responses in public policy are most appropriate, and again limitations in the debate between sceptics and transformationalists on AI come plainly into view.

      Getting public policy right on advances in, and the regulation of, AI is an urgent and necessary task for nations worldwide. The new politics of AI has, however, been constrained by the marked scepticism in some policy circles which view the scope and intensity of AI as wholly exaggerated. Rather than developing responses to support new industries and future technologies, this kind of approach emphasizes that economic prosperity depends on industrial manufacturing, productive investment and ongoing government collaboration with the private sector to support job creation. Where innovation in AI technologies and developments in automated production are recognized as significantly impacting upon the economy and employment, much policy thinking remains focused largely on training, education and lifelong learning. For example, Geoff Colvin has argued that the ‘public policy response should include helping today’s young people become winners’.¹⁷ But what, exactly, might ‘winning’ look like in AI-powered societies? And what would be the fate of ‘losers’? Focusing on promoting a winner-takes-all approach is hardly a sound means of developing public policy in this new area of technological innovation.

      We should also recognize that the utility of sceptical and transformationalist standpoints is limited as a guide for practical action towards the development, implementation, adoption and regulation of AI technologies. The scale of the task facing many countries in the wake of the AI revolution is huge, and various countries have made significant progress in developing public policy to confront how people live, work and engage with one another in the context of new technology. In the next chapter, I move on to examine how various countries have developed national strategies to guide strategic investment in AI. It is worth taking a close look at the policy approaches of various countries towards AI – focusing upon such areas as scientific research, skills and education, digital infrastructure and adoptions by the public and private sectors – as this provides an alternative insight into the impacts (both current and future) of AI from that offered in the sceptical and transformationalist literature.

Notes

      1  1 Jaron Lanier, You Are Not a Gadget, Vintage, 2011.

      2  2 Nicholas Carr, The Glass Cage: Automation and Us, Norton, 2014.

      3  3 Sydney J. Freedberg Jr, ‘Artificial Stupidity: When Artificial Intelligence + Human = Disaster’, Breaking Defense, 2 June, 2017: https://breakingdefense.com/2017/06/artificial-stupidity-when-artificial-intel-human-disaster/

      4  4 See, for example, Geoff Colvin, Humans Are Underrated: What High Achievers Know that Brilliant Machines Never Will, Penguin, 2015.

      5  5 For a fascinating critique of these contributions see Ross Boyd and Robert J. Holton, ‘Technology, Innovation, Employment and Power: Does Robotics and Artificial Intelligence Really Mean Social Transformation?’, Journal of Sociology, 2017 (Online First): https://doi.org/10.1177/1440783317726591

      6  6 Joel Mokyr, Chris Vickers and Nicolas Ziebarth, ‘The History of Technological Anxiety and the Future of Economic Growth’, Journal of Economic Perspectives, 29 (3), 2015, pp. 31–50; and Joel Mokyr, ‘The Past and the Future of Innovation: Some Lessons from Economic History’, Explorations in Economic History, 2018 (Online First): https://doi.org/10.1016/j.eeh.2018.03.003

      7  7 Erik Brynjolfsson and Andrew McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, Norton, 2014, p. 8.

      8  8 See Martin Ford, The Rise of the Robots: Technology and the Threat of a Jobless Future, Basic Books, 2015. See also the interesting analysis developed by Ursula Huws, Labor in the Global Digital Economy: The Cybertariat Comes of Age, Monthly Review Press, 2014.

      9  9 Richard Baldwin made these remarks in an interview published as ‘AI and Robots Will Take Jobs – But Make the World Better’, 2019: https://www.pri.org/stories/2019-02-13/new-book-suggests-ai-and-robots-will-take-jobs-make-world-better

      10 10 Paul R. Daugherty and H. James Wilson, Human + Machine: Reimagining Work in the Age of AI, Harvard Business Review Press, 2018.

      11 11 Klaus Schwab, The Fourth Industrial Revolution, World Economic Forum, 2016, p. 1.

      12 12 Schwab, Fourth Industrial Revolution, pp. 109, 112.

      13 13 Bernard Stiegler, Automatic Society: Volume 1. The Future of Work, Polity, 2016, p. 7.

      14 14 Stiegler, Automatic Society, pp. 8–9.

      15 15 Christopher Pissarides and Jacques Bughin, ‘In Automation and AI, Many See a Jobless Future and Higher Inequality. But the Technologically Driven Shift Should Be Welcomed’, 17 January 2018: https://www.interest.co.nz/business/91625/automation-and-ai-many-see-jobless-future-and-higher-inequality-technologically

      16 16 See Anthony Elliott, The Culture of AI: Everyday Life and the Digital Revolution, Routledge, 2019.

      17 17 Martin Ford and Geoff Colvin, ‘Will Robots Create More Jobs Than They Destroy?’, The Guardian, 6 September 2015.