Making Sense of AI. Anthony Elliott
of deeper technological shifts in the scale of economic organization and social relations worldwide. This can be discerned, argue transformationalists, in the rise of advanced automation, supercomputers, 3D printing, Industry 4.0 and the Internet of Things. AI technologies, including robotics and advanced digital systems that deploy deep learning, neural networks, machine decision-making and pattern recognition, have given rise to an era of intelligent machines which can increasingly sense their own environments, think, learn and react in response to data. The rise of neural networks, a kind of machine learning roughly modelled on the human brain, consisting of deeply layered processing nodes, has been especially consequential for the powering up of AI-based economies and societies. Today, fewer and fewer things are removed from the impress of AI, and every phenomenon, including private life and the self, seems influenced by self-learning algorithms to its roots.
Box 2.1 Sceptics
1 Sceptics show some recognition that AI is sweeping through industries, enterprises and public life, but AI is not viewed as revolutionary. On the contrary, ‘no significant change’ is the motto.
2 For many authors of a sceptical persuasion, AI as a transformative power is recast as little more than marketing hype or a myth.
3 Rather than a transformed world economy powered by AI, sceptics advance a business-as-usual model comprising technological advances on the one hand, and adaptation by the labour force on the other hand.
4 There is an emphasis upon workplace change as involving the twin forces of people and machines, employees and technology.
5 It is implicitly acknowledged that AI poses a risk to some jobs (mostly routine, unskilled work, according to sceptics), but in general the position advanced is that AI will create more jobs than it destroys.
6 There may be some spillover from AI breakthroughs that impact society, culture and everyday life – especially the globalizing forces of communication. Nonetheless, AI is primarily a technological process which principally impacts the economy in limited and partial ways.
7 For many of a sceptical persuasion, traditional economic power is paramount and the actions of national societies are important too. Accordingly, the globalizing dimensions of AI are treated as contingent on these economic and national state factors.
Central to this transformationalist perspective is an emphasis on the social relations impacted by AI. That is to say, the technologies associated with AI are understood to reshape not only institutions and organizations but also identities and intimacies. Another way of making this point is to say that the AI revolution is as much about entertainment as it is about the economy, as much about meaning and morality as it is about money and manufacturing. For lifestyle change is likely to be of key importance in the spheres of both professional and personal life when assessing the impacts of AI, or so argue transformationalists. As Erik Brynjolfsson and Andrew McAfee write of these massive changes in The Second Machine Age: ‘Computers started diagnosing diseases, listening and speaking to us, and writing high-quality prose, while robots started scurrying around warehouses and driving cars with minimal or no guidance.’7 Brynjolfsson and McAfee capture well the idea that digital transformation is not only about the economy, industry and corporate life, but crucially also about sociality, everyday life and power. The advance of AI is, in a word, generative. The digital revolution creates different kinds of work and different sorts of skills and gives rise to different ways of living from those of even the very recent past.
Transformationalists question the idea that economy and society can be adequately grasped from the business-as-usual perspective advanced by sceptics. For the extensive penetration of the global economy by digital forces has fundamentally altered its operations and dynamics. Transformationalists generally underscore the essential significance of the digital revolution, an historic moment in the worldwide transformation of manufacture and services. This involves locating contemporary patterns of globalization within the new technological revolution, and a dazzling variety of terms has been coined to capture these momentous shifts – including ‘Industry 4.0’, ‘digital capitalism’, ‘algorithmic governmentality’, ‘bot economy’ and ‘automated society’. Three aspects of change tend to be emphasized in the transformationalist literature: the radical transformation of manufacture and services, of consumption and citizenship, and of public policy. In transforming both the conditions and consequences of economy and society, according to this argument, AI, robotics and other forms of automation have revolutionized corporate life and businesses across the world. Advances in machine learning algorithms and big data in particular have underpinned extraordinary innovations in the manufacturing of goods and services as well as the emergence of new industries, and consequently jobs and employment have come under assault as never before. The impact of smart software, and of social media more generally, has significantly transformed the consumer economy itself. At the same time, these unparalleled technological innovations directly impact upon issues of ethics and governance. Recognizing how closely the impact of AI on jobs and public policy are intertwined, governments worldwide have sought to introduce a raft of measures geared towards enabling robust engagement with the digital revolution.
If you accept the argument that AI involves the transformation of manufacturing and services between and across the world’s advanced economies and societies, then it follows logically that there will also be a wholesale shift at the base of the job skills pyramid, with very broad employment implications as well as the prospects of massive unemployment. As AI reorganizes the global economy, so transformationalists argue, blue- and white-collar jobs alike increasingly evaporate. The transformationalist story of what this will do to jobs and the future of employment is, however, multilayered and complex. For some transformationalists, the economic consequences of increasing automation are clear: the proportion of the labour force in manufacturing will decline sharply in all the industrialized countries. Martin Ford, in The Rise of the Robots, equates AI and automated technology directly with the threat of jobless futures. From telepresence robots to the digital offshoring of high-skill jobs, Ford sees a relentless AI-driven technology trend towards rising unemployment and greater inequality.8 Seeking to shift the debate beyond the conventional solution that increased education and training will facilitate better adaptation by workers into new, higher-skill roles, Ford argues the case for a new economic paradigm, one based on a guaranteed income or living wage that incentivizes risk-taking and entrepreneurship. Similarly, Richard Baldwin’s The Globotics Upheaval views the disruptive impacts of digital technology as wall-to-wall, resulting in an unparalleled displacement of jobs worldwide. In Baldwin’s telling of the transformationalist narrative, however, these negative impacts will be mostly short-lived, opening the way for a more optimistic prognosis of automated technology in the long run. As Baldwin comments:
I view AI . . . as a good thing once we can get through the transition. People’s jobs will be more interesting because all the robotic repetitive stuff will be done by machines. Things that can be done remotely will be done remotely and that will allow us to do things where we actually have to be together. So, ultimately, I think it will be a very, very good thing.9
An excessive zeal also applies to other aspects of the transformationalist position, especially as regards the creation of new jobs. Transformationalists contend that automated production destroys jobs within industrial manufacturing. But, within this literature, there is also the argument that AI is creating new jobs elsewhere in the economy. An extraordinary range of knock-on services and jobs, especially roles performed as ‘digital work’, has been unleashed by the rise of AI – which, in turn, has led to the emergence of new industries, businesses and even occupations. As Paul R. Daugherty and H. James Wilson argue in Human + Machine: Reimagining Work in the Age of AI: ‘In the current era of business process improvement AI systems are not replacing us; they are amplifying our skills and collaborating with us to achieve performance gains that have previously not been possible.’10 In today’s circumstances, argue some transformationalists, the future of jobs increasingly depends on AI–human collaboration. In this view, the deployment of human–machine hybrid teams dramatically improves productivity and thereby increases prosperity. Other transformationalists highlight that AI and machine learning algorithms (based on big data) underpin the