of human skills and cognitive abilities. Nicholas Carr, a former editor of Harvard Business Review, is one of the most influential authors to argue that the risks arising from advancing automation have been radically underestimated. In The Glass Cage: Automation and Us, Carr contends that what is really sinister about automation is just how far it erodes autonomy.2 This is a theme he has pursued in his writings for some considerable period, dating back to a 2007 article he wrote in The Atlantic, ‘Is Google Making Us Stupid?’ He says that the automation of economy and society is double-edged: promising undreamt-of opportunities and new freedoms on the one hand, and yet impairing human expertise and deskilling women and men in profound ways on the other. It is just this contradiction that Carr detects in the widely discussed 2009 case of Air France Flight 447, which crashed into the Atlantic Ocean en route from Rio de Janeiro to Paris, killing everyone on board. Having entered a powerful storm, the aircraft’s autopilot system disconnected, after which the crew sought to regain control of the plane, but due to further complications were unable to do so. The catastrophic failure occurred, Carr contends, because the pilots had become overly reliant on automated systems, thus finding themselves unable to control the aircraft once flight computers had shut themselves off. It is just this radical deskilling effect which has elsewhere been referred to as the rise of ‘artificial stupidity’.3
If one sceptical response to the rise of AI is to shrink the whole phenomenon to the category of myth, and another casts AI as a particular selection of technical values which diminishes human capacity, there is still another, third response which addresses more soberly the effects of AI on economy and society. From this standpoint, AI is neither dissociated from economy and society nor wholly interwoven with them. AI is rather a form of technological threshold which facilitates social opportunities and economic risks. Authors who write from this sceptical position believe that the impacts of AI are not dramatic and will take a considerable period of time, possibly many decades, to be fully realized at any rate. Should one pay any attention to claims of an AI revolution? Many sceptics say ‘no’. What, ask the sceptics, is ‘revolutionary’ about AI? Rejecting the equation of technology and transformation, this line of sceptical criticism develops a conception of workplace change which focuses squarely on the adaptability of employees, the enhancement of skills and new forms of economic efficiency and organizational innovation.4 Such a standpoint thus ties talent and technology firmly together. Such sceptics develop an argument for the continued primacy of workplace productivity, workers’ skills and emerging patterns of adaptation to technological innovation. From this standpoint, there is a clear disjuncture between the widespread innovations of AI and the world of work in which, for the most part, employees adjust to new technologies and find continued opportunities to acquire skills and capabilities.
This sceptical encounter is thus one which emphasizes people with technology – of a cultural response underscoring adaptation, adjustment and processes of reorganization. The idea that AI triggers a sudden lurch from one socio-economic system to another – say, industrial manufacture to new industries centred on digitalization – is rejected. To understand why this is so, a number of prominent economic historians contend that AI must be assessed against long-term patterns of historical change.5 From this broader standpoint, it is possible to better understand why AI is unlikely to mark a radical disjuncture in history. This is an argument for the ongoing centrality of established economic power and industrial production, with many sceptics discerning a mobile relation in the intersection of past and present across the forces of technological innovation. Modernization, and specifically the mechanization of agriculture, did not destroy economic and social exchanges in conditions of modernity, so why should the technological innovations of AI be any different? Only an historical approach to economy and society can be truly empathetic, capturing the long-term trends of political struggle in workplace change as well as the broad insight that technological innovation has, by and large, created more jobs than it has destroyed. This is not to deny the potential for social change, or economic dynamism. But if technological change and economic productivity are viewed as intersecting, so that the centrality of employment is emphasized, then innovations which were widely thought to be radical or transformational may in fact be more continuous or stable. In brief, technology-driven innovation in the era of AI is likely to produce more jobs and wages growth.6 Or, so argue the sceptics.
The three distinct positions on AI sketched above tend to be linked to varying standpoints on technology and its impact on economy and society. According to these sceptical interpretations, the evolution of technology moves both with and against the grain of historical progress. But nothing at the level of technological innovation, it is argued, can be transformative of the economy unless it somehow takes its cue from culture and the wider, resourceful, reflective responses of human agents. For many sceptics, AI disturbs and disrupts, because the technological advances it ushers into existence have been largely unforeseen, thus taking the world by surprise. By roping AI firmly within those industrial practices associated with modernity, however, sceptics conclude that AI is unlikely to have any major or lasting impact upon the very social order of which it is the product. In short, this is a business-as-usual scenario in terms of economy and society. The three different positions recognize, to some degree, that what we witness today are significant differences between newer and older techniques of production and manufacturing. Yet sceptics reject as intrinsically flawed the idea of AI dissolving the boundary between the real world and the digital universe. It follows from this that there are also other ways in which these three sceptical positions on AI intersect. The idea of AI as creating a novel way of life – generating changes in lifestyle patterns – is viewed by sceptics as a massive public relations campaign to advance the commercial interests of tech companies. Similarly, arguments that intelligent machines can increasingly perform tasks once imagined to be purely the domain of human agents do not get much of a hearing from sceptics.
Transformationalists
By contrast, the current of cultural experimentation that I shall call transformationalism develops a very different interpretation of AI. Transformationalists reject the claim advanced by sceptics that AI is a synonym for hype, or a cover story for tech companies. Whilst certain sensationalist aspects of the discourse of AI are not denied, the transformationalist response emphasizes that AI is an expression 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
