retention rates and help create new job opportunities.
Let us turn now to contrast two transformationalist interventions which centre upon the problem of work and employment. The first is Klaus Schwab’s The Fourth Industrial Revolution, issued by the World Economic Forum (of which Schwab is executive chairman). The second is Bernard Stiegler’s Automatic Society, volume 1 of which is subtitled The Future of Work. There is a telling feature about the writing of Klaus Schwab that several critics have noted, and which pertains to the underlying ardour of his transformationalist stance. Schwab makes it abundantly clear that the AI transformation in manufacturing and services is already well under way. The digital revolution, he contends, is producing ‘exponential disruptive change’, and this can be discerned in the prevalence of advanced robotics, machine learning, big data and supercomputers in business and organizational life today. The scope and scale of the digital revolution for Schwab – what he terms the ‘fourth industrial revolution’ – are ‘unlike anything humankind has experienced before’.11 Yet if Schwab’s transformationalism is clearly evident in this diagnosis of our times, his critique of the consequences of AI appears (at least on an initial reading) as scrupulously non-judgemental. Employment is a signal example. Schwab contends that AI ushers in massive efficiency gains and cost reductions for businesses and industry, but also highlights the massive automation of jobs stemming from these very developments. On the one hand, he emphasizes that technological innovation today destroys jobs as never before, whilst on the other hand he underscores that AI unleashes a new era of prosperity through the creation of novel employment opportunities and future industries. He argues that AI disrupts labour markets and workplaces around the world, and yet emphasizes the ability of workers in the new economy to adapt continuously and fashion new skills through lifelong learning.
In other words, Schwab’s approach seeks to capture both the stunning opportunities and threatening risks stemming from AI. Pressed to an extreme, however, his analytic approach is never free from a certain degree of ambivalence, as every social change associated with the digital revolution appears mediated through this both/and logic. This might be said to be the conceptual equivalent of wanting to have your cake and eat it too. Towards the latter sections of The Fourth Industrial Revolution, Schwab’s analytic reserve – where his lack of a conclusion on the consequences of AI becomes a conclusion all of its own – gives way to a more robust transformationalist sensibility. As he concludes:
The digital mindset, capable of institutionalizing cross-functional collaboration, flattening hierarchies, and building environments that encourage a generation of new ideas, is profoundly dependent on emotional intelligence . . . The world is fast changing, hyper-connected, even more complex and becoming more fragmented but we can still shape our future in a way that benefits all. The window of opportunity for doing so is now.12
In the end, AI for Schwab is an exhilaratingly progressive affair. He argues that AI has the potential to be institutionalized as a global, cosmopolitan form of life, one to be celebrated rather than castigated.
In contrast to this business-school approach to understanding AI, radical French theory informs Bernard Stiegler’s Automatic Society. Like Schwab, Stiegler holds that the AI revolution is already upon us. AI for Stiegler inaugurates a new social order of ‘total autonomization’, in which production and manufacturing are controlled by software and big data. But unlike Schwab with his stab at analytic even-handedness, Stiegler is out to develop a more full-blooded critique of the destructive aspects of AI for economy and society. He writes, for example, of today’s ‘immense transformation’ whereby ‘capitalism becomes purely computational’, of ‘generalized autonomization and autonomisms’, and of ‘algorithmic governmentality’. Taking his cue from the post-structuralist analysis of ‘control societies’ developed by Gilles Deleuze, Stiegler seeks to lay bare the short-circuiting of minds and spirits – the ‘shock and stupefaction’ inflicted on contemporary women and men – arising from full automatization. Drawing upon quantum physics, Stiegler argues that automatized societies are increasingly locked in a contradictory relationship between entropy (where life-energy dissipates) and negative entropy (the reversal, or undoing, of such decomposition). ‘Automation’, writes Stiegler, ‘has given rise to an immense amount of entropy, on such a scale that today, throughout the entire world, humanity fundamentally doubts its future – and in young people especially so.’13 Google Translate, as Stiegler remarks, is a good example of the immense linguistic entropy occurring throughout the world today, as split-second machine translation of the world’s diverse languages into English results in a radical impoverishment of vocabulary. Google’s algorithms simply flatten both the individual and collective use of language. What is at stake, as Stiegler shrewdly points out, is human knowledge in the broadest sense; knowing how to think, reflect, talk, communicate and act in the world.
If for Stiegler Google Translate represents destructive linguistic entropy, the algorithmic automation of society signals massive economic entropy. AI makes it possible not just to economize upon labour, but to fully automate tasks and thus render employees redundant. This is a redundancy of the worker’s expertise, as advanced automation for Stiegler produces a generalized (economic as well as environmental) ‘disorder of hyper-standardization’ – where work, and the value of employees, are determined by calculating probabilities based upon averages. Today’s industrial capitalism, writes Stiegler, is ‘an era in which calculation prevails over every other criteria of decision-making, and where algorithmic and mechanical becoming is concretized and materialized as logical automation and automatism . . . as computational society becomes a society that is automated and remotely controlled’.14 We are at the beginning of a process of technological transformation that will have a massive impact upon the nature of work, expertise and knowledge – the algorithmic governmentality of 24/7 capitalism, according to Stiegler, will precipitate ‘entropic catastrophe’.
The new technological landscape, however, results not only in doom and gloom. Stiegler also seeks to discern a hidden trend in economic entropy for reversing the devastating impacts of algorithmic capitalism. Emancipation for Stiegler is linked to the primacy of meaningful work, which he sharply differentiates from employment. In this perspective, work is fundamentally meaningful and creative, whereas the bureaucratized terrain of employment is increasingly automated and dependent upon computational software. His argument, broadly speaking, is that the production and transformation of automation prepare the way, paradoxically, for the ‘dis-automatization of society’. In a striking irony, the kind of employment which is bound up with automated entropy also consists in de-automating routines, which can liberate most of the population from exploitative domination. If employment is increasingly the terrain of advanced automation, complex algorithms and computational software on the one hand, work produces value and the creation of something new to society on the other hand. From this angle, Stiegler emphasizes that work consists of practical know-how (savoir-faire), formal knowledge (savoirs formels) and life skills (savoir-vivre). The ‘data economy’ is therefore not the inevitable destiny of automated society; a range of other possible systems can be envisaged. This scenario, Stiegler proposes, is already practicable. We have reached a stage, in algorithmic capitalism, in which the automated forces of production are overdeveloped and new economic models based on the social economy and cultural solidarity – especially through associations, cooperatives and public services, as well as new industries – will create novel, intermittent forms of work and new professions. A non-repressive automated society, Stiegler argues, would become an ‘economy of contribution’.
How is it possible that there should be such significant differences in assessment between two authors associated with the transformationalist position? To begin with, Stiegler’s writings serve as an apt counterbalance to Schwab’s emphases, particularly the former’s penetrating analysis of the very large decline in jobs worldwide resulting from advanced automation. Schwab’s work is explicitly concentrated on how organizations create value, and he repeatedly emphasizes that technological transformation today creates new opportunities and dilemmas – the results of which can lead to positive, shared benefits for all of society. Stiegler on the other hand clearly does intend his analysis to have a very broad application: not just economics and the market, but society and the politics