Abstract:
Since Klaus Schwab of the World Economic Forum’s announcement in 2016 of the impending Fourth Industrial Revolution (4IR) in his book of the same title, the world has been swept up in the wave of global hype around the extraordinary potential for 4IR technologies – artificial intelligence, robotics, drones and blockchains – and the dire fate of nations who fail to embrace these inevitable technological developments. This has now been repackaged by Schwab and the WEF in the context of the COVID-19 pandemic as the BIG RESET.
There has been a disconcerting lack of critical engagement with the concept intellectually, politically and particularly from a policy perspective. A range of institutions from Ivy League universities, international industry conferences, multilateral agencies, development banks and regional economic commissions have enabled it becoming policy conventional wisdom. At the same time international donor agencies and governments are diverting public funding from pro-poor policy research agendas on digital inclusion to artificial intelligence as well as robotics, machine learning, drones and blockchain. While technologies associated with large industrial shifts can be disruptive and certainly digital technologies associated with what is referred to as the third industrial revolution have developed rapidly in relation to earlier technologies to disrupt industries and their incumbents – take uber and the taxi- industry or air b&b and the hotel industry – they tend to be more evolutionary than the rhetoric suggests.
This ahistorical and technologically deterministic appropriation of the term 4IR by probably the most powerful global epistemic community in history, the World Economic Forum, has been arguably one the most successful lobbying and policy influence instruments of global big capital ever. Organising around the elite annual gathering in Davos to build consensus between the private and public sector on the future of the world, the privately resourced policy blueprints on the 4th IR – replicated by the big international consultancies whether for Singapore, Rwanda or South Africa – fills a vacuum for many countries, that have not publicly invested themselves in what they want the future to look like. With visions of global prosperity, packaged with futurist conviction and economic forecasts of exponential growth and job creation, they appear to provide a roadmap in an uncertain future.
There is nothing inherent in so-called 4IR technologies of artificial intelligence, blockchain or drones that will result in economic growth, job creation or empowerment of the marginalised. Evidence from the so-called third industrial revolution (of which some see current digital developments simply as an intensification) tells us we should not take for granted that technology will translate into wage or productivity growth – unless we develop a good set of complementary policies, both as the public and private sector. Certainly it the task is too big for either to do on its own. On the contrary, unless there are targeted, evidence-based policy interventions that do something differently from what we have done in the past – or implement policies that we have failed to – the introduction of more advanced technologies will simply amplify current inequalities.This digital inequality paradox is arguably the biggest policy challenge for nations. It is not addressed through the discourse of the 4th industrial revolution, no matter in how revolutionary the narrative in which it is presented.
Some of the developments have been incremental and some disruptive, but they have all been highly uneven. Today, information generation, processing and transmission, critically define who benefits from the transformative potential of digitalisation. Global platforms have been the major beneficiaries and creators of the new value created by these processes. Their dominance of markets through the control of data, as well as their capacity to create and capture value, have resulted in their concentration and consolidation in a very few countries and a handful of companies.
Instead of examining technological developments we will examine the increasingly globalised trends towards digitalisation – and now ‘datafication’ – which now impact every aspect of social and economic activity. Established technologies that led to the development of the Internet in the latter part of the 20th century, and ultra-highspeed broadband networks at the turn of the century, have been augmented over the last decade by ‘free’ applications running ‘Over-The-Top’ (OTT) of such infrastructure (such as social networks), and the Internet of Things (IOT), which is able to remotely measure, monitor and record information. With the emergence of advanced technologies merging the physical and digital realms, artificial intelligence (AI) and machine-learning technologies enable the collection, use and analysis of vast amounts of digital data arising from personal, social and business online activities.
With the rise of these technologies, developing countries cannot abandon or be distracted from other more fundamental digital projects, often necessary precursors to any technological take off, to address these new challenges. These changes tend to build upon earlier developments, which are often overlapping and the outcomes uneven and contradictory. In fact, prioritising, current demand-side constraints on digital inequality – including access and affordability of information infrastructure, institutional capacity and capability and human development – will reduce the unevenness of the positive and negative impacts.
The hyper-globalised and uneven nature of these developments have implications for the United Nations (UN) 2030 Sustainable Development Goals (SDGs), a significant number of which are underpinned by global ICT targets that the region is way off meeting, giving rise to fundamental challenges for policymakers in countries at all levels of development. Whether countries and regions are able to create the conditions for the exploitation of these process of digitalisation and datafication to create added value, increase efficiency and productivity, create new jobs and maximise revenue generating trade and taxation, will depend on the policies adopted and implemented, as this is a common institutional challenge for developing countries. “Harnessing its potential for the many, and not just the few, requires creative thinking and policy experimentation” (UNCTAD 2019:1). While it will present challenges at different levels of government, its globalised nature will nevertheless require greater global cooperation to overcome many of them.