At the close of 2022, there remains quite a lot of industrial and manufacturing assets that just won’t be relevant for much longer. Much of it will become stranded and subject to demographic decline. But not all of it will have to be replaced. In the fractured world that is emerging, the longer and more tortuous a supply chain is, the more open it is to irrevocable and even catastrophic collapse. Rebuilding resilient global supply chains during the SARS-CoV-2 viral pandemic was a signal that something was not as it should be. CARICOM short-haul intraregional traffic may increase as manufacturing footprints disperse into networks of campuses that are themselves assemblages of linked work packages dispersed over a terrain that is both mountainous, and largely water.
Many of the technologies deployed under globalization will not be applicable because the global environment is adapting to the “Twin Transitions” to a green and digitalized world. These shifts are interlaced and put every achievement of previous upheavals into the footnotes of history. The 4th Industrial Revolution brings into being a new humanity of machine learning, globotics, edited life, and interfaces. The world we have made until now – is not the limit for humanity. Ahead is a broken past and a divided future.
Demographic decline, which peaked in the golden pre-Corona era, may influence deeper fracturing of the global system, further reducing overall global income and wealth. But it will be inside the fragments, that the greatest need to replace stranded industrial and manufacturing plants and infrastructure with new types of factories will reside.
The new clades and species of factories will have features unseen before. Features unlike those that preceded them. The new norms of deglobalization will not demand the simple formula of disassembling an electric vehicle and reassembling it in a new location. It will require the disassembly of an EV and reassembling it as a high-tech cherry tomato robot picker that reaps and learns inside “Plant Factories” and “Vertical Farms” that produce edited foods using optimization analytics, artificial lighting, and sensors.
This shift always unearths the misplaced fear that workers will be left worse off by automation and the interplay of globalization and robotics, a process described as “globotics” by Richard Baldwin. But centuries of industrialization and automation in developed economies have uncovered no evidence of competition with machines for jobs, lowered earnings and displaced workers. Since the Luddites, two hundred years ago sabotaged factory equipment in Britain, workers have feared “The Rise of the Machines”.
But the facts always collide with the fiction. Automation can raise employment in a given industry even as it reduces the labour needed per unit of production, by reducing costs sufficiently to generate large increases in overall product demand. In such instances, the percentage increase in production surpasses the percentage decline in labour needed per unit.
This happened three times already. The Ford factory assembly line to produce the Model T resulted in substantial price reductions. For the first time, middle-class Americans of the Ford era could purchase a combustion-engine automobile. This generated enormous growth in jobs. When the price of the personal computer fell in the 1980s and 1990s and the purchase of the PC became commonplace the same thing happened. In the early 2000s, the same thing happened when cellular phones reached the market.
Conversely, if price reductions and income elasticities are not sufficient to drive new product demand in innovations to offset per-unit reductions in labour demand, then employment might decline. In a Brookings Paper on Economic Activity by David Atour and Anna Salomons (2018), it is argued that even if overall employment remains constant over time despite automation, two groups of workers may still not fare well even prior to automation. The first group of workers will be those with skills similar to those displaced, who now face low demand in the same or other industries. The second group will be those directly displaced by automation.
While industrial economies have constantly shown the ability to create enough jobs to replace those that have become automated, many commentators fear that the reach of AI embodied in robots and other forms of “artificial life” will go far beyond routine and mundane tasks. By using machine learning and algorithms to process vast quantities of Linked Data stored in data cooperatives and data lakes, and continuously updating its analytical and adaptive power, AI will increasingly be able to discern intricate arrays and fractal patterns in such data and make judgements on pathways in a spectrum of environments and circumstances that outpace human workers. Environments like financial markets, and freight forwarding will encompass robots in fulfilment centres, and maritime autonomous surface ships.
This requires a response from the school and the university to ignite the slow fuse of the imagination. Systems of education at each level of schooling and pupillage which make “Doubt” and “Evidence” the epistemological foundation of curriculum architectonics. Careful scrutiny of the number of work permits issued over a specific period of time will underscore the skills that are not outputs of the existing ecology of schooling. If the skill exists, then the application for a work permit would fail naturally.
