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Reading Between the Lines of Automation Employment Forecasts

Potential job losses from automation aren’t a new concern, but the issue has appeared to spike in the last few months with a spate of new studies that forecast how automation will affect work in different global regions and sectors. If you take a quick glance at the headlines, the situation looks distressing, and headlines seem aimed to produce maximum alarm: Special Report: Automation Puts Jobs in Peril! Robots Do Destroy Jobs and Lower Wages, Says New Study. Automation Could Slash Jobs in Developing Countries.

A look behind the headlines reveals more nuance though. For starters, quantified predictions about the numbers of potential jobs lost are only calculations about whether the technology exists to replace a certain task or occupation. When you dig behind the numbers, the number of factors required to implement automation in the workplace multiplies considerably: legislation and regulation, affordability, and specific business considerations all have an important role to play.

The best prediction to date may come from a study on artificial intelligence and automation completed last December by the Council of Economic Advisors under the Obama Administration, which said that, “Given the available evidence, it is not possible to make specific predictions. So policy makers must be prepared for a range of potential outcomes” in the United States.  This is largely because of additional critical factors, such as “other forms of technological change, globalization, reduction in market competition and worker bargaining power, and the effects of past public policy choices.” 

This is a version of good news. It tells us that policy planners, business owners and not least, citizens and workers, have agency and options about how best and at what pace to implement automated labor.  The alarmist language in the headlines that tells us that the machines are in charge and coming for our jobs isn’t quite right. And it certainly isn’t good for us. It paralyzes us into thinking that we are endangered and helpless victims of a force that lies beyond us. But paralysis is probably a quick route to unpleasant and possible large scale disruption. Why not choose wise and coordinated collaboration across sectors to better manage the shift to highly automated economies?

I have compiled a 1-page reference page of the current predictions and links to recent major studies. If you’d like to download it for yourself, you can find it here.

Each month, the Catalyst provides a quick list of useful and provocative sources for thinking more deeply and building strong strategic narratives in our institutions, communities and nations. This month:

Book: The Cunning of Uncertainty by Helga Nowotny

Once perceived as a “carrier of opportunities,” uncertainty has come to be perceived as a threat and as something to be mitigated as much as possible. Yet, despite the ability of ‘big’ data to limit uncertainty in some circumscribed situations, we will never be able to eliminate it entirely (thus, its ‘cunning).  Nowotny, the former president of the European Research Council, aims to resuscitate the virtues of uncertainty especially in the arena of knowledge production in science and technology.  In these realms, progress only occurs when researchers push against the boundaries of what is already known and into the region of uncertainty, where any knowledge gained is provisional, as what is yet unknown may challenge it later.

Nowotny’s book is wise and surprisingly lyrical, given the topic matter. Although it is surely difficult to relinquish our fears of uncertainty in the midst of rising complexity and systemic risk, Nowotny reminds us of the good reasons we have to do just that: “Uncertainty is the dynamic balance between what we know and do not yet know about the world and about ourselves. Recognizing its cunning and entering into collusion with it enables us to exploit the dynamic balance in favor of moving on. It opens the cracks in the wall to let the new in.”  You can find The Cunning of Uncertainty here

Theory about the Evolution of Societies: Tribes, Institutions, Markets and Networks by David Ronfeldt

David Ronfeldt, a former analyst at the RAND Corporation, first proposed his theory that all societies contain aspects of Tribal, Institutional, Market-based and Networked forms of social organization in 1996, nearly twenty years ago. Yet I have found myself recommending his work frequently in the last few months, perhaps because the once-fanciful premise that social and economic foundations laid during the industrial revolution could radically change now seems to be a palpable likelihood.  Theorists like Ronfeldt help us understand how different forms of social organization generate societies with different capabilities and weaknesses, and thus about how we might influence the evolution of our own in productive directions.

In Ronfeldt’s elaboration, different forms are prevalent in different periods and each embodies distinct values and metaphors, modes of economic exchange, behavior and governance. Whereas the key value of a tribal world was ‘belonging,’ in a market dominated society, it is ‘freedom.’  Public goods are the primary products of a world in which public institutions such as central governments, are dominant;  the primary products of a networked world might be collective goods.  The TIMN framework is well elaborated, but it is also open-ended: A great way to engage with it would be to question whether the further evolution of our information technology will generate another evolutionary step, or to ask how we could promote existing forms to best advantage.

Resources can be found in the following places:  In an explanatory essay published by RAND, here,  in a twenty minute video, in which Ronfeldt explains his thoughts, here,  and at his blog, Two Theorieshere

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  • The Chinese Global Television Network program The Heat recently featured a panel discussion about the future of automation in relation to employment, the economy and society. I was pleased to join Michael Chui, parter at McKinsey Global Institute and Joanna Wei, co-founder of Beijing MakerSpace for the discussion.  You can find links to the program description here and to the video program in three parts: Part 1, Part 2 and Part 3
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