Benedict Dellot and Fabian Wallace-Stephens – RSA
This is a refreshing post about the implications of work being displaced by machines, which isn’t about the work, the displacement, or the machines. Instead it puts forward a range of suggestions about what would need to be in place to make the consequences of that displacement socially and economically beneficial.
The ideas themselves are still fairly undeveloped at this stage – this is more a prospectus of issues to be explored than the substantive exploration – but even in embryonic form, they demonstate that a wider range of responses is possible than is often assumed. At first sight, some of the ideas look considerably more robust than others, but regardless of their specific merits, being imaginative about ways of dealing with the consequences of technology change must be a better strategy than trying to impede it.
Richard Susskind – The British Academy Review
The debate about the scale of the impact of automation on employment rumbles on. Opinions vary enormously both on the numbers and types of jobs affected and on the more esoteric question of whether jobs or tasks are the more useful unit of measurement.
This short article neatly sidesteps that debate altogether. Its focus is on outcomes, the things we want to achieve. They will remain unchanged even as the means of achieving them changes radically. So the core question is not whether the way humans achieve the outcome can be replicated by robots and AI, but rather whether there is an alternative – and perhaps very different – way of achieving the same outcome in a way which is optimised for machines, not people.
Framing the question that way does two things. The first is that it brings some much needed clarity to a complex issue. The second is that all of us who have been congratulating ourselves on our irreplaceability need to start worrying much sooner than we might have thought.
Louis Hyman – The New York Times
This is a good reminder that the development and, even more, the application of technology are always driven by their social. economic and political context. There is a tendency to see technological change as somehow natural and unstoppable, which is dangerous not because it is wholly wrong, but because it is partly right and so can easily be confused with being wholly right.
New technologies cannot be uninvented (usually) or ignored, but how they are developed and deployed is always a matter of choice, even if that choice isn’t always self-evident. This article focuses on the implications for employment, where too often the destruction of jobs is assumed to be both inevitable and undesirable (leaving only the numbers up for debate). But the nature of the change, the accrual of the benefits of greater efficiency and of the costs of disruption and transition are all social choices. That’s a very helpful reframing – which creates the space to ask how we might retain the benefits of traditional employment structures, while adding (rather than substituting) the advantages which come from new ways of working.
Benedict Dellot – RSA
You can find an estimate for the impact of automation on jobs to support more or less any prior opinion you happen to hold. Apparently sensible forecasts from apparently respectable organisations range from the benign to the apocalyptic. One reason why it can be hard to make sense of that is that different factors – some potentially with opposite effects – can get bundled together into an agglomeration of technologies in an agglomeration of sectors and contexts having an agglomeration of effects. Disentangling any of that then becomes next to impossible
This useful short post separates out four different forms of automation, briefly explaining the employment impact of each. That doesn’t magically give us a single number which is somehow better than all the other single numbers. But it does provide a framework for understanding and debating all the other single numbers.
Ben Proctor – Sartori Lab
The rather counter-intuitive idea that open-plan working might reduce the rate at which people talk to each other has been getting quite a lot of coverage recently, no doubt for man bites dog reasons. This post goes beyond that to ask a vital, but less obvious, point – that we can’t know what environments promote or detract from collaboration without a clearer sense of what we mean by it and how we might measure it. In other words, even – or perhaps especially – in the case of an apparently mundane issue such as office layout design, evidence-based iterative test and learn approaches really matter.
And in the week that the new UK Government Estate Strategy was published, that may be particularly pertinent.
Benedict Dellot and Fabian Wallace-Stephens – the RSA
The RSA has established itself as a source of insight on the future of work and the intersection of technology and employment, avoiding the hyperbole and hysteria which all too often characterises work in this area. Now they are building on that by setting up a Future Work Centre to explore these issues systematically. That’s definitely one to keep an eye on.
The launch event at the RSA was recorded and can be watched here:
Sharon O’Dea – Intranetizen
AI is often written about in terms of sweeping changes resulting in the wholesale automation of tasks and jobs. But as this post sets out, there is also a lower key version, where forms of AI appear as feature enhancements (and thus may not be apparent at all). Perhaps self-generating to do lists are the real future – though whether that will be experienced as liberation or enslavement is very much a matter of taste. Either way, AI won’t be experienced as robots, breaking into the building to take our jobs; instead tasks will melt away, enhanced in ways which never quite feel revolutionary.
Erin Winick – MIT Technology Review
This devastatingly simple short post brings together estimates of the employment effects of automation, and assesses their consistency and coherence. There turns out to be none: ‘we have no idea how many jobs will actually be lost to the march of technological progress.’
Tim Harford – the Undercover Economist
One of the problems with predicting the future is working out when it’s going to happen. That’s not quite as silly as it sounds: there is an easy assumption that the impact of change follows closely on the change itself, but that assumption is often wrong. That in turn can lead to the equally wrong assumption that because there has been limited impact in the short term, the impact will be equally limited in the long term. As Robert Solow famously put it in 1987, ‘You can see the computer age everywhere but in the productivity statistics.’ In this post, Tim Harford updates the thought from computers to robots. The robot takeover isn’t obviously consistent with high employment and low productivity growth, but that is what we can currently observe. The conclusion – and the resolution of the paradox is disarmingly simple, if rather frustrating: wait and see.
Michael Weatherburn – Resolution Foundation
This post introduces a longer paper which takes the idea of understanding the future by reflecting on the past to a new level. The central argument is that digital technologies have been influencing and shaping the industry sectors it examines for a long time, and that that experience strongly suggests that the more dramatic current forecasts about the impact of technology on work are overblown.
The paper’s strengths come from its historical perspective – and, unusually for this topic, from being written by a historian. It is very good on the underlying trends driving changing patterns of work and service delivery and distinguishing them from the visible emanations of them in web services. It does though sweep a lot of things together under the general heading of ‘the internet’ in a way which doesn’t always add to understanding – the transformation of global logistics driven by ERP systems is very different from the creation of the gig economy in both cause and effect.
The paper is less good in providing strong enough support for its main conclusion to justifying making it the report’s title. It is true that the impacts of previous technology-driven disruptions have been slower and less dramatic to manifest themselves than contemporary hype expected. But the fact that hype is premature does not indicate that the underlying change is insubstantial – the railway mania of the 1840s was not a sign that the impact of railways had peaked. It is also worth considering seriously whether this time it’s different – not because it necessarily is, but because the fact that it hasn’t been in the past is a reason to be cautious, not a reason to be dismissive.
It’s often tempting – because it’s easy – to think that the way things currently are is the necessary and natural way of their being. That can be a useful and pragmatic assumption. Until it isn’t.
James Manyika, Susan Lund, Michael Chui, Jacques Bughin, Jonathan Woetzel, Parul Batra, Ryan Ko, and Saurabh Sanghvi – McKinsey
Much is being written about how robots and automation either will or won’t displace lots of employment, often with breathless excitement as a substitute for thoughtful analysis. This report brings a more measured approach, in every sense. Its focus, as seems increasingly sensible, is less on the end point of change (which can’t be known in any case) and much more on the pace and direction of change. It also pays as much attention to the jobs which will be created as to those which might be displaced, which must be right as it is the net effect which really matters. The conclusion is that up to 2030, jobs will be created in sufficient number to offset the effects of automation – but that that overall stability may involve 375 million people around the world and 6.6 million in the UK being displaced from their current occupation, in part because an estimated 8 or 9% of jobs by 2030 being in occupations which haven’t existed before.
Chris Weller – World Economic Forum
This is a beguiling timeline which has won a fair bit of attention for itself. It’s challenging stuff, particularly the point around 2060 when “all human tasks” will apparently be capable of being done by machines. But drawing an apparently precise timeline such as this obscures two massive sources of uncertainty. The first is the implication that people working on artificial intelligence have expertise in predicting the future of artificial intelligence. Their track record suggests that that is far from the case: like nuclear fusion, full blown AI has been twenty years in the future for decades (and the study underlying this short article strongly implies, though without ever acknowledging, that the results are as much driven by social context as by technical precision). The second is the implication that the nature of human tasks has been understood, and thus that we have some idea of what the automation of all human tasks might actually mean. There are some huge issues barely understood about that (though also something of a no true Scotsman argument – something is AI until it is achieved, at which point it is merely automation). Even if the details can be challenged, though, the trend looks clear: more activities will be more automated – and that has some critical implications, regardless of whether we choose to see it as beating humans.
Benedict Dellot and Fabian Wallace-Stephens – the RSA
This new report from the RSA takes a more balanced view than most on the impact of automation on work, and particularly on low-skill work. This is neither a story of a displaced workforce condemned to penury as the robots take over, nor one of a blithe assumption that everything will muddle through. Much of the underlying analysis is now fairly familiar – certainly to regular readers here – what is distinctive and valuable is the focus on the quality as well as the quantity of work and the ways in which automation can enhance human work rather than displace it
Impressively, the authors have put some of their approach into practice by partly automating the process of reading it. Traditional manual readers can work through the full eighty page report; automation maximalists need only skim the eight key takeaways; and those with intermediate ambitions can focus on extracts from the main report summarising the main arguments or focusing on the impact of automation on the quality of work.
How do changing patterns of employment affect not just the nature of people’s work in the short term, but their ability to progress and to have careers? This article attempts an answer to that question by looking at two tech giants of different generations, Kodak and Apple, and their very different employment models. It is unashamedly a powerful story rather than a deep analysis – but interesting read as an illustration of Simon Caulkin’s recent article, which covers closely related ground in a very different way.
Neil Irwin – New York Times
The fact that new technologies can destroy jobs (even if they can enable the creation of others) is almost universally discussed as a problem for the workers concerned. That doesn’t always mean that those affected are abandoned – there is recognition that governments have a role in retraining or providing other forms of support, up to and perhaps including a universal basic income – but it does mean that the component of the wider system which is expected to deal with the negative consequences is the affected worker. In the modern corporate era focused above all on shareholder value, companies necessarily do everything they can to minimise employment costs. But that is a political choice, not a force of nature (as a report from the White House recognised last year).
That framing of the issue is so deep rooted as to be almost invisible – this post brings it to light in order to challenge its assumptions: what can be done and should be done to sustain the demand for labour, and what implications does that have for the role and purpose of employing organisations?
The impact of technology on employment often focuses on the jobs at risk of being automated out of existence, not at the ones which might be created, either because of new technical possibilities, or as a consequence of increasing wealth and disposable income. This research looks at how patterns of employment have changed by tracking census data on occupations from 1871 to 2011 and concludes, not altogether surprisingly that their distribution has steadily changed, with patterns ranging from a steady decline in agricultural labourers and launderers, to telephonists rising to a peak in 1971 before declining by 2011 to the level of 1911 – and accountants, hairdressers and bar staff showing relentless growth, which is either the triumph of the service economy or an alarming step towards the reality of the B Ark.
Critically though, the conclusions are that although technological unemployment is very real, the stock of employment is not fixed or limited by technology, and that there is every reason to expect that new – and often unforeseen – jobs will continue to be created, as they always have been.
Link to the full report below – there was also a good summary of it published in the Guardian.
Ian Stewart, Debapratim De and Alex Cole – Deloitte
All the signs that you would expect to see in the labour market and wider economy if robots were displacing jobs are absent: productivity is not growing rapidly, labour turnover is not going up, and employment remains high.
That’s not to say, of course, that automation isn’t happening – and Surowiecki is careful not to say it – or that what has happened up to now is an infallible guide to what will happen in the future. But this article does contribute to the recognition that technological progress, the social and economic adoption of that progress, and the wider impact of that adoption are all very different things, potentially with very significant lags between them. That perspective is now coming through more strongly elsewhere as well – which should mean that the debate can be more balanced.
James Surowiecki – Wired
Technology is rarely just about technology, a fact often overlooked in slightly hysterical predictions about the impact of AI on jobs. This is a good summary of social, political and financial reasons why the path to universal automation might not be as straightforward as it is often portrayed. And that is to say nothing of the reasons to think that the technology itself may have intrinsic limitations as a substitute for humans.
Fabian Wallace-Stephens – the RSA
Organisations exist to get things done. They are necessary because they solve problems ranging from communication and co-ordination to moral hazard. But in principle, if we could find other ways of solving those problems, we wouldn’t need organisations any more – at least of the traditional kind. This article gives some examples of where that is starting to happen, by assembling not just project teams, but project organisations, created to meet a specific need and disbanded as soon as that need is met.
The examples given show that it can work, but they don’t and can’t show that it can scale, and there may be good reasons to think that it can’t. But that doesn’t stop the idea being a good challenge, particularly to those in organisations which don’t tend to think about organisational change in quite those terms.
Noam Scheiber – New York Times