The rise of the robots is a recurrent theme of popular culture. Robots are often seen as a threat, heralding the prospect of human beings being replaced by their creations, perhaps to the extent of being deemed useless by them and attacked. Underlying this fear is the reality of automation: technology being more adept at particular tasks and so replacing human beings for this purpose. But automation isn’t new. All manner of what we now consider mundane automated tasks were once undertaken by hand, representing whole categories of employment which have now wholly or largely vanished. For instance our phone system no longer relies on switchboard operators and withdrawal of money no longer necessitates interaction with a bank clerk. But technological change has often produced new jobs to replace those that have been lost. Human beings are adaptable. As a 1965 NASA report put it, “Man is the lowest-cost, 150-pound, nonlinear, all-purpose computer system which can be mass-produced by unskilled labour”. More often than not, technology has been used alongside human beings to improve their productivity, sometimes as a skilled tool and sometimes as a tool for deskilling, taking a skilled task and breaking it into component elements. In fact, some might argue that the history of scientific management, analysing and dictating workflows to improve economic efficiency, somewhat resembles an attempt to turn human beings into machines: replacing their skilled and situational responses with a pattern imposed by outside experts.

But many are arguing that we are on the cusp of a turning point in automation. This is not a matter of hyper-intelligent robots replicating human capacities but rather of quite specific technological advances facilitating entirely new kinds of automation: what Jerry Kaplan describes as synthetic intellects and forged labourers. The first relies on advances in machine learning and cloud computing to process unprecedented quantities of data at speed, facilitating the rapid development of accumulated expertise in a particular sphere without strictly speaking ‘understanding’ it: the machine can learn from a much greater amount of data than was previously the case and the computational challenge involved in doing so can be distributed through the cloud. The second relies on developments in sensor technology to facilitate much more sophisticated engagements with the environment than has ever previously been possible, moving beyond highly specified tasks under strictly defined circumstances, allowing for entirely new work place designs built around the needs of the robot rather than the humans working alongside it. Rather than organising warehouses in a manner comprehensible to human packers, Amazon warehouses can now order their stock in a manner that seems chaotic to workers because items are located on the basis of imperceptible connections between them (e.g. sales data for this region shows that A and B are frequently shipped together) but allow the robot packers to work ever more efficiently:

One of the most radical developments in the near future is likely to be self-driving cars, such as those currently under development at Google. As Kaplan notes, vehicle accidents cause 4 million injuries and cost over $870 billion annually in the United States alone. Seen in this light, the total switch to self-driving cars looks like common sense. But it will also destroy whole categories of existing jobs upon which millions of people depend, including those such as taxi driver which have traditionally been a reliable open route into the work force for new immigrants in many countries. However this has still up till recently be seen as a matter of automating routine jobs. What has seemingly provoked much of the controversy in recent years is the newfound recognition that what are seen to be skilled jobs will themselves be under threat. The most interesting example of this is Narrative Science’s innovative tools to automatically generate stories from structured datasets. Starting with formulaic business stories, they have since moved into sports stories and make a disturbingly convincing case that with enough sophistication about underlying narrative structures, this process can work for any appropriately structured dataset.

This might not lead to all journalists losing their jobs but it certainly does suggest the possibility that much of the routine work of journalism might be automated. On the one hand, this could be seen as unproblematic given the financial challenges newspapers and magazines face at present: if it can be done cheaper, couldn’t this help secure journalism’s future? On the other hand, it’s difficult to see how the journalistic environment won’t suffer if routine entry level jobs are eliminated. Where will the stars of the future, those with sufficient individual expertise to resist automation, get their start? How will they become known? These are questions which have been raised across range of fields even prior to automation, as competitive pressures advantage those with sufficient financial resources and willingness to work for free. But the prospect of automation is likely to intensify this, ratcheting up the already endemic sense of uncertainty under which much of the workforce already labours.

How are people responding to the uncertainty facing occupational futures? Though the basis for his claims is somewhat unclear, I find Zygmunt Bauman’s analysis of this intuitively plausible. He suggests that the spectre of exclusion, the possibility that we won’t make the cut and we will be cast out without hope or prospects, animates a profound need for recognition. We ‘recast ourselves as commodities’ in order to cope under these circumstances, desperately seeking visibility in order to better sell ourselves against a backdrop in which, as the economist Tyler Cowen puts it, average is over. Economic polarisation is becoming the defining feature of the contemporary economy. As Cowen puts it, writing about the United States, “Demand is rising for low-pay, low-skill jobs, and it is rising for high-pay, high-skill jobs, including tech and managerial jobs, but pay is not rising for the jobs in between” (pg 40).

What Bauman is offering constitutes a speculative social psychology of how people respond to this condition of profound polarisation. If we’re aware that opportunities are contracting and that our future security is uncertain then these fears find expression in a competitive scramble to ensure we are recognised and valued: as commodities, if not necessarily as persons. He suggests that much social media behaviour can be seen as an expression of this impulse (though many, including myself, would object to generalisations about how people in general behave across social media in general). But I nonetheless think it identifies something interesting about the fame-seeking cultures that can be found across many platforms, even if there’s a tendency to “publicize successful outliers to propagate the illusion” in a way that serves the self-interest of platforms. The growing tendency to be fascinated with wealthy Vloggers, in virtue of the fact they are wealthy through vlogging, embodies something of this. Does the fact some people have seemingly secured their own future through social media visibility help propagate the sense that this is a viable strategy for many others? By definition there can only be a handful of celebrities on any platform. What we do know is how many young people see their future as determined by forces outside of their control, insusceptible to change through the avenues of work and education that older generations claim is a pathway to success.

Could fame culture thrive alongside this fatalism? People pray that they will ‘be discovered’ while also despairing about a future that seems beyond their control? What Furlong and Cartmel call the ‘epistemological fallacy of late modernity’ is a recipe for anxiety: the precise way in which opportunities constrain individuals has become more obscure than ever in a culture of competitive individualism which increasingly lacks the cultural resources to make sense of classed experience, while individuals are made to feel responsible for their biographical outcomes as pure expressions of their own talent and exertion.

Talent becomes fetishised under these circumstances. We can see this when Boris Johnson mocks the 16% ‘of our species’ with an IQ below 85 and praises the 2% with an IQ over 130. We can see it in the way that Donald Trump repeatedly proclaims that “I’m, like, a really smart person”, while condemning his rivals as not smart, without explaining what this really means or how it qualifies him for office. It’s why the popularisation of developmental neuroscience is so sinister: it heralds a social imaginary in which ‘talent’ can be understood as hardwired, while still acknowledging that circumstances plays a role in how these characteristics are inscribed in the human i.e. it justifies present arrangements while licensing punitive interventions against parents who fail to raise their children in a way conducive to the genesis of talent. Looking to the more ridiculous forms this fetishisation of talent takes can help us critique the more insidious and sophisticated variants that are increasingly dominant. This case can be made in particular about the most popular forms of self-help in recent years:

And this is the most remarkable feat of The Secret: its ability to defend inequality. While the 99 per cent has become a worldwide slogan questioning the concentration of wealth, the author of The Secret offers an alternative view of the situation. ‘Why do you think that 1 percent of the population earns around 97 percent of all the money that’s being earned?’, Bob Proctors is asked rhetorically in the book, answering, ‘People who have drawn wealth into their lived used The Secret, whether consciously or unconsciously. They think thoughts of abundance and wealth, and they do not allow any contradictory thoughts to take root in their mind.

The Wellness Syndrome, Carl Cederstrom & Andre Spicer, pg 80

What makes The Secret so interesting is how nakedly metaphysical it is. The affluent do it ‘unconsciously’ and that is why they are affluent. Those who are not nonetheless have the choice to do it. If they do it correctly then they too will become affluent. If they do not then they deserve their fate. This bizarre concept of “The Secret” fascinates me because it’s easy to see how it holds the whole picture together: this latent faculty, to which we all have access, allows us to succeed. Some people are disposed to access it already (inherited privilege) but this places no restriction on others. We can all access this latent ability to be a success if only we choose to do so and then use it in the proper way. Or to put it more mundanely: “there are plenty of good jobs out there for those who want them, it’s just that people don’t try”. The idea that differential outcomes can be explained away in terms of the moral failings of individuals means we take the existing state of society and the economy for granted: there aren’t questions to be asked about social structures, just more failings to be condemned in individuals. This is something

These are trends we can already see in contemporary society. My depressing question: how might they intensify under circumstances of widespread structural redundancy? What if the low-wage, low-skill jobs into economic polarisation is forcing much of the workforce rapidly begin to vanish? What will happen if 47% of jobs are eventually automated? It’s possible many new categories of job might open up but, as suggested earlier, there are good reasons to be sceptical about the scale and speed of this replacement. Will those who can’t find work be seen as unfortunate victims of unavoidable change or as moral failures placing a burden on the ‘wealth creators’? Will they mobilise themselves to collectively struggle for the transformation of a social order incapable of providing them access to the good life or will they be mobilised by others through potentially surreptitious means to serve the ends of those who are already wealthy and powerful? Popular culture provides us with many dystopian representations of what this might look like. The graphic novel Lazarus paints a bleak picture of a world in which nation states have been superseded by corporations and a small number of families dominate the planet. There are those who serve the families and those who are surplus to their needs, with the former group being composed of those who have been ‘elevated’ from the latter category. The possibility of freedom from insecurity and struggle represents a powerful tool to keep the population in line, coupled with private militaries to enforce this order through violence:

There are many other dystopian representations of a possible future in which there is little work or security for the majority of the population. However there are also popular representations of worlds in which scarcity has been conquered and everyone’s needs are met: ones in which some people still strive for work and adventure because of the intrinsic rewards that these provide. These are only representations but they are the resources we inevitably draw upon, deliberately or otherwise, when imagining the possibilities ahead of us for how these trends will unfold. Both of these categories however tie utopian or dystopian outcomes to the technology itself: seeing it as either liberating us or rendering us redundant. How does this suppress the role of politics – i.e. the tension and conflict between groups with different interests – in determining the outcome of these processes? Does it also preclude the possibility that our future might see a turn against technology, as something deemed to be responsible for systematic disenfranchisement? Would a neo-luddite movement be possible? Or are people too wedded to their devices? Would powerful interests allow such a movement, given the centrality of technology firms to the contemporary economy and the new possibilities for surveillance and control which the internet opens up? These are all open questions but they’re ones which sociology can help us think through in a systematic way, even if not necessarily answer.