Financial Times reporter Sarah O\u2019Connor confesses to having once been a techno-optimist, confident in technology\u2019s power to automate away dangerous, dirty and boring work. Her new book, We Are Not Machines, superbly explains how she came to think otherwise.<\/p>\n
O\u2019Connor adopts a \u201cshow, don\u2019t tell\u201d approach to debunking some of our society\u2019s most banal and unhelpful narratives about technology and work \u2014 among them the idea that AI will \u201cfree up\u201d cognitive load and enable people to take on more creative and satisfying tasks and enjoy more leisure. Through nine lively chapters organised into sections on the \u201cmind,\u201d \u201cbody\u201d and \u201csoul,\u201d she introduces us to many different kinds of people who work with, around and under highly automated and AI-infused systems, including coders, translators, drivers, warehouse workers, miners and screenwriters.<\/p>\n
What emerges is not a ledger of winners and losers but a set of skilfully drawn portraits of power, self-awareness, hard choices and collective contestation. None of O\u2019Connor\u2019s informants is beguiled by grand narratives of human liberation, and none seems to accept at face value the idea that AI is \u201cjust a tool.\u201d For O\u2019Connor and many of her interviewees, the question of whether any particular job is robotised always co-exists with the question of whether and how human beings are being made more robot-like when they are forced to work in highly automated systems.<\/p>\n
Where things stand within any particular occupation is, O\u2019Connor observes, often detectable from the words people choose they use to talk about their jobs:<\/p>\n
\u201cWe send him away, then we send him back,\u201d the miner had said about the autonomous truck. Compare that to what the Amazon workers said: \u201cThe robot is moving and you have to move with the robot.\u201d Or, indeed, compare it to what Rebecca, the translator, had said: \u201cYou still have to be quite fastidious in receiving all this machine translation output, and that\u2019s exhausting, it\u2019s stressful.\u201d All of which is to say, sure, technology might be \u201cjust a tool,\u201d but if you\u2019re not the one with the tool in your hand, you\u2019re not the master carpenter, you\u2019re the screwdriver, or, worse, you\u2019re what\u2019s getting screwed.<\/p>\n
One of the real strengths of We Are Not Machines is O\u2019Connor\u2019s deftness in showing how AI is, and isn\u2019t, the latest act in a centuries-long drama of worker alienation in response to industrial capitalism. The varieties of anxiety, danger, resentment, acceptance, exit and resistance she chronicles are never detached from the history of capitalism and its critics. In describing the risks of machine users becoming machine-like, for instance, she quotes Ruskin: \u201cIt is not, truly speaking, the labour that is divided; but the men \u2014 divided into mere segments of men \u2014 broken into small fragments and crumbs of life.\u201d<\/p>\n
The hypermodern Amazon warehouses that bring the shelf to the worker (rather than the other way around) \u2014 and rely on a remote global workforce of \u201chumans in the loop\u201d to oversee mistakes \u2014 can be seen, she says, as a new iteration of Henry Ford\u2019s moving assembly line. Appropriately enough, the American engineer F.W. Taylor plays a recurrent role as the architect of the most notorious system for using \u201ctime and task\u201d techniques to deskill and speed up workers.<\/p>\n
But O\u2019Connor hasn\u2019t written another weary \u201cit\u2019s capitalism, stupid\u201d narrative. This is largely because she has a finely tuned ear for workers\u2019 descriptions of the ways AI-infused systems shape their inner lives at work.<\/p>\n
She tells us, for instance, about the silent mantra that Affan, a human \u201cGO-AI Associate\u201d for Amazon in Costa Rica, recites while watching videos of people putting items onto canvas shelves in nine-hour shifts. Faced with a 99.9 per cent accuracy rate requirement and the need to watch approximately 1200 ten-second videos a shift, Affan\u2019s time before the screen is accompanied by the prayer, \u201cPlease God, save me from a defect, please God, save me from a defect.\u201d<\/p>\n
Poignantly evocative, too, are her presentations of translators\u2019 lives and perceptions before, during and after the imposition of AI-based software. The creativity and sense of meaningfulness of translating from scratch shines through one translator\u2019s explanation of the process:<\/p>\n
[Y]ou take a message, a part of the message\u2026 then you render it in the other language, mostly through the equivalence of expression, the equivalence of feeling. \u201cIf I was thinking this, how would I say it?\u201d That becomes automatic \u2014 it feels almost automatic. Sometimes you get stuck [but] if I am hitting the flow, then it feels fantastic.<\/p>\n
Having to edit a machine translation, however, is \u201ca bulkier process in your mind,\u201d says Majkic, \u201cit\u2019s less rewarding, it takes more cognitive effort, not less.\u201d In the words of another translator, Petr:<\/p>\n
When someone presents you with a solution, and you\u2019re looking at that, and you\u2019re supposed to make it sound natural. It\u2019s difficult to come up with your own solution\u2026 I compare this to counting from one to a hundred: one, two, three four \u2014 with someone whispering in your ear some random numbers. Imagine that. It\u2019s so frustrating. That, to me, is what machine translation post-editing feels like.<\/p>\n
O\u2019Connor doesn\u2019t present the degradation of translation work as something afflicting only the translators, either. End-users of the work \u2014 the readers and watchers of the films and TV series being translated \u2014 receive more literal translations that might be comprehensible but are also \u201cflat and boring and uninteresting.\u201d The loss here isn\u2019t merely of \u201cquality,\u201d it is also of people\u2019s capacity to recognise what \u201cquality\u201d is or be aware that any alternative might be possible in a market flooded with \u201cgood enough\u201d products.<\/p>\n
Noting that this, too, isn\u2019t a new dynamic, O\u2019Connor quotes George Orwell in The Road to Wigan Pier: \u201cMechanisation leads to the decay of taste, the decay of taste leads to the demand or machine-made articles and hence to more mechanisation, and so a vicious circle is established.\u201d<\/p>\n
O\u2019Connor\u2019s main example of a group of workers for whom the \u201cAI is just a tool\u201d maxim seems plausibly true is software engineers. Most of them view AI tools as a welcome addition to their workflow because they don\u2019t see them as affecting the part of their job they really value, which is problem solving rather than simply writing code. Nor were AI tools forced on this group: because they wield relatively great labour market power, they retain control over whether and how to use them.<\/p>\n
But they are very far from representative. For creatives, educators and carers, the application of productivity and efficiency values \u2014 even before they were expressed in AI form \u2014 seems like a category error in any attempt to grasp the purpose and value of their work. O\u2019Connor depicts the sense of violation felt by artists, for instance, who see the idea of AI as simply a \u201ctool\u201d as profoundly misconceived. For them, it is \u201cfar more like an end-results machine than a new kind of paintbrush.\u201d As the historian Lewis Mumford once explained, \u201cthe purpose of art has never been labour-saving but labour-loving, a deliberate elaboration of function, form, and symbolic ornament to enhance the interest of life itself.\u201d<\/p>\n
In care work, too, technology-reliant approaches provide new iterations of old ways of missing the point. Debates about AI-infused care robots are a distraction unless they recognise what is lost or degraded when we attempt to organise something inherently and profoundly relational (beautifully elaborated by sociologist Allison Pugh as \u201cconnective labour<\/a>\u201d) as if it were an industrial commodity to be produced via principles of scientific management.<\/p>\n The Buurtzorg<\/a> nurses O\u2019Connor interviewed (who have a high level of worker autonomy, are geographically embedded, and deliver client-centred, defragmented care) were aghast at the idea that performing \u201csimple tasks\u201d was a \u201cwaste\u201d of their training. \u201cYou are not only there for that simple task, you are there to see the people, to see the life, to see what you are dealing with,\u201d said one. \u201cYou can\u2019t take care of someone who doesn\u2019t trust you, because they won\u2019t tell you the whole story, because sometimes they think it\u2019s not important, but even the little signals can be something that\u2019s really wrong.\u201d<\/p>\n O\u2019Connor doesn\u2019t merely observe the multiple clashes between the AI-enabled Taylorism and the values that hold us together as human beings with bodies, minds and souls. She also delves into the structures of power that make contestation over those matters meaningful.<\/p>\n One of her key case studies describes underground miners in Sweden who don\u2019t evince categorical hostility to digital technology and automation, and show openness, creativity and collaboration in how such systems might be integrated into their work. She describes how the agreement they reached about self-driving underground trucks and loaders reflected genuine give-and-take: how worker concerns that digital surveillance systems would drift from safety mechanisms into forms of discipline and speeding-up were worked through to the parties\u2019 mutual satisfaction.<\/p>\n In that case, says O\u2019Connor, the understanding and compromise on display rested on \u201ca very human edifice: a system based on relationships of trust, underpinned by a careful balance of power. It struck me that it required a great deal of skill, effort and emotional intelligence to maintain it.\u201d It was a system underpinned by collective bargaining not only at enterprise-level but also nationally, sectorally and locally. Employers and unions (the latter with 70 per cent membership density) were able to reach sector-specific agreements lasting one to three years within a system that, by its nature, is more responsive than one-size-fits-all laws imposed sporadically in the face of powerful political resistance.<\/p>\n Integral to the Swedish miners\u2019 approach is a reliable and comprehensive welfare safety net that provides 80 per cent of pre-employment earnings to displaced workers. Through this lens, whether you see AI as a \u201ctool\u201d is not a matter of individual preference or psychological flexibility but intimately related to institutional arrangements that reflect collective workplace power.<\/p>\n The nature of industrial power is also critical in O\u2019Connor\u2019s account of the Writers Guild of America\u2019s agreement with film and TV producers that set the conditions for writers to control when AI is used. The new contract didn\u2019t ban the technology, but it did remove the economic incentive for companies to use it to displace writers by specifying that AI content could not be classified as \u201csource material\u201d merely to be \u201crevised\u201d for lower rates.<\/p>\n The agreement wasn\u2019t merely the product of enlightened and flexible thinking on both sides. It emerged from an industrial relations framework that supported sector-based contracts and permitted industrial action, in this case a 148-day strike in which writers were supported by actors and support from Teamsters and United Auto Workers. As well as generating countervailing power, the process ensured the issue wasn\u2019t metabolised by workers as a private source of shame, lack of training or bad choices. By making the issue public and visible, says O\u2019Connor, workers felt \u201cas if the wider public was also on their side.\u201d<\/p>\n We Are Not Machines concludes with persuasive observations about the importance of attending carefully to how we talk, and therefore think, about work and technology. It is impossible to disagree with O\u2019Connor\u2019s observation that \u201cwave,\u201d \u201ctsunami\u201d and other metaphors \u201cencourage us to see this process as analogous to a powerful force of nature \u2014 something that cannot be controlled, but can only be prepared for, and then mopped up after.\u201d As she says, \u201cnew technology doesn\u2019t just unfold. It never has. It is created by people and implemented by people.\u201d<\/p>\n Nor, she argues, should we accept the thin, desiccated view of humanity that makes up Silicon Valley\u2019s view of progress: the idea that we are merely slower, stupider, weaker and more biased versions of the machines. Anyone who doubts her point \u2014 and in fact everyone that doesn\u2019t \u2014 should urgently read the Papal encyclical Magnifica Humanitas<\/a>.<\/p>\n O\u2019Connor writes brilliantly, too, about the importance of not feeling boxed in when we ask difficult and complicated questions about where AI belongs and how it should operate:<\/p>\n To say you don\u2019t want AI to clone musicians does not also mean you don\u2019t want protein-folding, antibiotics, low child mortality rates or indoor plumbing. That is a ludicrous mental box to put oneself into. And people don\u2019t do it with any other kind of produce. If you think heroin is bad, you don\u2019t worry that people will think you are also against paracetamol.<\/p>\n O\u2019Connor guides us, instead, to some better starting questions. She cites Neil Postman who suggested in his 1992 book Technopoly that we ask: \u201cWhat is the problem to which this technology is the solution? And whose problem is it?\u201d To Postman\u2019s questions, O\u2019Connor adds another, \u201cAre there any other ways to solve the problem?\u201d To these, I would perhaps suggest one more that emerges from her account: what structures are we building to enable answers to these questions to be meaningfully debated rather than simply imposed?<\/p>\n O\u2019Connor is to be applauded for insisting we centre human agency when we talk about how AI is designed and introduced into workplaces, that we always ask who decides. The next step in the analysis \u2014 and one beyond the scope of her book \u2014 is to ask why we so often accept the formations of industrial power and corporate power inherited from the last century as \u201cgivens,\u201d as if they are features of the natural landscape (\u201cNorway has mountains,\u201d \u201cAustralia is flat\u201d) rather than as structures we have built and can choose to maintain or change.<\/p>\n If we know Taylorism is deeply corrosive to the forms of trust and relationality that are critical to care, for example, why do we increasingly choose to provide care via private equity<\/a> companies, the institutional vehicles perhaps least capable of reversing disastrous low-trust, high-fragmentation \u201ctime and task\u201d-based approaches? Why do we persist with collective bargaining structures that (with narrow and highly conditional exceptions<\/a>) confine collective worker voices to the enterprise level and narrow range of \u201cpermitted matters<\/a>\u201d? These institutional structures were built in the time before AI, and whether and how we continue to use them is up to us. \u2022<\/p>\n","protected":false},"excerpt":{"rendered":"Financial Times reporter Sarah O\u2019Connor confesses to having once been a techno-optimist, confident in technology\u2019s power to automate…\n","protected":false},"author":2,"featured_media":793104,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[256,254,255,64,63,457,105,6624],"class_list":["post-793103","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-au","tag-australia","tag-books","tag-technology","tag-work"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/793103","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=793103"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/793103\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/793104"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=793103"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=793103"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=793103"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}