Having watched the film, I thought I’d get Robert Linhart’s book off the shelf and finally read it. I think I bought it in Oxford in the early 80s. To remind you, it depicts Linhart’s experience as a Maoist cadre who has chosen to get a job in a Citroen factory in Paris in order to foment “resistance”. There’s an English translation, apparently, called The Assembly-Line, long out of print.
One reason for my hesitance in reading, perhaps, is that I have quite a low opinion of Maoists, particularly Western ones, and I’m sure that Linhart had at the time all kinds of dubious opinions about the Moscow Trials or the Cultural Revolution, but there’s really none of that in the book where he comes across as a fairly generic far-leftist. Instead there’s a fascinating description by someone with real literaray talent of the human reality of mass production as it was in the 1960s and probably still is somewhere other than Europe. It aslo gives an account of the ethno-sociology of the workforce which was “multicultural” long before the rest of society meaningfully was. Possibly the best book ever written by a Maoist then.
When Linhart enters the factory it is very different to how he imagined it would be, which was an assembly line shifting in short bursts as workers performed their tasks. Instead, the line moves continuously with workers running to catch up trying do their jobs quickly so they can get ahead of the game and sneak a quick cigarette or taking too long and getting tangled up with the next section. A manager puts him in the hands of a spot welder, who makes his movements with speed, precision and grace. But when that same Arab worker hands over to Linhart the novice makes a complete mess, molten solder all over the place, and he’s a danger to others and himself with his blowtorch. In a break they get chatting and he discovers that his “trainer” is graded as an unskilled worker (despite showing consummate skill) whereas he, Linhart, has been taken on at a skilled grade. But it soon becomes clear that the assignment of workers to grades has nothing to do with the skills those grades nominally represent: blacks are at the lowest unskilled level, Arabs at the higher unskilled ones, Spanish and Portuguese at the lowest tier of “skilled” and white French people like himself a notch above that, even if they can’t actually do anything. Who says there’s no such thing as “white privilege”?
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I am at the airport in Melbourne (again). I’m sitting in the window eating one of those excellent boxes of kale, broccoli, beans, seeds, peas and a boiled egg that I am grateful are now available at airports. Next to me a father and daughter are observing the world – look at how that plane looks like a giant shark! And oooh, here come the bags!
What looked like an automated process when a Virgin Airlines robot told me my bag on the conveyer belt was heading towards the same destination as me turns out, my eyes now tell me as this adorable pair observe the world out the window, is also a matter of human labour. A human is driving all the bags to the plane.
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My last post described my attempt to generate a report on housework using Deep Research, and the way it came to a crashing halt. Over the fold, I’ve given the summary from the last version before the crash. You can read the whole report here, bearing in mind that it’s only partly done.
As I said, I chose the questions to ask and the points on which to press further. DR extracted the data (I was planning to get detail on this process before the whole thing crashed), produced graphs to my specifications and generated the first draft of the text, with a style modelled on mine.
If I were doing this to produce a report for publication, I’d initially I was about halfway there, after only a few hours of work on my part. But as with LLMs in general, I suspect the final editing would take quite a bit longer.
Still, the alternative would have been either nothing (most likely) or a half-baked blog post using not-quite-right links to the results of Google searches. So, I’m going to keep on experimenting.
Early versions of LLMs were mostly substitutes for medium-level skill. It made it easy for someone barely literate to generate an adequate business email or (in the graphics version) for a complete klutz like me to produce an obviously-AI illustration for a post (Substack expects some kind of picture)
But with Deep Research, I think there’s an amplification of general research skills. It’s ideal for topics where I have some general idea of the underlying reasoning, but am not familiar with the literature and am unaware of some important arguments
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I’ve long been interested in the topic of housework, as you can see from this CT post, which produced a long and unusually productive discussion thread [fn1]. The issue came up again in relation to the prospects for humanoid robots. It’s also at the edge of bunch of debates going on (mostly on Substack) about living standards and birth rates.
I’m also interested (like nearly everyone, one way or another) in “Artificial Intelligence” (scare quotes intentional). My current position is, broadly, that it’s what Google should have become instead of being steadily enshittified in the pursuit of advertising dollars. But I’m alert to other possibilities, including that more investment will deliver something that genuinely justifies the name AI. And I think a lot of the concerns about power and water use, the spread of AI slop and so on are either overstated or (as with deepfakes) are mostly new iterations of concerns that always arise with new IT and communications technology, and can be addressed with existing conceptual and legal tools.
With this background, I thought it would be interesting to try out ChatGPTs Deep Research (DR) on the question of what has happened to housework and why. As I may have mentioned before, I’ve trained DR on a big volume of my own writing. That produces a passable imitation of my style, and means I don’t worry about the ethical issues of plagiarising the writing style of others (of course, standard norms of citation and attribution still apply).
I decided to focus on single-person households, to abstract away from the issues of child-raising (which I want to look at separately) and the allocation of work between partners (about which there is a vast literature to which I can’t add anything new).
Everything went really well to start with. I prompted DR for time use data, then pushed further on with more detailed questions like the impact of air fryers on male cooking habits (I was given one recently and was impressed enough that I promptly bought a second). I asked for a literature search and got references to Judy Wajcman and Michael Bittman[2], both of whom I knew and a couple of people I didn’t. DR missed Ruth Schwartz Cowan’s classic More Work for Mother.
On the other hand, I wasn’t aware of Wajcman’s recent Pressed for Time and hadn’t thought about the broader issue of life administration, which DR pointed out. I gave it a more economistic take, trying to divide labour-saving innovation (electronic bill paying) from the labour costs of more digital consumption (retrieving passwords for streaming services etc).
I got DR to produce a LaTeX file, and was nearly ready to go to digital press when I noticed that the references were incomplete. At this stage, the whole process spiralled into disaster. Every draft seemed to lose more material, and to be worse written. Finally, I demanded an explanation
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I spent a good chunk of the afternoon watching l’Etabli, the film of Robert Linhart’s book (which I own but have never read). It is an arresting depiction of the brutality of the assembly-line and the racalialised hierarchies at work in the factory. The theme of the film is of a Maoist cadre from an academic and privileged background (in philosophy!) who enters the factory to foment resistance and revolution and finds that it is a lot tougher than he had perhaps imagined. But an opportunity presents itself when the Citroen management decide to make the workers toil unpaid for an extra three-quarters of an hour each day to “repay” the gains they’d made in May and June 1968. He helps to lead a strike and watches as the his new comrades are picked off by management and their goons, as immigrant workers are threatened with deportation and they are all subjected to acts of petty humiliation. A year later, we see him lecturing on Hegel at the University of Vincennes (later, I believe, dismantled by the French authorities as a hotbed of leftism).
The film is available to watch for free here (under “Drama”)
It reminded me a little of the Fourth International (Mandel version)’s policy of sending its students and white-collar workers into the “industrial working class” a decade later. Just as the industrial working class was actually disappearing from Western Europe and North America, they decided it was (as previously announced by Marxist theory) central to the struggle to overthrow capitalism. Some of my friends did end up in a car factory in Oxford, from which they were very soon fired once their identities became known. Others gave up good jobs in health and education but failing to find factory jobs ended up working in public transport. One of them I remember absolutely loved being a train driver compared the anxiety and stress of their previous school-teaching life. As for me, I was torn between my misplaced allegiance to the organisation (which in the UK at the time was the International Marxist Group then the Socialist League) and my conviction that this was all a dreadful mistake. So I took the path of least resistance and decided to carry on being a student (a postgraduate one) until the madness blew over. And so I ended up as a political philosopher in a university rather than whatever else I might have become (a lawyer, I suspect).
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I heard a rumour that London IT professionals have selected the pub where they will meet when the internet goes down.
It is apocalyptic thinking, perhaps, but it also feels plausible. Though the internet feels permanent, stable and sufficiently distributed to seem impervious to target, this infrastructure that underpins our daily work and life is strikingly vulnerable. Undersea cables get damaged; phone and cable systems go down; and software is frequently corrupted or hacked.
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I’ve been seeing more and more alarmism about the idea that, on current demographic trends, the world’s population might shrink to a billion in a century or two. That distant prospect is producing lots of advocacy for policies to increase birth rates right now.
One of the big claims is that a smaller population will reduce the rate of scientific progress I’ve criticised this in the past, pointing out that billions of young people today, particularly girls, don’t get the education they need to have any serious chance of realising their potential. But it seems as if I need to repeat myself, so I will do so, trying a slightly different tack
It’s surprisingly difficult to get an estimate of the number of researchers in the world, but Google scholar gives us a rough idea. Google Scholar indexes research across all academic disciplines, including social sciences and humanities. No exact count is available, but I’ve seen an estimate that 1.5 million people have Google scholar profiles. I’d guess that this would account for at least half of all active researchers, for a total of 3 million.
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“I am especially to speak to you of the character and mission of the United States, with special reference to the question whether we are the better or the worse for being composed of different races of men.”
— Frederick Douglass, Composite Nation, 1869
Today is Thanksgiving Day in the USA. So, here’s a Thanksgiving cartoon from 1869, by the great American cartoonist Thomas Nast.
You may have seen it before. But it’s an interesting piece of work, and rewards close attention.
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I think a fair bit about how generative AI can help our everydays. (I also think a lot about its challenges, but this post is not about that.) Here is a good example for how it can be useful with a complex meal prep situation for which Thanksgiving is the ultimate case (which I’m celebrating in Zurich this year having taken a day off work since of course it’s not a holiday here, but my cooking requires more than a few hours).
Assuming limited stove top, oven, and counterspace (a very fair assumption in the Zurich housing market), it is important to optimize the order of preparing the various dishes that require a complex mix of preparations. One example is needing to roast some garlic for 30 minutes as just one ingredient in this amazing mashed potatoes and yams dish that I have been making annually for 25 years (I seem to have blogged about it already 20 years ago).
So how can Gen AI help? Give it your list of recipes and ask it to optimize the process for you. I used Google’s NotebookLM for this as cooking optimization is something I want to keep long-term and I like having a separate saved notebook for it (handled well by some AI tools, but not so much Gemini, which is where I have a subscription). (As much as I like NotebookLM – as far as I can tell it requires a Google account – I do wish they would introduce folders.. available as browser add-ons, I know.) This should all work with your preferred Gen AI tool as well, or if it doesn’t then you may want to rethink your Gen AI choices. ;-)
My prompt was simple: [click to continue…]
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The US is one big grift these days: the Trump Administration, traditional and social media, corporations, crypto, financial markets are all selling some kind of spurious promise. It’s hard to pick the most egregious example. But for me, it’s hard to go past Tesla. Having lost its dominant position in the electric car market, the company ought to be on the edge of delisting. Instead, its current market capitalisation is $US1.33 trillion ($A 2 trillion). Shareholders have just agreed on an incentive deal with Elon Musk, premised on the claim that he can take that number to $8.5 trillion.
Having failed with the Cybertruck and robotaxis, Tesla’s value depends almost entirely on the projected success of the Optimus humanoid robot. There’s a strong case that Optimus will be outperformed by rivals like Unitree But the bigger question is: why build a humanoid robot at all?
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I have a piece over at the London Review of Books Blog about the UK government’s appalling changes to the way refugees are treated in the country.
“After the home secretary, Shabana Mahmood, announced the government’s new policies for ‘Restoring Order and Control’ in the House of Commons yesterday, one MP after another stood up to commend the British people for their ‘proud tradition’ of giving sanctuary, for their openness and toleration, before moving onto questions of ‘stopping the boats’, ‘fairness for the British taxpayer’ and whether asylum seekers might be housed near their constituents. The European Convention on Human Rights was mentioned so often that one might have imagined it to be the international treaty at the centre of refugeehood. It isn’t: that’s the Refugee Convention of 1951, largely absent from the debate.”
Read the continuation over there.
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