soylent culture

(this was originally published as Implausipod Episode 37 on September 22nd, 2024)

https://www.implausipod.com/1935232/episodes/15791252-e0037-soylent-culture

What is Soylent Culture? Whether it is in the mass media, the new media, or the media consumed by the current crop of generative AI tools, it is culture that has been fed on itself. But of course, there’s more. Have a listen to find out how Soylent Culture is driving the potential for “Model Collapse” with our AI tools, and what that might mean.

In 1964, Canadian media theorist Marshall McLuhan published his work Understanding Media, The Extensions of Man. In it, he described how the content of any new medium is that of an older medium. This can help make it stronger and more intense. Quote, “The content of a movie is a novel, or a play, or an opera.

The effect of the movie form is not related to its programmed content. The content of writing or print is speech, but the reader is almost entirely unaware either of print or of speech.” End quote.

60 years later, in 2024, this is the promise of the generative AI tools that are spreading rapidly throughout society, and has been the end result of 30 years of new media, which has seen the digitalization of anything and everything that provides some form of content on the internet.

Our culture has been built on these successive waves of media, but what happens when there’s nothing left to feed the next wave? It begins to feed on itself, which is why we live now in an era of soylent culture.

Welcome to the Implausipod, an academic podcast about the intersection of art, technology, and popular culture. I’m your host, Dr. Implausible, and in this episode, we’re going to draw together some threads we’ve been collecting for over a year and weave them together into a tapestry that describes our current age, an era of soylent culture.

And way back in episode 8, when we introduced you to the idea of the audience commodity, where media companies real product isn’t the shiny stuff on screen, but rather the audiences that they can serve up to the advertisers, we noted how Reddit and Twitter were in a bit of a bind because other companies had come in and slurped up all the user generated content that was so fundamental to Web 2. 0 and fundamental to their business model as well, as they were still in that old model of courting the business of advertisers.

And all that UGC – the useless byproduct of having people chat online in a community that serve up to those advertisers – got tossed into the wood chipper, added a little bit of glue and paint, and then sold back to you as shiny new furniture, just like IKEA.

And this is what the AI companies are doing. We’ve been talking about this a little bit off and on, and since then, Reddit and Twitter have both gone all in on leveraging their own resources, and either creating their own AI models, like the Grok model, or at least licensing and selling it to other LLMs.

In episode 16, we looked a little bit more at that Web 2. 0 idea of spreadable media and how the atomization of culture actually took place. How the encouragement of that user generated content by the developers and platform owners is now the very material that’s feeding the AI models. And finally, our look at nostalgia over the past two episodes, starting with our look at the Dial-up Pastorale and that wistful approach to an earlier internet, one that never actually existed.

All of these point towards the existence of Soylent Culture. What I’m saying is is that it’s been a long time coming. The atomization of culture into its component parts, the reduction and eclipsed of soundbites to TikToks to Vines, the meme-ification of culture in general were all evidence of this happening.

This isn’t inherently a bad thing. We’re not ascribing some kind of value to this. We’re just describing how culture was reduced to its bare essentials as even smaller bits were carved off of the mass audience to draw the attention of even smaller and smaller niche audiences that could be catered to.

And a lot of this is because culture is inherently memetic. That’s memetic as in memes, not memetic as in mimesis, though the latter applies as well. But when we say that culture is memetic, I want to build on it more than just Dawkins’s original formulation of the idea of a meme to describe a unit of cultural transmission.

Because, honestly, the whole field of anthropology was sitting right over there when he came up with it. A memetic form of culture allows for the combination and recombination of various cultural components in the pursuit of novelty, and this can lead to innovation in the arts and the aesthetic dimension.

In the digital era, we’ve been presented with a new medium. Well, several perhaps, but the underlying logic of the digital media – the reduction of everything to bits, to ones and zeros that allow for the mass storage and fast transmission of everything anywhere, where the limiting factors are starting to boil down to fundamental laws of physics –

this commonality can be found across all the digital arts, whether it’s in images, audio, video, gaming. Anything that’s appearing on your computer or on your phone has this underlying logic to it. And when a new medium presents itself due to changing technology, the first forays into that new medium will often be adaptations or translations of work done in an earlier form.

As noted by Marshall McLuhan at the beginning of this episode, it can take a while for new media to come into its own. It’ll be grasped by the masses as popular entertainment and derided by the high arts, or at least those who are fans of it. Frederick Jameson, who we talked about a whole lot last episode on nostalgia noted, quote, “it was high culture in the fifties that was authorized as it still is to pass judgment on reality.

to say what real life is and what is mere appearance. And it is by leaving out, by ignoring, by passing over in silence and with the repugnance one may feel for the dreary stereotypes of television series that high art palpably issues its judgment.” End quote.

So, the new medium, or works that are done in the new medium, can often feel derivative as it copies stories of old, retelling them in a new way.

But over time, what we see happen again and again and again are that fresh stories start to be told by those familiar with the medium that have and can leverage the strengths and weaknesses of the medium, telling tales that reflect their own experiences, their own lives, and the lives of people living in the current age, not just reflections of earlier tales.

And eventually, the new medium finds acceptance, but it can take a little while.

So let me ask you, how long does it take for a new medium to be accepted as art? First they said radio wasn’t art, and then we got War of the Worlds. They said comic books weren’t art, and then we got Maus, and Watchmen, and Dark Knight Returns. They said rock and roll wasn’t art, and we got Dark Side of the Moon and Pet Sounds, Sgt.

Pepper’s and many, many others. They said films weren’t art, and we got Citizen Kane. They said video games weren’t art, and we got Final Fantasy VII and Myst and Breath of the Wild. They said TV wasn’t art, and we got Oz and Breaking Bad and Hannibal and The Wire. And now they’re telling us that AI generated art isn’t art, and I’m wondering how long it will take until they admit that they were wrong here, too.

Because even though it’s early days, I’ve seen and heard some AI generated art pieces that would absolutely count as art. There are pieces that produce an emotional effect, they evoke a response, whether it’s whimsy or wonder or sublime awe, and for all of these reasons, I think the AI generated art that I’ve seen or experienced counts.

And the point at which creators in a new medium produce something that counts as art often happens relatively early in the life cycle of that new media. In all of the examples I gave, things like War of the Worlds, Citizen Kane, Final Fantasy VII, these weren’t the first titles produced in that medium, but they did come about relatively early, once creators became accustomed to the cultural form.

As newer creators began working with the media, they can take it further, but there’s a risk. Creators that have grown up with the media may become too familiar with the source material, drawing on the representations from within itself. And we can all think of examples of this, where writers on police procedurals or action movies have grown up watching police procedurals and action movies and they simply endlessly repeat the tropes that are foundational to the genre.

The works become pastiches, parodies of themselves, often unintentionally, and they’re unable to escape from the weight of the tropes that they carry. This is especially evident in long running shows and franchises. Think of later seasons of The Simpsons, if you’ve actually watched recent seasons of The Simpsons, compared to the earlier ones.

Or recent seasons of Saturday Night Live, with the endlessly recycled bits, because we really needed another game show knock off, or a cringy community access parody. We can see it in later seasons of Doctor Who, and Star Trek, and Star Wars, and Pro Wrestling as well, and the granddaddy of them all, the soap opera.

This is what happens with normal culture when it is trained on itself. You get Soylent Culture.

Soylent Culture is this, the self referential culture that is fed on itself, an ouroboros of references that always point at something else. It is culture comprised of rapid fire clips coming at the audience faster than a Dennis Miller era Saturday Night Live weekend update. Or the speed of a Weird Al Yankovic polka medley.

It is 30 years of Simpsons Halloween episodes referring to the first 10 years of Simpsons Halloween episodes. It is the hyper referential titles like The Family Guy and Deadpool, whether in print or film, throwing references at the audience rapid fire with rhyme and reason but so little of it, that works like Ready Player One start to seem like the inevitable result of the form.

And I’m not suggesting that the above works aren’t creative. They’re high examples of this cultural form; of soylent culture. But the endless demand for fresh material in an era of consumption culture means that the hyper-referentiality will soon exhaust itself and turn inward. This is where the nostalgia that we’ve been discussing for the previous couple episodes comes into play.

It’s a resource for mining, providing variations of previous works to spark a glimmer in the audience’s eyes of, hey, I recognize that. But even though these works are creative, they’re limited, they’re bound to previous, more popular titles, referring to art that was more widely accessible, more widely known.

They’re derivative works and they can’t come up with anything new, perhaps.

And I say perhaps because there’s more out there than we can know. There’s more art that’s been created that we can possibly experience in a lifetime. There’s more stuff posted to YouTube in a minute than you’ll ever see in your 80 years on the planet.

And the rate at which that is happening is increasing. So, for anybody watching these hyper referential titles, if their first exposure to Faulkner is through Family Guy, or to Diogenes is through Deadpool, then so be it. Maybe their curiosity will inspire them to track that down, to check out the originals, to get a broader sense of the culture that they’re immersed in.

If they don’t get the joke and look around and wonder why the rest of the audience is laughing at this and say, you know, maybe it’s a me thing. Maybe I need to learn more. And that’s all right. It can lead to an act of discovery; of somebody looking at other titles and curating them, bringing them together and developing their own sense of style and working on that to create an aesthetic.

And that’s ultimately what it comes down to. Is art an act of learning and discovery and curation? Or is it an act of invention and generation and creation, or these all components of it? If an artist’s aesthetic is reliant on what they’ve experienced, well, then, as I’ve said, we’re finite, tiny creatures.

How many books or TV shows can you watch in a lifetime to incorporate into your experience? And if you repeatedly watch something, the same thing, are you limiting yourself from exposure to something new? And this is where the generative art tools come back into play. The AI tools that have been facilitated by the digitalization of everything during web 1. 0 and the subsequent slurping up of everything into feeding the models.

Because the AI tools expand the realm of what we have access to. They can draw from every movie ever made, or at least digitalized. Not just the two dozen titles that the video store clerked happened to watch on repeat while they were working on their script, before finally following through and getting it made.

In theory, the AI tools can aid the creativity of those engaging with it, and in practice we’re starting to see that as well. It comes back to that question of whether art is generative or whether it’s an act of discovery and curation. But there’s a catch. Like we said, Soylent cultures existed long before the AI art tools arrived on the scene.

The derivative stories of soap operas and police procedurals and comic books and pulp sci-fi. But it has become increasingly obvious that the AI tools facilitate Soylent culture, drive it forward, and feed off of it even more. The A. I. tools are voracious, continually wanting more, needing fresh new stuff in order to increase the fidelity of the model.

That hallowed heart that drives the beast that continually hungers. But you see, the model is weak. It is Vulnerable like the phylactery of a lich hidden away somewhere deep.

The one thing the model can’t take too much of is itself: model collapse is the very real risk of a GPT being trained on text generated by a large language model identified by Shumailov, et al, and “ubiquitous among all learned generative models” end quote. Model collapse is a risk that creators of AI tools face in further developing those tools.

Quoting again from Shumailov: “model collapse is a degenerative process affecting generations of learned generative models in which the data they generate end up polluting the training set. of the next generation. Being trained on polluted data, they then misperceive reality.” End quote. This model collapse can result in the models ‘forgetting’ or ‘hallucinating’.

Two terms drawn not just from psychology, but from our own long history of engaging with and thinking about our own minds and the minds of others. And we’re exacting them here to apply to our AI tools, which – I want to be clear – aren’t thinking, but are the results of generative processes of taking lots of things and putting them together in new ways, which is honestly what we do for art too.

But this ‘forgetting’ can be toxic to the models. It’s like a cybernetic prion disease, like the cattle that developed BSE by being fed feed that contained parts of other ground up cows that were sick with the disease. The burgeoning electronic minds of our AI tools cannot digest other generated content.

And in an era of Soylent Culture, where there’s a risk of model collapse, where these incredibly expensive AI tools that require mothballed nuclear reactors to be brought online to provide enough power to service them, that thirst for fresh water like a marathon runner in the desert, In this era, then the human generated content of the earlier pre AI web becomes a much more valuable resource, the digital equivalent of the low background steel that was sought after for the creation of precision instruments following the era of atmospheric nuclear testing, where all the above ground and newly mined ore was too irradiated for use in precision instruments.

And it should be noted that we’re no longer living in that era because we stopped doing atmospheric nuclear testing. And for some, the takeaway for that may be that to stop an era of Soylent culture, we may need to stop using these AI tools completely. But I think that would be the wrong takeaway because the Soylent culture existed long before the AI tools existed, long before new media, as shown by the soap operas and the like.

And it’s something that’s more tied to mass culture in general, though. New media and the AI tools can make Soylent Culture much, much worse, let me be clear. Despite this, despite the speed with which all this is happening, the research on model collapse is still in its early days. The long term ramifications of model collapse and its consequences will only be learned through time.

In the meantime, we can discuss some possible solutions to dealing with Soylent Culture. Both AI generated and otherwise. If Soylent Culture is art that’s fed on itself, then the most effective way to combat it would be to find new stuff. To find new things to tell stories about. To create new art about.

Historically, how has this happened with traditional art? Well, we’ve hinted at a few ways throughout this episode, even though, as we noted, in an era of mass culture, even traditional arts are not immune from becoming soylent culture as well. One of the ways we get those new artistic ideas is through mimesis, the observation of the world around us, and imitating that, putting it into artistic forms.

Another way we get new art is through soft innovation when technologies enhance or change the way that we can produce media and art, or where art inspires the development of new technology as they feed back and forth between each other, trading ideas. And as we’ve seen throughout this episode and throughout the podcast in general, new media and new modes of production can encourage new stories to be told as artists are dealing with their surroundings and whatever the current zeitgeist is and putting that into production with whatever media that they have available.

As our world and society and culture changes, we’re going to reflect upon our current condition and tell tales about that to share with those around us. And as we noted much. Earlier in this particular episode, that familiarity with a form, a technical form, allows those who are using it to innovate within that form, creating new, more complex, better produced and higher fidelity works in whatever medium they happen to be choosing to work in.

And ultimately that comes down to choice. By the artists and the audience and the associated industries that allow the audience to experience those works, whether they are audio, visual, tactile, experiential, like games, any version of art that we might come in contact with. The generation and invention in the process is important to be sure, but the curation and discovery is no less important within this process.

And this is where humans with an a sense for aesthetic and style will still be able to tell. How would an AI tool discover or create? How could it test something that’s in the loop? The generative AI tools can’t tell. They have no sense. They can provide output, but no aura, no discernment. Could an AI run a script that does A-B testing on an audience for each new generated piece of art to see how they react, and the most popular one gets put forward?

I guess so, it’s not outside the realm of possibility, but that isn’t really something that they’re able to do on their own, or at least I hope not.

Would programming in some variance and randomness in the AI tools allow for them to avoid the model collapse that comes with ingesting soylent culture in much the same way that we saw with the reveries for the hosts in the Westworld TV series?

Well, the research by Shumailov et al that we mentioned earlier suggests that that’s possibly not the case. I mean, it might help with the variation, perhaps, but that doesn’t help with the selection mechanisms, the discernment.

AI is a blind watch, trying to become a watchmaker, making new watches. The question might be, what would an AI even want with a watch anyways?

Thank you for joining us on the Implausipod. I’m your host Dr. Implausible. We’ll explore more on the current state of AI art tools and their role as assistive technologies in our next episode. called AI Refractions. But before we get there, we need to return to our last episode, episode 36, and offer a postscript on that one.

Even though it’s been only a week, as of the recording of this episode, September 22nd, 2024, we regret to inform you of the passing of Professor Frederick Jameson, who was the subject of episode 36. As we noted in that episode, he was a giant in the field of literary criticism and philosophy, and a long time professor at Duke University.

Our condolences go out to his family and friends. Rest in peace. If you’d like to contact the show, you can reach me at drimplausible at implausipod. com, and you can also find the show archives and transcripts of all our previous shows at implausipod. com as well. I’m responsible for all elements of the show, including research, writing, mixing, mastering, and music, and the show is licensed under a Creative Commons 4. 0 share alike license.

You may have noticed at the beginning of the show that we described the show as an academic podcast, and you should be able to find us on the Academic Podcast Network when that gets updated. You may have also noted that there was no advertising during the program, and there is no cost associated with the show, but it does grow from word of mouth of the community, so if you enjoy the show, please share it with a friend or two.

and pass it along. There’s also a buy me a coffee link on each show at implausipod. com which will go to any hosting costs associated with the show. Over on the blog, we’ve started up a monthly newsletter. There will likely be some overlap with future podcast episodes, and newsletter subscribers can get a hint of what’s to come ahead of time, so consider signing up and I’ll leave a link in the show notes.

Until then, take care and have fun.

Bibliography

McLuhan, M. (1964). Understanding Media: The Extensions of Man. The New American Library.

Shumailov, I., Shumaylov, Z., Zhao, Y., Gal, Y., Papernot, N., & Anderson, R. (2024). The Curse of Recursion: Training on Generated Data Makes Models Forget (No. arXiv:2305.17493). arXiv. https://doi.org/10.48550/arXiv.2305.17493

Shumailov, I., Shumaylov, Z., Zhao, Y., Papernot, N., Anderson, R., & Gal, Y. (2024). AI models collapse when trained on recursively generated data. Nature, 631(8022), 755–759. https://doi.org/10.1038/s41586-024-07566-y

Snoswell, A. J. (2024, August 19). What is ‘model collapse’? An expert explains the rumours about an impending AI doom. The Conversation. http://theconversation.com/what-is-model-collapse-an-expert-explains-the-rumours-about-an-impending-ai-doom-236415

Soylent Culture

In 1964, Marshall McLuhan described how the content of any new medium is that of an older medium. This can make it stronger and more intense:

The content of a movie is a novel or a play or an opera. The effect of the movie form is not related to its program content. The “content” of writing or print is speech, but the reader is almost entirely unaware either or print or of speech.

Marshall McLuhan, Understanding Media (1964).

In 2024, this is the promise of the generative AI tools, that we currently have access to, tools like ChatGPT, Dall-E, Claude, Midjourney, and a proliferation of others. But this is also the end result of 30 years of new media, of the digitalization of anything and everything that can be used as some form of content on the internet.

Our culture has been built on these successive waves of media, but what happens when their is nothing left to feed the next wave?

It feeds on itself, and we come to live in an era of Soylent Culture.

Of course, this has been a long time coming. The atomization of culture into it’s component parts; the reduction in clips to soundbites, to TikToks, to Vines; the memeification of culture in general were all evidence of this happening. This isn’t inherently a bad thing, it was just a reduction to the bare essentials as ever smaller bits of attention were carved off of the mass audience.

Culture is inherently memetic. This is more than just Dawkins’ formulation of the idea of the meme to describe a unit of cultural transmission while the whole field of anthropology was right over there. The recombination of various cultural components in the pursuit of novelty leads to innovation in the arts and the aesthetic dimension. And when a new medium presents itself, due to changing technology, the first forays into that new medium will often be adaptations or translations of work done in an earlier form, as noted by McLuhan (above).

It can take a while for that new media to come into its own. Often, it’ll be grasped by the masses as ‘popular’ entertainment, and derided by the ‘high’ arts. It can often feel derivative as it copies those stories, retelling them in a new way. But over time, fresh stories start to be told by those familiar with the medium, with its strengths and weaknesses, tales told that reflect the experiences and lives of the people living in the current age and not just reflections of earlier tales.

How long does it take for a new media to be accepted as art?

First they said radio wasn’t art, and then we got War of the Worlds
They said comic books weren’t art, then we got Maus
They said rock and roll wasn’t art, then we go Dark Side of the Moon (and Pet Sounds, and Sgt Peppers, and many others)
They said films weren’t art, then we got Citizen Kane
They said video games weren’t art, and we got Final Fantasy 7
They said TV wasn’t art, and we got Breaking Bad
And now they’re telling us that AI Generated Art isn’t art, and I’m wondering how long it will take until they admit they were wrong here too.

But this can often happen relatively ‘early’ in the life-cycle of a new media, once creators become accustomed to the cultural form. As newer creators began working with the media, they can take it further, but there is a risk. Creators that have grown up with the media may be too familiar with the source material, drawing on the representations from within itself.

F’rex: writers on police procedurals, having grown up watching police procedurals, simply endlessly repeat the tropes that are foundational to the genre. The works become pastiches, parodies of themselves, often unintentionally, unable to escape from the weight of the tropes they carry.

Soylent culture is this, the self-referential culture that has fed on itself, an Ourobouros of references that always point at something else. The rapid-fire quips coming at the audience faster than a Dennis Miller-era Saturday Night Live “Weekend Update” or the speed of a Weird Al Yankovic polka medley. Throw in a few decades worth of Simpson‘s Halloween episodes, and the hyper-referential and meta-commentative titles like The Family Guy and Deadpool (print or film) seem like the inevitable results of the form.

And that’s not to suggest that the above works aren’t creative; they’re high examples of the form. But the endless demand for fresh material in the era of consumption culture means that the hyper-referentiality will soon exhaust itself, and turn inward. This is where the nostalgia that we’ve been discussing come into play, a resource for mining, providing variations of previous works to spark a glimmer in the audience’s eyes of “Hey, I recognize that!”

But they’re limited, bound as they are to previous, more popular titles, art that was more widely accessible, more widely known. They are derivative works. They can’t come up with anything new.

Perhaps.

This is where we come back to the generative art tools, the LLMs and GenAIs we spoke of earlier. Because while soylent culture existed before the AI Art tools came onto the scene, it has become increasingly obvious that they facilitate it, drive it forward, and feed off it even more. The AI art tools are voracious, continually wanting more, needing fresh new stuff in order to increase the fidelity of the model, that hallowed heart driving the beast that continually hungers.

But the model is weak, it is vulnerable.

Model Collapse

And the one thing the model can’t take too much of is itself. Model collapse is the very real risk of a GPT being trained on LLM generated text. Identified by Shumailov et. al. (2024), and “ubiquit(ous) among all learned generative models”, model collapse is a risk that creators of AI tools face in further developing the tools. In an era of model collapse, the human-generated content of the earlier, pre-AI web becomes a much valuable resource, the digital equivalent of low-background steel sought after for the creation of precision instruments in an era of atmospheric nuclear testing, where the background levels of radiation made the newly mined ore unsuitable for use.

(The irony that we were living in an era when the iron was unusable should not go un-noted.)

“Model collapse is a degenerative process affecting generations of learned generative models, in which the data they generate end up polluting the training set of the next generation. Being trained on polluted data, they then mis-perceive reality.”

(Shumailov, et. al., 2024).

Model collapse can result in the models “forgetting” (Shumailov, et al, 2023). It is a cybernetic prion disease. Like the cattle that developed BSE by being fed feed that contained parts of other ground up cows sick with the disease, the burgeoning electronic “minds” of the AI tools cannot digest other generated content.

Soylent culture.

But despite the incredible velocity that all this is happening at, it is still early days. There is an incredible amount of research being done on the effects of model collapse, and the long term ramifications for it on the industry. There may yet be a way out from culture continually eating itself.

We’ll explore some of those possible solutions next.

Jameson on Nostalgia

Writing on a topic like nostalgia is a path many have gone before, so my own thoughts – summed up over the last handful of posts (and a little bit on the newsletter too) – are unlikely to be wholly new to to the world. That by no means the exercise is wasted, as those reflective moments are wh0ere we can put together what we know, and what we think we know, about a given topic. That reflection can also allow us to compare those thoughts with other works on the subject.

As I outlined in my post on Nescience, I’m aware of at least one major author who has written on Nostalgia: Fredric Jameson. There are a few others that we may get to in time (but I’m not the biggest Freud guy, tbh, so there might be some skips along the way too). Jameson’s essay “Nostalgia for the Present” was published in the South Atlantic Quarterly in 1989, and has been reprinted in various books and collections of his since, such as 1992’s Postmoderism, or, The Cultural Logic of Late Capitalism. Which, given our previous discussion on commodities and such, may come as a surprise to hear is on my TBR rather than “fully digested”. There’s a lot to chew on out there, and we come to these things as we are meant to, I guess.

Before we get to Jameson’s thoughts on nostalgia, a quick summary of what we’ve covered so far here:

Nostalgia is representational (in a memetic way)
Nostalgia is an assemblage
The perceived value of the nostalgia of a property can impact financing
This value is subjective, and also relative
Nostalgia is also subjective, and can be constraining
Nostalgia can be contrasted with Novelty
Real nostalgia can be the audience longing for something actually produced
Imagined nostalgia is something the audience thinks they’ve seen before
Nostalgia can be organic (from the audience) or manufactured (by the producers)
Nostalgia is substrate neutral – it can happen in nearly any field

With the above in mind, what does Jameson have to say, and how does his work compare with the above? Let’s check out…

1989

Whoops…

(Apparently 1989 was a pivotal year).

“Nostalgia for the Present” (1989)

Fredric Jameson is a literary critic and philosopher who is – as of the writing of this in 2024 – the Director of the Institute for Critical Theory at Duke University. He’s written in a lot of fields, most notably on post-modernism and capitalism, and “Nostalgia for the Present” fits in this vein, coming 30 years after the publication of his PhD. He’s been working on these ideas for a while at this point. For the piece, he looks at the role of nostalgia in three works: Philip K Dick’s novel Time out of Joint (1959), Jonathan Demme’s Something Wild (1986), and David Lynch’s Blue Velvet (1986), which is as unique a selection of content as one might to choose to analyze as any, I suppose.

(Though looking over what we cover here on the blog, I’m not going to criticize the selections. Glass Houses (not the album) and all that.)

Time Out Of Joint (hereafter, TOOJ) is a faux time travel story, where a man who is apparently trapped in the 1950s notices small differences are errors in reality, which leads him to suspect that something weird if going on, kinda like the “Deja Vu” moment in The Matrix. These themes are typical of Philip K Dick: representations of reality, false consciousness, things moving behind the scenes. Looking at it in 2024, we’ve seen it in so many of the adaptations of his work, Blade Runner, A Scanner Darkly, Total Recall, Minority Report, and more.

Here in TOOJ, the protagonist is quite astute: he is in a “potemkin village” of the 1950s, rebuilt in 1997 during an interstellar civil war (Jameson, p.521). Not quite our current reality (well the interstellar part, at least), and again like much older science fiction, now rooted firmly in our past, in a future that will not come to be, as we noted in a previous post. While at times TOOJ feels more like a rough draft of The Truman Show, with the apparatus moving around to ensure the world is static for this one particular man, and this feeds into our various narcissistic, main-character desires, the film clip that would best describe TOOJ would be the epilogue to Captain America: The First Avenger (2011), where he wakes in a room, and recognizes from the radio broadcast that things are not what they seem. If there were a way to cliff notes a 221 page novel, this would be it.

There’s more going on in the novel, of course. Jameson notes how TOOJ is set up to be a model of the 1950s, as something that the protagonist will accept, echoing the Machines’ creation of the late 1990s virtual world in order to pacify the humans kept in the endless rows of creches in The Matrix (1999). Elements of the work of PKD have been copied so many times (at least six, by last count) that it’s hard to recognize the original source. We find it here in TOOJ, but that’s what Jameson is arguing (what with the Matrix being released a decade later and all).

TOOJ: “(The novel) is a collective wish fulfillment and the expression of a deep unconscious yearning for a simpler and more human social system, a small-town Utopia very much in the North American frontier tradition” (Jameson, p.521). I guess here’s where we’ll put a pin in our discussion to talk about the Fallout TV series, and Westworld too, but for now we need to press on.

There are details of the other two titles Jameson refers to – Something Wild and Blue Velvet – and they are fantastic films as well, but here they are to bolster his case, provide further evidence and allow him to triangulate towards the elements of nostalgia he is looked for. As our remit, familiarity, and focus here in the Implausiverse is more on the sci-fi side of things, we’ll see what he says about that and then use that to figure out what nostalgia is all about.

Jameson on Science Fiction

Science Fiction is a “category” in Jameson’s words, with bunny ears included, though we might just wanna call it a genre that came about during that Eisenhowerian period, of the US conquering space and battling “communists” at the same time, and this ideology is inherent within the lit. The “category” might be bigger, going large to include some real lit like Moore’s Utopia, and others, or it might be more tightly bound to the pulps. I like the expansive view of sci-fi for our POV here, though it seems best to loop in Shelley’s Frankenstein by definition and intent, and pin down the start of sci-fi proper to ‘sometime around when Jules Verne wrote Journey to the Centre of the Earth‘ (1864 for those keeping track), which scoops up HG Wells’ stuff as well, and gives us a strong foundation.

The classic 1950s era of sci-fi is kinda the “Golden Age”: a particular vision of the future both technologically and aesthetically. Its goal is to help us process our history, to come to terms with it and understand how we fit into the current era. Jameson contrasts sci-fi with the historical novel, a cultural form (along with costume films and period dramas on TV) that reflected the ideology of the feudal classes, and had fallen off throughout the late 20th century as the (then new) middle class sought something different, something that amped up their own achievements. Enter sci-fi. The historical novel failed not simply due to the feudalist ideals, but because, according to Jameson: “in the postmodern age we no longer tell ourselves our history in that fashion, but also because we no longer experience it that way, and indeed, perhaps no longer experience it at all” (p.522).

(This may have been true at the time, though the recent rise in historicism and historicity in its forms in the 21st century may suggest Varoufakis is more correct about Technofeudalism than one might suppose. Or rather then, the other way around: did Shakespeare in Love preceed Technofeudalism? Or succeed because of it? Was it the harbinger or the aftershock?)

(We’ll put another pin down here for the fantasy vs. sci-fi debate too, while we’re at it.)

So for Jameson, science fiction is an aspirational vehicle for the masses who are rejecting the previous historical viewpoint. Compared to the historical novel: “Science Fiction equally corresponds to the waning of the blockage of that historicity, and particularly in our own time, in the postmodern era, to its crisis and paralysis, its enfeeblement and repression” (p.523). A lot of the reasons why this occurs have less to do with the content (though there are parts of that too, to be sure), or at least particular aesthetic choices that are made, and more to to with the socio-economic conditions of post-WWII USA (and to a lesser extent Canada and the UK).

And this is where nostalgia starts to come in. Because both historical novels and sci-fi have a tie to the imagination, an imagined past or an imagined future. They use representation in their relationship with the past or future (p.523), but they are really ‘a perception of the present as history’, a way, that we can look at our situation through a few steps removed. This is the conceit throughout the Star-Trek-War-Hammer(s), the alien “other” is but an aspect of our selves, our society, our culture, that we try to take a closer look at.

Nostalgia for the 1950s (in the 1980s)

Describing TOOJ, Jameson presents us with a list of things that “evoke” the 1950s: Eisenhower, Marilyn Monroe, PTAs, etc., and if it reads like a certain Billy Joel song, that’s not by accident (though “We Didn’t Start the Fire” also being released in 1989 is most certainly coincidental). Nostalgia can often look like a collection of stuff in some hoarders back room. The items are referrents to the era, not facts per se, but ideas about those facts. The question Jameson asks is “Did the ‘period’ see itself this way?” PKD was writing TOOJ in 1959, looking at the decade that just passed and choosing what the essential elements might look like from the perspective of 1997, the year of the fictional interstellar war in his novel, and for the most part getting it right.

There is a “realistic” feel to how PKD describes the `1950s, a feel that arises from the cultural referents that are used. Jameson notes: “If there is ‘Realism’ in the fifties, in other words, it is presumably to be found there, in mass cultural representation, the only kind of art willing (and able) to deal with the stifling Eisenhower realities of the happy family in the small town, of normalcy and non-deviant everyday life.” (p.518, emphasis mine). To the spectator looking back from the 1980s, the image of the 1950s comes from the pop-cultural artifacts that the people in the 1950s understood themselves by. We’re just looking at it from a distance, through a scanner, darkly, and darker over time.

What this accomplishes is “a process of reification” (p.523). The reality gets blurred by the nostalgic elements, and this ends up becoming the signifier that represents the whole. So our sense of our selves, and of any moment in history, may have little or nothing to do with reality, objective reality that is. Which is the biggest PKD-style head trip out there. Though it’s hard to put into words. Show, don’t tell, and in the works of PKD and all of the PKDickensian-inspired media out there, they keep trying to show, over and over again. It’s tricky though. It requires a lot of speculation.

And TOOJ is ultimately a piece of speculative fiction. “It is a speculation which presupposes the possibility that at an outer limit the sense people have of themselves and their own moment of history may ultimately have nothing whatsoever to do with its reality” (Jameson, p.520). How we think of ourselves, our histories, and our generations, are only tied to a fraction of the things that are out there, and much of it may be that “imagined nostalgia” we talked about a few posts ago.

Fitting the pieces together

Which brings us back to the goal we had near the top of this post: What did Fredric Jameson have to say about nostalgia, and how does it jive with our own concept of the nostalgia curve. We can elements of what Jameson was talking about in at least four of our categories:

Nostalgia is representational
Real nostalgia
Imagined nostalgia
Nostalgia happens in different media

Tackling these in turn, we can see how our idea of nostalgia being a representation of a thing, rather than being the thing itself is fundamental in Jameson’s work, and carried throughout it. The ideas of thing, not the things themselves. And for Jameson, those mediated examples coming from pop culture versions, and then informing the generational logic for successive viewers is important too; it connects with our idea of “imagined nostalgia”, the kind that the audience thinks they are remembering, rather than actually experienced.

Jameson doesn’t distinguish between different “kinds” of nostalgia, or at least at the source of where it is produced, but looks at what the the nostalgia is “for” (hence the title, natch). A 1980s audience longing for the imagined view of the `1950s; a interstellar warrior (in the text) longing for their imagined view of the same; or a writer from the decade of the 1950s constructing a longing for that decade while it is still going on. These are all “nostalgia” writ large, to Jameson, whereas we’ve increased the granularity a bit to fine tune our analysis of the Nostalgia Curve/

Jameson also looks at the construction of nostalgia in various media – novels and film in this case, though there could be others – tying in with our “substrate neutral” idea above. The Nostalgia Curve is a transmedia property, and not particular to any one kind or another.

The elements of nostalgia that focused on value are largely absent from his work. Not completely, but as he was looking at the reification of ideology that takes places via nostalgia, and not necessarily the production culture and political economy elements, this is understandable.

Next steps: Memory and Soylent Culture

There’s more to nostalgia than just the media aspect, though, and we’ll need to take a deeper look at the connection it has with memory. There are a few authors I have on the bookshelf that talk about it, and we’ll get into them soon.

The other place nostalgia is showing up in is as part of our Soylent Culture, where bits and pieces of past properties we like or love are dredged back up by the cultural sieves that are our Generative AI tools, and the Platforms that encourage their use as Spreadable Media. Media theorist Marshall McLuhan talked about how new media is built out of the pieces of the old, and nowhere is that more true than in our current online culture. We’ll look deeper into these pieces soon.

References:

Jameson, F., (1989). “Nostalgia for the Present”, The South Atlantic Quarterly 88:2, Spring 1989. Duke University Press,