Episode catch-up

Looks like the last episode we published here was at the start of 2024, with Episode 25 – Echanger. We’ll take the time to link one episode a day, getting caught up, starting from then.


The indie version is also getting up to speed. Not quite to the point where I’m publishing simultaneously to both, but the archives are coming along nicely. We have full episodes of the newsletter available, and we’re working on a couple different feeds too. I’m excited to get those going. 🙂

The big job, of course, will be moving all the previous blog posts over. Still looking at a way to automate that effectively, as it’s way easier than doing that by hand.

I’m also going to try and post some of the content that feeds the sections of the newsletter here first, things like the Current Reading and Multi-Melting sections, as well as podcast episodes and other feed info. We’ll still have something unique for each issue, so feel free to subscribe here.

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.

The Nostalgia Curve

Watching Deadpool and Wolverine, and engaging with the discourse surrounding it after, (I notoriously skip trailers, spoilers, and all but the most superficial reviews and prefer walking into movies relatively open-minded), one of the recurring themes in those discussions is how much the movie trades on nostalgia.

And with the recent release of Deadpool & Wolverine, there’s a renewed look at how nostalgia is driving (or if not behind the wheel, definitely tucked in with the seatbelts on. To a degree, this is understandable, as Hollywood is fairly risk-averse (seriously, this is the reason why you’ll see 100 sequels or adaptations in a given year, and only rarely does an original property break through). Of course there is more than just track record that nostalgia trades in on. Witness how it was deployed in the recent Twin Peaks: The Return.

I think they’re right, in so far as nostalgia can act as a balm, so that often people want more of that thing that they liked, but this isn’t necessarily a point of critique. There’s nothing wrong with liking what you like, and asking for (and maybe even getting) more of that, when it is available.

Three Fandoms

I’m thinking the best way to illustrate this would be by looking at three (enduring) fandoms here: Star Trek, Pro-wrestling, and comic books, and how they relate to and engage with new material produced for them.

These fandoms aren’t exactly equivalent, but they’re more alike beneath the surface than is usually acknowledged. All three cater to niche fandoms, and have persisted long enough that most of the population had had the opportunity to engage with them at some point in their lives. The slipping in and out of the zeitgeist that comes with successive waves of popularity is a critical part of that, as nostalgic parents can introduce their children to the media (and by extent the fandoms) that they enjoyed when they were younger.

Both comic books and pro-wrestling live in this weird kinda Eternal Now, that can acknowledge (and play off) their history (often as a means of generating credibility or cache), but continually, inexorably, have to put out new product. Sometimes they’ll re-introduce old characters in a new way to play off that, either through legacy characters or children (or relatives) of past performers but the trends are largely the same.

Star Trek is different (for the most part) as it has to continually create new stuff that is kinda like the old stuff, but still new and distinct enough that the fans will enjoy it. Witness the titles it has put out during the streaming era, with the dichotomy between Discovery, Picard, The Lower Decks, Prodigy, and Strange New Worlds, all coming out during roughly the same time period, and all engendering different reactions as they touch down on different points along that “nostalgia curve”.

Obviously, other properties play with the nostalgia curve at times too. Especially long running ones: Star Wars and Dr. Who come to mind; some gaming titles like Dungeons and Dragons, Magic:the Gathering, Pokemon, and Warhammer 40000 are getting old enough to test the waters as well.

So perhaps we should get to the point:

What is the Nostalgia Curve?

Maybe it’s best to think of the amount of nostalgia a given property evokes as existing along a gradient (maybe it can be a continuum, but we use that a lot. This time, we’re grading on the curve.) When something appears in a long-running piece of media, one with an inherent fandom, it can be a challenge to separate something from appearing for nostalgia purposes (i.e. marketing or whatever) and something existing just because it’s part of the setting)

Where you go “Hey look, it’s a wookie! they last showed up in Season 1 Episdoe 8 of the Acolyte! It’s been 20 years!” (says the viewer from the grimdark future of 2044).

(As unlikely as that scenario may be: Wookie’s Will Never Die; they’re the number one furry beast in my heart (behind Cookie Monster, and maybe Snuffleupagus. Wookies are top 5, is what I’m getting at.)

But back to the point I think I’m making is that the commodification of nostalgia, where whether or not a given movie or project even gets made depends on how much the perceived nostalgia factor is worth, is really the issue.

If the perceived value is enough, if you’re far enough along the nostalgia curve, then the movie can get made. And Hollywood being a place where money talks, it may be worth trying to create nostalgia for something that never existed in the first place. If you can create (or incept?) a “fake-thing-which-evokes-real-nostalgia” (actually name pending some focus groups), then you can commodify that in the same way that Deadpool did with Wolverine, and the “comic book accurate costume” that still isn’t 100%.

Nostalgic Memes

Nostalgia is representational (in a memetic way). Like earlier in the flick where Deadpool explicitly calls out the montage during a fourth wall break, and each scene in the montage is iconic within the comics, and instantly recognizable to a long-time fan, even though they never have occurred on screen at any point prior.

Every point of nostalgia is an assemblage (or container, or docker) for all the associations that accompany it. And these are all “shorthand” for everything else that is associated with those books. The time they were published, the creators (writers, artists, and editors), the events that they occurred during (“Age of Apocalypse” “Fall of the Mutants”, etc.).

Thus each and every nostalgic element packs in more and more, until a meta-textual movie like Deadpool & Wolverine can’t help but burst at the seams.

But in this case, it’s in a way that feels deserved. A recent IGN review of D&W lumped it in with the adaptation of Ready Player One, a film similarly stuffed to the brim with “Hey, I recognize that!” moments, and criticized it as being one of Steven Spielberg’s weakest films. Now, Senor Spielbergo may have forgotten more about making fantastic movies than most will ever know, so were the failures of RP1 Spielberg’s fault, or was he simply faithful to the source material?

(I’m asking as I found RP1 (The Book) execrable, and punted it at around the 20 page mark. I declined to watch the RP1 (The Movie.)

What we’re getting at here is that nostalgia is a hot commodity. It isn’t going away any time soon, and even though we all yearn for something fresh and new, and endlessly scrolling on our apps of choice to find it, we end up finding community and joy in our shared nostalgia for things we’re pretty sure we never saw, at least not the way we imagined them to be.

Multi-melting

I mentioned this a few months ago in Issue 1 of the Newsletter:

In the Warhammer 40000 game, there is a weapon called the “multi-melta” a ludicrous gun made better by strapping more of them together.  It’s awesome.  I always think of it when I hear the term multimedia, so here we go.
Dr Implausivble, Echoes of Implausibility – April 2024

So we’ll keep that up on the mainline blog and on other platforms as well.

The 7G Network

Online spaces have often been labeled as ‘toxic’, and new entrants to an online community may unwittingly run into this before really engaging with the community. We’ve talked about this on the podcast a couple times, at least in passing, over the last two years (E0010 Eternal September, E0014 Dumpshock, and E0032 Baked In would all qualify, for a start), but this idea of the 7G network is something I started working on for a conference paper back in 2021.

At the time, I was frustrated with the behaviours I was witnessing in the D&D community within TikTok, and recognized some of the behaviours as being strikingly similar to ones I had noticed around gaming web-forums over two decades earlier. So I began to catalogue those practices, and how the members of online communities would deploy them, sometimes intentionally, sometimes unknowingly, and how these practices, these doxa, made the online space a worse place to be in, driving people away, often never to return.

So as part of an effort to communicate some better practices for online communities, I’m publishing these here (while I continue to work on the full paper) in hopes that people can recognize these toxic elements and take steps to stop or remove them when they occur.

The ‘G’ in 7G Network is mostly a mnemonic, as it helps to keep the characteristics in mind, and it is by no means an exhaustive list. The seven are Gatekeeping, Gaslighting, Gravedancing, Grandstanding, Griefing, Grifting and Grooming. The toxicity of most of these should be self-evident, but in case there’s some ambiguity I’ll go into them in a bit more detail below. The ‘Network’ part of the term means you’ll often find the toxic characteristics working in concert; where there’s one, there are likely to be more. This can also help when trying to identify some of the more subtle characteristics like Grifting and Grooming. Not sure if something qualifies as grifting? Were there other toxic characteristics that you noticed? Perhaps being a little more reticent in your interactions is warranted…

But without (much) further ado, let’s see what we’re talking about.

Gatekeeping is that class of activities that focus on exclusion. If the subcultural wars are a battle for territory waged using social and gamer capital, the gate is at the boundary of that territory.  It defines the limits of the group, the marker for inclusion or exclusion. And it is continually contested.

Gaslighting is the denial of objective reality for your audience. Now, there can be some quibbles about “objective reality”, but we’re not getting into the edge cases here. We’re dealing with “sun rises in the West” levels of denialism here. While gaslighting has gotten more attention in the “post-truth” era of the current political landscape, it still manifests in some ways in geek subcultures too. There’s different kinds of gaslighting too: we’ll group them as overt and covert for ease of use.

Gravedancing is a form of communal organizing and editing of collective memory. Once a person has been chased out of the community, there will often be a period of celebration, where the community justifies their actions, in which community members congratulate themselves on how they came together and worked towards a common goal.  Of course, that goal is ostracism and exclusion, but they were able to put aside whatever other differences they may have and achieve something, so it can often be somewhat celebratory. The community will engage in a reification of the past event, restating the reasons why the offender had to be chased out, and reframing the event in the groups’ collective memory.

Grandstanding is the typical online posturing and performative “tough talk” that is somewhat endemic in online spaces, where internet users drastically overstate their prowess, ability, and credentials from the safety of the couch or behind their keyboard, free from immediate reprisal and unlikely to be fact-checked or called on it.

Griefing is online harassment, trolling, and bullying, and we are grouping these here under the singular “griefing” which is a form of harassment common in online video games (Chesney, 2009).

Grifting. The prevalence of #venmo, #cashapp and other payment details in bios facilitates this. This is a challenge, of course, as not every cry for aid on GoFundMe is a grift, especially in the era of the gig economy typical of late-stage capitalism in the 21st century. Rather, the ease of payment options and transactions has made the opportunity for grifting that much easier. The barrier to entry is that much lower.

Grooming is the set of behaviours “in which an adult builds an emotional relationship with a minor in order to gain the minor’s trust for the purposes of future or ongoing sexual contact, sexual abuse, trafficking, or other exploitation.” (Bytedance, Inc., 2022). As these appear


To sum up (well, the sum should be “7”, but in words…), the 7G Network is a heuristic, a collection of interconnected hostile and anti-social behaviours that can be used to identify the if an online space is particularly “toxic”, however that might be defined.

And as a heuristic, it isn’t set in stone. The 7G is a mnemonic, and any or all of the components might be swapped out at some point. But it is a starting point, and I’ll share more on the heuristic and how it might be deployed in the coming weeks.


Bibliography:

Chesney, T., Coyne, I., Logan, B., & Madden, N. (2009). Griefing in virtual worlds: Causes, casualties and coping strategies. Information Systems Journal, 19(6), 525–548. https://doi.org/10.1111/j.1365-2575.2009.00330.x