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Simulation Theory as Cyber-Eschatology

While reviewing some of the deep cuts on accelerationism – stuff that won’t make it onto the current episode by may well be part of a standalone ep – several things kept popping up. One of those is Kurzweil’s earlier work on the Singularity (and I do happen to have a copy of that in the depths of Dr Implausible’s Bookshelf, so we’ll dig into that a bit more later). The second is repeated reference’s back to Simulation Theory, most formally put forth by Nick Bostrom, and picked up by others since.

The two competing theories mesh quite well – they’re situated at different “sides” of the singularity, pre- and post-. Kurzweil’s “A Theory of Technological Evolution: The Law of Accelerating Returns”, presented as chapter 2 of The Singularity is Near (2005) uses various trends in computing tech to extrapolate a trend where we can achieve full brain simulation and eventually neural uploading. (The timeframes he suggested for these two events were 2013 and 2025, respectively, and while there are still a few months left in 2024, I think we’ll miss those targets.) The obvious goal here, is to reach a state where full simulation can be achieved.

On the other side of that – taking a jump through the event horizon of the technological singularity – we have the Simulation Hypothesis, where the acceleration is already assumed to have taken place, and we’re all already uploaded (or NPCs in someone else’s simulation, tbh). Bostrom was writing around the same time as Kurzweil (2003 compared to 2005), so it was floating around in the zeitgeist.

Viewed in this way, simulation theory can’t be seen as anything less that a cyber-eschatology. (Eschatology being the theological interest in the final judgement and the soul). If the drive by accelerationists is to go fast enough with the development of technology that they can outrun death by uploading their consciousness, then living in a simulation is that final goal. Eternal (virtual) life.

Hail to the new (machinic) flesh.

We’ve seen this cyber-hell before, in various forms, but nowhere near as vividly as that described in Iain M Banks’ Surface Detail (2010), the penultimate novel in his Culture series. Here, we are treated to a war in the virtual heavens (and hell), and the fate that may bestow billions if this were to be achieved.

Within the context of the novel, the souls are released, but such a fate was by no means assured. And depending on your view of the fate of humanity locked away within the creches of The Matrix (1999), one might wonder if they fate they escaped to was perhaps worse than the virtual one they were entombed within.

Hard to say. This is why it remains firmly within the idea of the “post-singularity”; there’s no way to answer the question until after that event horizon is crossed.

Perhaps.

Perhaps our collective imagination will allow us to evaluate the promises and perils of the course we’re on, before we hit the point of no return. To take a look from the side at the width of the Snake River Canyon before launching down the ramp, Evel Knievel style. And maybe, just maybe that allows us to judge whether strapping rockets to our motorcycle is really the best way to make that leap.

1970s-era accelerationism at its finest.

We’ll see if that’s the fate in store for us.

AI Refractions

(this was originally published as Implausipod Episode 38 on October 5th, 2024)

https://www.implausipod.com/1935232/episodes/15804659-e0038-ai-refractions

Looking back in the year since the publication of our AI Reflections episode, we take a look at the state of the AI discourse at large, where recent controversies including those surrounding NaNoWriMo and whether AI counts as art, or can assist with science, bring the challenges of studying the new medium to the forefront.

In 2024, AI is still all the rage, but some are starting to question what it’s good for. There’s even a few that will claim that there’s no good use for AI whatsoever, though this denialist argument takes it a little bit too far. We took a look at some of the positive uses of AI a little over a year ago in an episode titled AI Reflections.

But it’s time to check out the current state of the art, take another look into the mirror and see if it’s cracked. So welcome to AI Refractions, this episode of ImplausiPod.

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’ve got a lot to catch up on with respect to AI. So we’re going to look at some of the positive uses that have come up and how AI relates to creativity and statements from NaNoWriMo caused a bit of controversy.

And how that leads into AI’s use in science. But it’s not all sunny over in AI land. We’ve looked at some of the concerns before with things like Echange, and we’ll look at some of the current critiques as well. And then look at the value proposition for AI, and how recent shakeups with open AI in September of 2024 might relate to that.

So we’ve got a lot to cover here on our near one year anniversary of that AI Reflections episode, so let’s get into it. We’ve mentioned AI a few other times since that episode aired in August of 2023. It came up in episode 28, our discussion on black boxes and the role of AI handhelds, as well as episode 31 when we looked at AI as a general purpose technology.

And it also came up a little bit in our discussion about the arts, things like Echanger and the Sphere, and how AI might be used to assist in higher fidelity productions. So it’s been an underlying theme about a lot of our episodes. And I think that’s just the nature of where we sit with relation to culture and technology.

When you spend your academic career studying the emergence of high technology and how it’s created and developed, when a new one comes on the scene, or at least becomes widely commercially available, you’re going to spend a lot of time talking about it. And we’ve been obviously talking about it for a while.

So if you’ve been with us for a while, first off, you’re Thank you, and this may be familiar to you, and if you just started listening recently, welcome, and feel free to check out those episodes that we mentioned earlier. I’ll put links to the specific ones in the text. And looking back at episode 12, we started by laying down a definition of technology.

We looked at how it functioned as an extension of man, to borrow from Marshall McLuhan, but the working definition of technology that I use, the one that I published in my PhD, is that “Technology is the material embodiment of an artifact and its associated systems, materials, and practices employed to achieve human ends.”

And this definition of technology covers everything from the sharp stick and sharp stick- related technologies like spears, pencils, and chopsticks, to our more advanced tech like satellites and AI and VR and robots and stuff. When you really think about it, it’s a very expansive definition, but that helps us in its utility in allowing us to recognize and identify things.

And by being able to cover everything from sharp sticks to satellites, from language to pharmaceuticals to games, it really covers the gamut of things that humans use technology for, and contributes to our view of technology as an emancipatory view. That technology is ultimately assistive and can aid us in issues that we’re struggling with.

We recognize that there’s other views and perspectives, but this is where we fall down on the spectrum. Returning back to episode 12, we showed how this emancipatory stance contributes to an empathetic view of technology, where we can step outside of our own frame of reference and think about how technology can be used by somebody who isn’t us.

Whether it’s a loved one, somebody close to us, or even a member of our community or collective, or you. More widely ranging, somebody that we’ll never come into contact with. How persons with different abilities and backgrounds will find different uses for the technology. Like the famous quote goes, “the street finds its own uses for things.”

Maybe we’ll return back to that in a sec. We finished off episode 12 looking at some of the positive uses of AI at that time that had been published just within a few weeks of us recording that episode. People were recounting how they were finding it as an aid or an enhancement to their creativity, and news stories were detailing how the predictive text abilities as well as generative AI facial animations could help stroke victims, as well as persons with ALS being able to converse at a regular tempo.

So by and large it could function as an assistive technology, and in recent weeks we have started trying to Catalogue all those stories. Back in July over on the blog we created the Positive AI Archive, a place where I could put those links to all the stories that I come across. Me being me, I forgot to update it since, but we’ll get those links up there and you should be able to follow along.

We’ll put the link to the archive in the show notes regardless. And, in the interest of positivity, that’s kinda where I wanted to start the show.

The street finds its own uses for things. It’s a great quote from Burning Chrome, a collection of short stories by William Gibson. It’s the one that held Johnny Mnemonic, which led to the film with Keanu Reeves, and then subsequently The Matrix and Cyberpunk 2077 and all those other derivative works. The street finds its own uses for things is a nuanced phrase and nuance can be required when we’re talking about things, especially online when everything gets reduced to a soundbite or a five second dance clip.

The street finds its own uses for things is a bit of a mantra and it’s one that I use when I’m studying the impacts of technology and what “the street finds its own uses for things” means is that the end users may put a given technology to tasks that its creators and developers never saw. Or even intended.

And what I’ve been preaching here, what I mentioned earlier, is the empathetic view of technology. And we look at who benefits from using that technology, and what we find with the AI tools is that there are benefits. The street is finding its own uses for AI. In August of 2024, a number of news reports talked about Casey Harrell, a 46 year old father suffering from ALS, amyotrophic lateral sclerosis, who was able to communicate with his daughter using a combination of brain implants and AI assisted text and speech generation.

Some of the work on these assistive technologies was done with grant money, and there’s more information about the details behind that work, and I’ll link to that article here. There’s multiple technologies that go into this, and we’re finding that with the AI tools, there’s very real benefits for persons with disabilities and their families.

Another thing we can do when we’re evaluating a technology is see where it’s actually used, where the street is located. And when it comes to assistive AI tools like ChatGPT, The street might not be where you think it is. In a recent survey published by Boston Consulting Group in August of 2024, they showed where the usage of ChatGPT was the highest.

It’s hard to visually describe a chart, obviously, but at the top of the scale, we saw countries like India, Morocco, Argentina, Brazil, Indonesia. English speaking countries like the US, Australia, and the UK were much further down on the chart. The country where ChatGPT is finding its most adoption are countries where English is not the primary language.

They’re in the global south, countries with large populations that have also had to deal with centuries of exploitation. And that isn’t to say that the citizens of these countries don’t have concerns, they do, but they’re using it as an assistive technology. They’re using it for translation, to remove barriers and to help reduce friction, and to customize their own experience. And these are just a fraction of the stories that are out there.

So there are positive use cases for AI, which may seem to directly contradict various denialist arguments that are trying to gaslight you into believing that there is no good use for AI. This is obviously false.

If the positive view, the use on the street, is being found by persons with disabilities, it follows that the denialist view is ableist. If the positive view, that use on the street, is being found by persons of color, non English speakers, persons in the global south, then the denialist view will carry all those elements of oppression, racism, and colonialism with it.

If the use on the street is by Those who find their creativity unlocked by the new tools and they’re finally able to express themselves where previously they may have struggled with a medium or been gatekept from having an arts education or poetry or English or what have you, only to now find themselves told that this isn’t art or this doesn’t count despite all evidence to the contrary, then there’s massive elements of class and bias that go into that as well.

So let’s be clear. An empathetic view of technology recognizes that there are positive use cases for AI. These are being found on the street by persons with disabilities, persons of the global south, non english speakers, and persons across the class spectrum. To deny this is to deny objective reality.

It’s to deny all these groups their actual uses of the technology. Are there problems? Yes, absolutely. Are there bad actors that may use the technology for nefarious means? Of course, this happens on a regular basis, and we’ll put a pin in that and return to that in a few moments, but to deny that there are no good uses is to deny the experience of all these groups that are finding uses for it, and we’re starting to see that when this denialism is pointed out, it’s causing a great degree of controversy.

In a statement made early in September of 2024, NaNoWriMo, the non profit organization behind National Novel Writing Month, it was acceptable to use AI as an assistive technology when writers were working on their pieces for NaNoWriMo, because this supports their mission, which is to quote, “provide the structure, community, and encouragement to help people use their voices, achieve creative goals, and build new worlds, on and off the page.” End quote.

But what drew the opprobrium of the online community is that they noted that some of the objections to the use of AI tools are classist and ableist. And, as we noted, they weren’t wrong. For all the reasons we just explained and more. But, due to the online uproar, they’ve walked that back somewhat.

I’ll link to the updated statement in the show. The thing is, if you believe that using AI for something like NaNoWriMo is against the spirit of things, that’s your decision. They’ve clearly stated that they feel that assistive technologies can help for people pursuing their dreams. And if you have concerns that they’re going to take stuff that’s put into the official app and sell it off to an LLM or AI company, well, that’s a discussion you need to have with NaNoWriMo, the nonprofit.

You’re still not held off from doing something like NaNoWriMo using notepad or obsidian or however else you take your notes, but that’s your call. I for one was glad to see that NaNoWriMo called it out. One of the things that I found both in my personal life, as well as in my research, when I was working on the PhD and looking at Tikkun Olam Makers is that it can be incredibly difficult and expensive for persons with disabilities to find a tool that can meet their needs, if it exists at all. So if you’re wondering where I come down on this, I’m on the side of the persons in need. We’re on the side of the streets. You might say we’re streets ahead.

Of course, one of the uses that the street finds for things has always been art. Or at least work that eventually gets recognized as art. It took a long time for the world to recognize that the graffiti of a street artist might count, but in 2024, if one was to argue that Banksy wasn’t an artist, you’d get some funny looks.

There are several threads of debates surrounding AI art, generative art, including the role of creativity, the provenance of the materials, the ethics of using the tools, but the primary question is what counts? What counts as art and who decides that it counts? That’s the point that we’re really raising with that question, and obviously it ties back to what we were talking about last episode when it comes to Soylent Culture, and before that when we were talking about the recently deceased Frederick Jameson as well.

In his work Nostalgia for the Present from 1989, Jameson mentioned this with respect to television. He said, Quote, “At the time, however, it was high culture in the 1950s who 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 judgments.” end quote.

Now, High Art in Bunny Quotes isn’t issuing anything, obviously, Jameson’s reifying the term, but what Jameson is getting at is that there’s stakes for those involved about what does and does not count. And we talked about this last episode, where it took a long time for various forms of new media to finally be accepted as art on its own terms.

For some, it takes longer than others. I mean, Jameson was talking about television in the 1980s, for something that had already existed for decades at that point. And even then, it wasn’t until the 90s and 2000s, to the eras of Oz and The Sopranos and Breaking Bad and Mad Men and the quote unquote “golden age of television” that it really began to be recognized and accepted as art on its own terms.

Television was seen as disposable ephemera for decades upon decades. There’s a lot of work that goes on on behalf of high art by those invested in it to valorize it and ensure that it maintains its position. This is why we see one of the critiques about A. I. art being that it lacks creativity, that it is simply theft.

As if the provenance of the materials that get used in the creation of art suddenly matter on whether it counts or not. It would be as if the conditions in the mines of Afghanistan for the lapis lazuli that was crushed to make the ultramarine used by Vermeer had a material impact on whether his painting counted as art. Or if the gold and jewels that went into the creation of the Fabergé eggs and were subsequently gifted to the Russian royal family mattered as to whether those count. It’s a nonsense argument. It makes no sense. And it’s completely orthogonal to the question of whether these works count as art.

And similarly, where people say that good artists borrow, great artists steal, well, we’ll concede that Picasso might have known a thing or two about art, but Where exactly are they stealing it from? The artists aren’t exactly tippy toeing into the art gallery and yoinking it off the walls now, are they?

No, they’re stealing it from memory, from their experience of that thing, and the memory is the key. Here, I’ll share a quote. “Art consists in bringing the memory of things past to the surface. But the author is not a Paessiest. He is a link to history, to memory, which is linked to the common dream.” This is of course a quote by Saul Bellow, talking about his field, literature, and while I know nowadays not as many people are as familiar with his work, if you’re at a computer while you’re listening to this, it might be worth to just look him up.

Are we back? Awesome. Alright, so what the Nobel Prize Laureate and Pulitzer Prize winner Saul Bellow was getting at is that art is an act of memory, and we’ve been going in depth into memory in the last three episodes. And the artist can only work with what they have access to, what they’ve experienced during the course of their lifetime.

The more they’ve experienced, the more they can draw on and put into their art. And this is where the AI art tools come in as an assistive technology, because they would have access to much, much more than a human being can experience, right? Possibly anything that has been stored and put into the database and the creator accessing that tool will have access to everything, all the memory scanned and stored within it as well.

And so then the act of art becomes one of curation of deciding what to put forth. AI art is a digital art form, or at least everything that’s been produced to date. So how does that differ? Right? Well, let me give you an example. If I reach over to my paint shelf and grab an ultramarine paint, right, a cheap Daler Rowney acrylic ink, it’s right there with all the other colors that might be available to me on my paint shelf.

But, back in the day, if we were looking for a specific blue paint, an ultramarine, it would be made with lapis lazuli, like the stuff that Vermeer was looking for. It would be incredibly expensive, and so the artist would be limited in their selection to the paints that they had available to them, or be limited in the amount that they could actually paint within a given year.

And sometimes the cost would be exorbitant. For some paints, it still actually is, but a digital artist working on an iPad or a Wacom tablet or whatever would have access to a nigh unlimited range of colors. And so the only choice and selection for that artist is by deciding what’s right for the piece that they’re doing.

The digital artist is not working with a limited palette of, you know, a dozen paints or whatever they happen to have on hand. It’s a different kind of thing entirely. The digital artist has a much wider range of things to choose from, but it still requires skill. You know, conceptualization, composition, planning, visualization.

There’s still artistry involved. It’s no less art, but it’s a different kind of art. But one that already exists today and one that’s already existed for hundreds of years. And because of a banger that just got dropped in the last couple of weeks, it might be eligible for a Grammy next year. It’s an allographic art.

And if you’re going to try and tell me that Mozart isn’t an artist, I’m going to have a hard time believing you.

Allographic art is a type of art that was originally introduced by Nelson Goodman back in the 60s and 70s. Goodman is kind of like Gordon Freeman, except, you know, not a particle physicist. He was a mathematician and aesthetician, or sorry, philosopher interested in aesthetics, not esthetician as we normally call them now, which has a bit of a different meaning and is a reminder that I probably need to book a pedicure.

Nelson was interested in the question of what’s the difference between a painting and a symphony, and it rests on the idea of like uniqueness versus forgery. A painting, especially an oil painting, can be forged, but it relies on the strokes and the process and the materials that went into it, so you need to basically replicate the entire thing while doing it in order to make an accurate forgery, much like Pierre Menard trying to reproduce Cervantes ‘Quixote’ in the Jorge Luis Borges short story.

Whereas a symphony, or any song really, that is performed based off of a score, a notational system, is simply going to be a reproduction of that thing. And this is basically what Walter Benjamin was getting at when he was talking about art in the age of mechanical reproduction, too, right? So, a work that’s based off of a notational system can still count as a work of art.

Like, no one’s going to argue that a symphony doesn’t count as art, or that Mozart wasn’t an artist. And we can extend that to other forms of art that use a notational system as well. Like, I don’t know, architecture. Frank Lloyd Wright didn’t personally build Falling Water or the Guggenheim, but he created the plans for it, right?

And those were enacted. He did. We can say that, yeah, there’s artistic value there. So these things, composition, architecture, et cetera, are allographic arts, as opposed to autographic arts, things like painting or sculpture, or in some instances, the performance of an allographic work. If I go to see an orchestra playing a symphony, a work based off of a score, I’m not saying that I’m not engaged with art.

And this brings us back to the AI Art question, because one of the arguments you often see against it is that it’s just, you know, typing in some prompts to a computer and then poof, getting some results back. At a very high level, this is an approximation of what’s going on, but it kind of misses some of the finer points, right?

When we look at notational systems, we could have a very, you know, simple set of notes that are there, or we could have a very complex one. We could be looking at the score for Chopsticks or Twinkle Twinkle Little Star, or a long lost piece by Mozart called Serenade in C Major that he wrote when he was a teenager and has finally come to light.

This is an allographic art, and the fact that it can be produced and played 250 years later kind of proves the point. But that difference between simplicity and complexity is part of the key. When we look at the prompts that are input into a computer, we rarely see something with the complexity of say a Mozart.

As we increase the complexity of what we’re putting into one of the generative AI tools, we increase the complexity of what we get back as well. And this is not to suggest that the current AI artists are operating at the level of Mozart either. Some of the earliest notational music we have is found on ancient cuneiform tablets called the Hurrian Hymns, dating back to about 1400 BCE, so it took us a little over 3000 years to get to the level of Mozart in the 1700s.

We can give the AI artists a little bit of time to practice. The generative AI art tools, which are very much in their infancy, appear to be allographic arts, and they’re following in their lineage from procedurally generated art has been around for a little while longer. And as an art form in its infancy, there’s still a lot of contested areas.

Whether it counts, the provenance of materials, ethics of where it’s used, all of those things are coming into question. But we’re not going to say that it’s not art, right? And as an art, as work conducted in a new medium, we have certain responsibilities for documenting its use, its procedures, how it’s created.

In the introduction to 2001’s The Language of New Media, Lev Manovich, in talking about the creation of a new media, digital media in this case, noted how there was a lost opportunity in the late 19th and early 20th century with the creation of cinema. Quote, “I wish that someone in 1895, 1897, or at least 1903 had realized the fundamental significance of the emergence of the new medium of cinema and produced a comprehensive record.

Interviews with audiences, systematic account of narrative strategies, scenography, and camera positions as they developed year by year. An analysis of the connections between the emerging language of cinema and different forms of popular entertainment that coexisted with it. Unfortunately, such records do not exist.

Instead, we are left with newspaper reports, diaries of cinema’s inventors, programs of film showings, and other bits and pieces. A set of random and unevenly distributed historical samples. Today, we are witnessing the emergence of a new medium, the meta medium of the digital computer. In contrast to a hundred years ago, when cinema was coming into being, We are fully aware of the significance of this new media revolution.

Yet I am afraid that future theorists and historians of computer media will be left with not much more than the equivalence of the newspaper reports and film programs from cinema’s first decades.” End quote.

Manovich goes on to note that a lot of the work that was being done on computers, especially in the 90s, was stuff prognosticating about its future uses, rather than documenting what was actually going on.

And this is the risk that the denialist framing of AI art puts us in. By not recognizing that something new is going on, that art is being created, and allographic art, we lose the opportunity to document it for the future. And

And as with art, so too with science. We’ve long noted that there’s an incredible amount of creativity that goes into scientific research, that the STEM fields, science, technology, engineering, and mathematics, require and benefit so much from the arts that they’d be better classified as STEAM, and a small side effect of that may mean that we see better funding for the arts at the university level.

But I digress. In the examples I gave earlier of medical research, of AI being used as an assistive technology, we were seeing some real groundbreaking developments of the boundaries being pushed, and we’re seeing that throughout the science fields. Part of this is because of what AI does well with things like pattern recognition, allowing weather forecasts, for example, to be predicted more quickly and accurately.

It’s also been able to provide more assistance with medical diagnostics and imaging as well. The massive growth in the number of AI related projects in recent years is often due to the fact that a number of these projects are just rebranded machine learning or deep learning. In a report released by the Royal Society in England in May of 2024 as part of their Disruptive Technology for Research project, they note how, quote, “AI is a broad term covering all efforts aiming to replicate and extend human capabilities for intelligence and reasoning in machines.”

End quote. They go on further to state that, quote, “Since the founding of the AI field at the 1956 Dartmouth Summer Research Project on Artificial Intelligence, Many different techniques have been invented and studied in pursuit of this goal. Many of these techniques have developed into their own sub fields within computer science, such as expert systems and symbolic reasoning.” end quote.

And they note how the rise of the big data paradigm has made machine learning and deep learning techniques a lot more affordable and accessible, and scalable too. And all of this has contributed to the amount of stuff that’s floating around out there that’s branded as AI. Despite this confusion in branding and nomenclature, AI is starting to contribute to basic science.

A New York Times article published July by Siobhan Roberts talked about how a couple AI models were able to compete at the level of a silver medalist at the recent International Mathematical Olympiad. And this is the first time that the AI model has medaled at that competition. So there may be a role for AI to assist even high level mathematicians to function as collaborators and, again, assistive technologies there.

And we can see this in science more broadly. In a paper submitted to arxiv. org in August of 2024, titled, The AI Scientist Towards Fully Automated Open Ended Scientific Discovery, authors Liu et al. use a frontier large language model to perform research independently. Quote, “We introduce the AI scientist, which generates novel research ideas, writes code, executes experiments, visualizes results, describes its findings by writing a scientific paper, And then runs the simulated review process for evaluation” end quote.

So, a lot of this is scripts and bots and hooking into other AI tools in order to simulate the entire scientific process. And I can’t speak to the veracity of the results that they’re producing in the fields that they’ve chosen. They state that their paper can, quote, “Produce papers that exceed the acceptance threshold at a top machine learning conference as judged by our automated reviewer,” end quote.

And that’s Fine, but it shows that the process of doing the science can be assisted in various realms as well. And in one of those areas of assistance, it’s in providing help for stuff outside the scope of knowledge of a given researcher. AI as an aid in creativity can help explore the design space and allow for the combination of new ideas outside of everything we know.

As science is increasingly interdisciplinary. We need to be able to bring in more material, more knowledge, and that can be done through collaboration, but here we have a tool that can assist us as well. As we talked about with Nessience and Excession a few episodes ago, we don’t know everything. There’s more than we can possibly know, so the AI tools help expand the field of what’s available to us.

We don’t necessarily know where new ideas are going to come from. And if you don’t believe me on this, let me reach out to another scientist who said some words on this back in 1980. Quote, “We do not know beforehand where fundamental insights will arise from about our mysterious and lovely solar system.

And the history of our study of the solar system shows clearly that accepted and conventional ideas are often wrong, and that fundamental insights can arise from the most unexpected sources.” End quote. That, of course, is Carl Sagan. From an October 1980 episode of Cosmos A Personal Journey, titled Heaven and Hell, where he talks about the Velkovsky Affair.

I haven’t spliced in the original audio because I’m not looking to grab a copyright strike, but it’s out there if you want to look for it. And what Sagan is describing there is basically the process by which a Kuhnian paradigm shift takes place. Sagan is speaking to the need to reach beyond ourselves, especially in the fields of science, and the AI assisted research tools can help us with that.

And not just in the conduction of the research, but also in the writing and dissemination of that. Not all scientists are strong or comfortable writers or speakers, and many of them come to English as a second, third, or even fourth language. And the role of AI tools as translation devices means we have more people able to communicate and share their ideas and participate in the pursuit of knowledge.

This is not to say that everything is rosy. Are there valid concerns when it comes to AI? Absolutely. Yes. We talked about a few at the outset and we’ve documented a number of them throughout the run of this podcast. One of our primary concerns is the role of the AI tools in échanger, that replacement effect that happens that leads to technological unemployment.

Much of the initial hype and furor around the AI tools was people recognizing that potential for échanger following the initial public release of ChatGPT. There’s also concerns about the degree to which the AI tools may be used as instruments of control, and how they can contribute to what Gilles Deleuze calls a control society, which we talked about in our Reflections episode last year.

And related to that is the lack of transparency, the degree to which the AI tools are black boxes, where based on a given set of inputs, we’re not necessarily sure about how it came up with the outputs. And this is a challenge regardless of whether it’s a hardware device or a software tool.

And regardless of how the AI tool is deployed, the increased prevalence of it means we’re leading to a soylent culture. With an increased amount of data smog, or bitslop, or however you want to refer to the digital pollution that takes place with the increased amount of AI content in our channels and For-You-Feeds, and this is likely to become even more heightened as Facebook moves to pushing AI generated posts into the timelines.

Many are speculating that this is becoming so prevalent that the internet is largely bots pushing out AI generated content, what’s called the “Dead Internet Theory”, which we’ll definitely have to take a look at it in a future episode. Hint, the internet is alive and well, it’s just not necessarily where you think it is.

And with all this AI generated content, we’re still facing the risk of the hallucinations, which we talked about, holy moly, over two years ago when we discussed the LOAB, that brief little bit of creepypasta that was making the rounds as people were trying out the new digital tools. But the hallucinations still highlight one of the primary issues with the AI tools, and that’s the errors in the results.

In order to document and collate these issues, a research team over at MIT has created the AI Risk Repository. It’s available at airisk. mit. edu. Here they have created taxonomies of the causes and domains where the risks may take place. However, not all of these risks are equal. One of the primary ones that gets mentioned is the energy usage for AI.

And while it’s not insignificant, I think it needs to be looked at in context. One estimate of global data center usage was between 240 and 340 terawatt hours, which is a lot of energy, and it might be rising as data center usage for the big players like Microsoft and Google has gone up by like 30 percent since 2022.

And that still might be too low, as one report noted that the actual estimate could be as much as 600 percent higher. So when you put that all together, that initial estimate could be anywhere between a thousand and 2000 terawatts. But the AI tools are only a fraction of what goes on at the data centers, which include cloud storage and services, streaming video, gaming, social media, and other high volume activities.

So you bring that number right back down. And AI is using? The thing is, whatever that number is, 300 terawatts times 1. 3 times six divided by five. Whatever that result ends up being doesn’t even chart when looking at global energy usage. Looking at a recent chart on global primary energy consumption by source over at Our World in Data, we see that the worldwide consumption in 2023 was 180, 000 terawatt hours.

The amount of energy potentially used by AI hardly registers as a pixel on the screen compared to worldwide energy usage that were presented with the picture in the media where AI is burning up the planet. I’m not saying AI energy usage isn’t a concern. It should be green and renewable. And it needs to be verifiable, this energy usage of the AI companies, as there is the risk of greenwashing the work that is done, of painting over their activities true energy costs by highlighting their positive impacts for the environment.

And the energy usage may be far exceeded by the water usage that’s used for the cooling of the data centers. And as with the energy usage, the amount of water that’s actually going to AI is incredibly hard to dissociate from all the other activities that are taking place in these data centers. And this greenwashing, which various industries have long been accused of, might show up in another form as well.

There is always the possibility that the helpful stories that are presented, AI tools have provided for various at risk and minority populations, are presented as a form of “aidwashing”. And this is something we have to evaluate for each of the stories posted in the AI Positivity Archive. Now I can’t say for sure that “aidwashing” specifically as a term exists.

A couple searches didn’t return any hits, so you may have heard it here first. However, while positive stories about AI often do get touted, do we think this is the driving motivation for the massive investment we’re seeing in the AI technologies? No, not even for a second. These assistive uses of AI don’t really work with the value proposition for the industry, even though those street uses of technology may point the way forward in resolving some of the larger issues for AI tools with respect to resource consumption and energy usage.

The AI tools used to assist Casey Harrell, the ALS patient mentioned near the beginning of the show, use a significantly smaller model than one’s conventionally available, like those found in ChatGPT. The future of AI may be small, personalized, and local, but again, that doesn’t fit with the value proposition.

And that value proposition is coming under increased scrutiny. In a report published by Goldman Sachs on June 25th, 2024, they question if there’s enough benefit for all the money that’s being poured into the field. In a series of interviews with a number of experts in the field, they note how initial estimates about both the cost savings, the complexity of tasks that AI is available to do, and the productivity gains that would derive from it, are all much lower than initially proposed or happening on a much longer time frame.

In it, MIT professor Daron Acemoglu forecasts minimal productivity and GDP growths, around 0. 5 percent or 1%, whereas Goldman Sachs predictions were closer to 9 percent and 6 percent increase in GDP. With such varying degrees of estimates, what the actual impact of AI in the next 10 years is, is anybody’s guess.

It could be at either extreme or somewhere in between. But the main takeaway from this is that even Goldman Sachs is starting to look at the balance sheet and question the amount of money that’s being invested in AI. And that amount of money is quite large indeed.

In between starting recording this podcast episode and finishing it, OpenAI raised 6. 6 billion dollars in a funding round from its investors, including Microsoft and Nvidia, which is the largest ever recorded. As reported by Reuters, this could value the company at 157 billion dollars and make it one of the the world. valuable private companies in the world. And this coincides with the recent restructuring from a week earlier which would remove the non profit control and see it move to a for profit business model.

But my final question is, would this even work? Because it seems diametrically opposed to what AI might actually bring about. If assistive technology focused on automation and Echange, then the end result may be something closer to what Aaron Bastani calls “fully automated luxury communism”, where the future is a post-scarcity environment that’s much closer to Star Trek than it is to Snow Crash.

How do you make that work when you’re focused on a for profit model? The tool that you’re using is not designed to do what you’re trying to make it do. Remember, “The street finds its own uses for things”, though in this case that street might be Wall Street. The investors and forecasters at Goldman Sachs are recognizing that disconnect by looking at the charts and tables in the balance sheet.

But their disconnect, the part that they’re missing, is that the driving force towards AI may be one more of ideology. And that ideology is the California ideology, a term that’s been floating around since at least the mid 1990s. And we’ll take a look at it next episode and return to the works of Lev Manovich, as well as Richard Barbrook, Andy Cameron, and Adrian Daub, as well as a recent post by Sam Altman titled ‘The Intelligence Age’.

There’s definitely a lot more going on behind the scenes.

Once again, thank you for joining us on the Implausipod. I’m your host, Dr. Implausible. 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 perhaps somewhat surprisingly, given the topic of our episode, no AI is used in the production of this podcast. Though I think some machine learning goes into the transcription service that we use. And the show is licensed under 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’s 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 implausopod.

com, which will go to any hosting costs associated with the show. I’ve put a bit of a hold on the blog and the newsletter, as WordPress is turning into a bit of a dumpster fire, and I need to figure out how to re host it. But the material is still up there, I own the domain. It’ll just probably look a little bit more basic soon.

Join us next time as we explore that Californian ideology, and then we’ll be asking, who are Roads for? And do a deeper dive into how we model the world. Until next time, take care and have fun.

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TikTok Tribulations

(this was originally published as Implausipod E0033 on June 10th, 2024)

What happens if your community disappears? How do online groups deal with the challenges of maintaining their social ties across fickle and fleeting platforms? And are there lessons to be learned by the TikTok creators from the online MMO communities that were shut down in the early 2000s?

https://www.implausipod.com/1935232/episodes/15146242-e0033-tiktok-tribulations

[00:00:00] DrI: On the last episode of the ImplausiPod, we asked what happened if you built an app and the community was still toxic, like, whoops, what do you do next? But there’s a darker side to that question. What if you built a successful community and then it disappeared? On April 24th, 2024, the US President Joe Biden signed a foreign aid package bill that included legislation demanding that ByteDance, the parent company of TikTok, divest itself of those holdings to an American owned firm or face banning in the United States. If the sale doesn’t happen within 270 days, TikTok would be prevented from appearing in app stores, as well as certain internet hosting services. Now, of course the story isn’t over, this will be contested and appealed, but for those individuals who had developed or participated in communities on TikTok, it can be a significant loss.

A loss that we’re going to look at in episode 33 of the Implausipod.

Welcome to the Implausipod, an academic podcast about the intersection of art, technology and popular culture. I’m your host, Dr. Implausible. And today we’re talking about the closure of online communities. It’s rare that a thriving online community is shut down, or explicitly banned. Often what happens is that a new competing service opens up and the user base dwindles until all that is left is a shell of the former community.

Other times, the service gets sold off, changing hands, and the community gets parceled off, the data being sold, the policy changes making the community lose interest and find alternatives. The latter can be seen in services like Yahoo Groups, Tumblr, Google Groups, Google Wave, Google Plus. There might be a bit of a trend there, is what I’m saying.

Examples of services actively shutting down can be seen more often in the video game market, especially in MMOs. The glut of MMOs in the early 21st century, all built on the assumption of online play and needing an engaged community to drive the operation, led to the abandonment of that community when the service shut down, the game was canceled, or the servers were closed.

Now, in some cases, the community was strong and was able to keep things going after a fashion, but in most cases, closure of the servers meant the end of the game, and the dispersal of the members of the community. Sometimes the community knew it was coming and were able to go out with a blaze of glory, as seen on the Matrix Online or the original City of Heroes, but sometimes the community just ended.

The server’s turned off, and the light’s no longer on. And this closure, with a looming deadline, is what communities and creators on TikTok are now facing. The announcement on April 24th started a ticking clock, a 270 day countdown timer with a date for divestment of the app by its parent company. And, in late April and early May following the announcement, a number of creators on the app, some recognizable figures, some longtime lurkers, first time posters, made heartfelt appeals.

To the communities that they built or discovered during their time on TikTok. I’d like to share a couple of those with you right now. They’re short because, well, it is TikTok after all, but if there is a video version of this podcast, I’ll try my best to splice them in. The first is by a creator by the name of Vegas Starfish, an events planner in Las Vegas, Nevada, USA.

At the time of recording of this episode, Her post had received a quarter of a million views, garnering 40, 000 likes and several thousand comments. Here’s her post, in her own words.

[00:03:39] Vegas: This is my farewell to TikTok. As you know, TikTok was just banned in the United States. This app changed my life. This is me before TikTok, and this is me after.

I was a miserable, mid level casino executive. I started making content about my city and how much I loved it, and then I started living life. I have never made this platform about me. It was always about the city, but I want to show you a glimpse at the creator behind the videos. I’ve always been socially awkward.

And it was through this app that I was able to meet other creators and most importantly, meet so many of you, every single one of you changed my life. Suddenly my voice mattered and I had a purpose and I started living boldly. I began traveling all over the world. As my self worth and self confidence grew, I became a better parent, a better friend, and I’ve never been great at making friends, but the best ones I’ve ever had came through this app.

I’ve had the opportunity to work with incredible artists and creators, people that I would have never had access to otherwise, and together by creating dynamic content, we’ve been able to change the paths for thousands of small businesses by directly highlighting great people doing great things. We’ve done so much good.

I know that the loss of this app will hurt creators and businesses financially, but I’m afraid of losing the human connection. We’ve been able to take you along for amazing resorts opening and iconic ones closing. Together we were among the first to discover a massive corporate hack last fall. You were with me when the sphere opened and we saw F1 cars race down the Las Vegas Strip together.

I have shared thousands of moments with millions of people. It has fundamentally changed my life and the lives of so many others. I am eternally grateful for every experience and every interaction. It has been a whirlwind. And I appreciate you more than you know. I hope to see some of you on IG. And thank you for following me for all the Vegas.

A special shout out to the feral cat from the Rio who helped me go viral in the beginning. You’re the real MVP.

[00:05:40] DrI: Here we can see how a person was able to change their career, find and build a community, and increase their personal happiness by becoming more engaged with the job they were doing. sharing that and then reaching out and taking a more active role within the community to the extent that they experienced better mental and physical health and career growth and wellbeing.

Pretty awesome all around. And while her story was specific to TikTok, there are similar stories like hers on many other platforms. During the same week that Vegas starfish posted, there was another post that was made that also. went somewhat viral, and it went into the benefits of TikTok for that person.

This was a first time post by a long time lurker, who felt compelled to reach out to her community for the first time because of the impending ban. I’ll play a portion of that post here, as the full post is over four and a half minutes long.

[00:06:36] Katy: Hi, my name’s Katie. And I’ve never posted on TikTok before, and I probably never will again, but I was watching the live vote today on TikTok, um, for Congress to ban it.

And I just started really reflecting on the past four years that I’ve been watching TikTok. I’ve been just a lurker. I don’t post. I just watch. Um, but it’s meant a lot to me and I wanted to maybe record my first and only video as a thank you. It’s going to be pretty rough because I had to look up how to do all of this.

So I apologize for that. I found TikTok in 2020 during COVID when my children with disabilities came home from school and instead of just mother, I was mother and teacher. And it was overwhelming. And I lived in a pretty homogenous suburban neighborhood where there was very much one way to be. And. I had a mental breakdown.

I know I’m not the only one and I was prescribed more antidepressants or maybe a stay in a treatment facility for an eating disorder. But instead, the thing that really helped me was discovering TikTok and all of you. I Learned a new parenting language toward my children that was very different from the one that I was taught from Mama Cusses.

Um, I was diagnosed with ADHD, as were we all, and I learned how to manage it and do struggle care, closing duties, and reset to functional with Casey Davis. Um, I learned how to normalize being normal from Emily Jean, I, um, watched TV shows and movies and pieces that I never would have watched before because of ADHD and anxiety comfort.

Always like watching the same thing. I learned that it’s. Um, normal and okay to cosplay, to, um, treat your fandoms like old friends, to like to read spicy fiction. Um, I learned more about my neurodivergent or neurospicy children in the last four years on TikTok than I did online. Almost all of the earlier childhood.

[00:08:49] DrI: And from there, Katie goes on to thank some of the specific creators that she followed and whose content she enjoyed. And we can see within her posts some of the challenges that she was facing, both as a mother and a teacher, dealing with a mental breakdown and parenting children with special needs, learning concepts like struggle care and normalize, and being exposed to new media, new hobbies, new fandoms, basically learning in all of these instances.

And in her post, we can see how much community contributed to that. And this is the power of community to the audience. Now, sometimes they’re derogatorily referred to as lurkers and the level of involvement and investment that they perceive to have of themselves with relation to the community. These can often be referred to as

parasocial relationships, and this can be true. Parasocial relationships are one sided relationships where someone develops a sense of connection or familiarity with someone they don’t know, like a celebrity or a media figure. With the rise of social media, creating more media figures than ever before, People have observed the rise of these relationships, but the term has been around since the 1950s when Horton and Wohl observed it in television audiences.

These relationships may look fake to the outside observer, but we can also see the power that these invisible social ties have. This is the demonstration of a well known phenomenon in the social sciences. In 1973, Mark Granovetter wrote a famous paper called The Strength of Weak Ties. You might not have heard of the paper, but judging by the nearly 40, 000 times it’s been cited, perhaps what was in the paper has been filtered out to become common knowledge.

In this paper, Granovetter was looking at job hunting specifically, and how people use their connections when searching for a job. And found that it was the secondary social ties, not your best friends, but your more casual acquaintances, that were more likely to come through in something like a job search.

Because your best friends, your strong ties, are more likely to run in similar social circles. They would be aware of similar opportunities. But those more Distant ties allow for further reach, and can be helpful as one looking for a career change, for example. We can see the effects of both of these in the posts I included above.

Both creators spoke of new connections they made, the knowledge they gained, and how they both Benefited from those social connections. There was another benefit that both creators had as well, though it isn’t as obvious. In the second post, Katie’s post, we can see how easy it was for a first time creator to reach out and make a post that was able to reach a million.

This has been one of the strengths of TikTok as a platform. As a tool, it democratized content production, turning users into Creators able to produce fully edited videos along with effects, captions, and connected to other content at the push of a button. And I cannot stress this enough, comparing something like TikTok to what needs to be done to produce this podcast or YouTube video, for instance, is night and day.

As the saying goes, the purpose of a system is what it does. A well known systems theory quote from Stafford Beer. And this is what TikTok succeeds at more than most. It isn’t just the algorithmic content delivery and sorting mechanisms that go on behind the scenes, but also turning more and more people into content creators.

To this end, TikTok democratizes the opportunity to create. It removes gatekeepers from the products and allows users to make the materials that they want to see. Often, when we talk about democratization, we’re talking about material things, but here we’re seeing it with informational objects as well.

People can create exactly what they want to see and then share it with everybody and perhaps find an audience for those kinds of things, whether they knew one existed or not. And as Eric von Hippel points out in his 2005 book on innovation, it’s more than just the products quote, it’s the joy and the learning associated with creativity and membership in creative communities that are also important.

These experiences too are made more widely available as innovation is democratized. End quote. And I really want to stress this because this is what pretty much every article that I’ve seen on TikTok misses the fact on. Everybody points towards the algorithm or the social network and those elements of it, but the true secret sauce of TikTok is the ease of use of the content creation tools.

It can literally, with the push of a button, turn anybody and everybody into a television producer. Or director, or actor, or creative of some form. If TikTok is the new television, which I argued four years ago or so now, then everybody who posts on TikTok is a TV content creator of some kind. And I’m gonna let that sit for a second.

To expand further on that idea of democratization, I’m gonna return to Eric Von Hippel and quote at length. User firms, and increasingly even individual hobbyists, have access to sophisticated design tools for fields ranging from software to electronics to musical composition. All these information based tools can be run on a personal computer and are rapidly coming down in price.

With relatively little training and practice, they enable users to design new products and services, and music and art. At a satisfyingly sophisticated level, then if what has been created is an information product, such as software or music, the design is the actual product, software you can use or music you can play, end quote.

Now that was published in 2005, so we’re seeing him capture in writing the effects of both the dot com revolution and the wide scale rollout of new computing in advance of the Y2K issue. That saw a massive expanse in computing products as everybody was purchasing new machines that were Y2K compatible.

But let’s go back to Von Hippel’s quote there. So, individual hobbyists having access to sophisticated design tools. Check. Allowing musical composition, video editing, all at the touch of a button. Absolutely. That’s what TikTok does. They could run on a personal computer at the time or now just the phone that is pretty much readily available to everybody.

Check. Rapidly coming down in price. Check. Basically free with an app or several apps in some cases with relatively little training and practice. Yes, new products and services and music and art all these things and we see some of this with AI tools Even though that’s not what we’re talking about right now and at a satisfyingly sophisticated level Good enough to show on the internet and a lot of people are obviously engaged with it and then software you can use music You can play Yes, the design is the product.

The thing that gets put out, gets shared with everybody, and that is the thing. And, as he said in the previous quote, this builds and allows access to creative communities, which ties directly to the quotes from the two TikTok users that we saw. There’s also another side effect of this democratization of content, and that is the increasing media literacy.

If we posit that literacy is not just being an informed reader, but also allows one the ability to write, so both input and output, upstream and downstream, then being more aware of content production The difference between what gets recorded, what gets seen, and how the audience reacts makes everybody involved more media literate.

Or at least it would if they’re paying attention. And I think to a large degree people are becoming more aware. However, more than just examples of democratizing content production and enhancing media literacy, Both posts from the users that I shared are evidence of the positive benefits of community.

We’ve referred to Howard Rheingold’s work on the virtual community earlier, and he quotes at length from M. Scott Peck’s Different Drum at the start of his book, and Scott writes, quote, We know the rules of community. We know the healing effect of community in terms of individual lives. If we could somehow find a way across the bridge of our knowledge, would not these same rules have a healing effect upon our world?

We human beings have often been referred to as social animals, but we are not yet community creatures. We are impelled to relate with each other for our survival, but we do not yet relate with the inclusivity, realism, self awareness, vulnerability, commitment, openness, freedom, equality, and love of genuine community.

It is clearly no longer enough to be simply social animals babbling together at cocktail parties and brawling with each other in business and over boundaries. It is our task, our essential, central, crucial task, to transform ourselves from mere social creatures into community creatures. It is the only way that human evolution will be able to proceed.

It’s a rather lengthy list that Scott has there in the middle of that quote. Inclusivity, realism, self awareness, vulnerability, commitment, openness, freedom, equality, and love of genuine community. But, I think it’s an essential one. When we think of the world around us, those are all things that we could use a little bit more of.

And as sociologist Richard Sennett notes in his book, Together, this community can be vocational as well. That working towards building the community can have such significant effects that it’s beneficial to all those involved, even the bystanders. As we saw with The Lurker in our second quote, that the audience gains benefits from the community as well.

The communities described by both creators are both meaningful. real despite being online. As we mentioned last episode, and probably often, is that there is no difference between online and offline communities save for the annihilation of distance and time. The distinctions made between cyberspace and quote meat space is often a false dichotomy.

Within academic writing on online communities, social networks, and the like, This difference was sometimes highlighted early in the literature, though more recent critical or reflective writing may no longer make that distinction. And that happens because in the 30 years or so since the publication of Rheingold’s Virtual Community, we have some Fantastic real world examples of what happens in online communities, especially when they go away.

And the reason there are so many online communities that went away is that in the early 2000s, having an online community was part of the business model of a number of companies. Including companies that were developing online games. And specifically those developing MMOs. The wave of massively multiplayer online roleplaying games that relied on a monthly subscription model.

This largely paralleled the shift to Web 2. 0 that was occurring at that time. around 1999 to 2004. But as we’ve been seeing with a lot of things gaming related during the course of this podcast, the gaming community somewhat preceded it, acting as a harbinger of things to come. Web 2. 0 is of course the change in the web from static web pages to user generated content, or UGC.

The MMO boom started in 1997 with the release of Ultima Online. where the term was coined, but it really took off beginning in 1999 with the release of EverQuest, and then heading straight to the moon with the release of World of Warcraft in 2004, and not 2001’s Shadows of Luclin expansion as maybe three people listening to this podcast might have been guessing.

Within the window of the MMO boom, numerous MMOs were launched based on a wide variety of intellectual property. Some licensed, some original, and all developed a community of some fashion around them. Even though the subscription based model that most used during this initial period represented a kind of Software as a Service, or SAAS, They were really more like community in a box.

The games relied on the volunteer labor provided by the community in terms of guides, maps, strategies, and communication hubs, external to the games themselves. In many cases, the games would be extremely difficult without the shared knowledge bases that the communities provided. It was the epitome of participatory culture that we discussed back in episode 16 on Spreadable Media.

And the communities. built around these games in part on the shared labour and collective action that was put into their creation. MMOs lived and died by the communities that existed around them. Alas, in a very dense and competitive marketplace, not every MMO succeeded, even if the community was there.

So I’d like to take a look at three that had high aspirations but ended up shutting down. These three were Sony Online Entertainment’s Star Wars Galaxies, released in 2003, Cryptic Studios slash NCSoft’s City of Heroes, launched in 2004, and Monolith Productions 2005 release of The Matrix Online. Each of these were big budget MMOs with a large fanbase.

Some due to the tie ins with existing popular media licenses, and in City of Heroes case, being a generic superhero simulator in the era prior to the rise of the MCU wasn’t a bad thing. It emphasized team play, with groups of heroes working together to complete missions and fight larger threats, emulating the fiction of the superhero comics in general.

Star Wars Galaxies was developed by Sony Online, with a rich user driven in game economy developed by Raph Koster, one of the more notable MMO designers from his work on Ultima Online, who pushed for a simulationist view, where players would be crafting all the gear and materials used in the game. At least, initially.

And the Matrix Online provided a rich narrative experience, providing what is called transmedia storytelling, as the events taking place in the game are part of the larger continuity of stories told about the Matrix, coexisting with the events of the movies and other properties like the Animatrix. Each of these games managed to develop a dedicated community of players, active participants in engaging and extending the world.

But despite this active community, each of these properties failed, and the MMOs were closed. For The Matrix Online, it was shut down in 2009 due to low player numbers, as competition was tough, and honestly, the 2008 crash saw a number of properties struggle with their business model. For Star Wars Galaxies, when it closed in 2011, it was stated it was due to the loss of the license for Star Wars gaming,

which is a risk for any media property as well. For City of Heroes, without the licensing issues of the other two, it was a change in the focus of the publisher as the stated reason for its closure in 2012. At least, for a little while. The interesting thing is how these communities reacted to the closing of the servers, of knowing that the community that they had lovingly built was was going to disappear at a specified point in the future.

Each of the games had a massive farewell event, with the community coming online to celebrate the last moments. The Matrix Online turned it into a story event, and you can check out the link to the videos of that storyline in the show notes. The fans of Star Wars Galaxies created a similar event, and I’ll link that one too, culminating in a massive battle between the Empire and the Rebel Alliance that was live streamed on the internet.

City of Heroes had a number of player run events leading up to the servers being shut down. When they went dark, all three Of these MMOs saw their communities dispersed, a virtual diaspora drifting out to other online places and virtual spaces.

But for both Star Wars Galaxies and City of Heroes, the game lived on. Fans of each game had started private servers using emulation software, allowing the members of the community to meet up again and play the game, after a fashion, much the same as they had before. Not every member of the old community signed up for the emulator servers, of course, and they did skirt the bounds of legality, but it allowed the games to continue.

It allowed the community to continue. And for City of Heroes, the under the radar private server launched in 2019 became an officially licensed private server in 2024, free to play but funded via donations for server costs and the like. The online community was able to rebuild and bring it back to an audience 12 years after it closed, at least officially.

SInce the private server relaunched in 2019, the devs working on the game have added new material, new missions, and new features, showing that an active community can still support a game enough to allow future development. The gaming community may be showing the TikTok community a path forward if the proposed legislation goes through in the United States.

While there are current alternatives to the short form video that TikTok popularized, like Instagram Reels, YouTube Shorts, Clapper, and others, each of those have appealed to a different community and haven’t seen the wholesale move of the TikTok user base. It may happen, as often users will move to a site or page or app or whatever that they find most appealing, but this isn’t always the case.

There may be an opportunity for users to build their own. Tools like loops. video, which is currently in alpha testing at the time of this show’s publication, allow a very similar short video format. built on the ActivityPub protocol that we’ve discussed last episode and several times before. And much like Meta’s threads was built in record time to capture disaffected Twitter users, we may see other options spring up if TikTok is truly banned in the United States.

We’ll keep an eye on this story as it develops, and come back to it in a few months to see what the results are, and where the community goes.

Once again, thank you for joining us on the Implausipod. I’m your host, Dr. Implausible. 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 Creative Commons 4. 0 share alike license. No AI tools were used in the production of this podcast, save for the transcription software, which I believe is just machine learning. 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’s no cost associated with the show, but it does grow through the 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 applausopod.

com, which would 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.

Coming soon on the ImplazaPod, we already have some episodes in the pipeline, though I’m not quite sure of their release order yet. We have a two part discussion on the first season of the Fallout TV series, as well as a recap of the most recent season of Doctor Who. And we’ll be looking at a few other online activities, including the emergence of the dial up pastoral and the commodification of curation.

I hope you join us for them, they’re going to be fantastic. Until then, take care, and have fun.

Bibliography:

Bartle, R. (2003). Designing Virtual Worlds. New Riders Press.

Granovetter, M. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360–1380.

Jenkins, H. (2006). Convergence Culture: Where Old and New Media Collide. NYU Press.

Koster, R. (2004). A theory of fun for game design. Paraglyph Press.

Rheingold, H. (2000). The Virtual Community: Homesteading on the electronic frontier. MIT Press.

Sennett, R. (2012). Together: The rituals, pleasures and politics of cooperation. Yale University Press.

The Matrix Online Videos—Giant Bomb. (2012, July 12). https://web.archive.org/web/20120712062536/http://www.giantbomb.com/the-matrix-online/61-9124/videos/

There Is Another: The End Of Star Wars Galaxies – Part 01 – Giant Bomb. (2012, January 7). https://web.archive.org/web/20120107150559/http://www.giantbomb.com/there-is-another-the-end-of-star-wars-galaxies-part-01/17-5439/

von Hippel, E. (2005). Democratizing Innovation. The MIT Press.

Links:

City of Heroes: Homecoming

Implausipod Episode 16 – Spreadable Media

The Implausi.blog Newsletter

Black Boxes and AI

(this was originally published as Implausipod E0028 on February 26, 2024)

https://www.implausipod.com/1935232/episodes/14575421-e0028-black-boxes-and-ai

How does your technology work? Do you have a deep understanding of the tech, or is it effectively a “black box”? And does this even matter? We do a deep dive into the history of the black box, how it’s understood when it comes to science and technology, and what that means for AI-assisted science.

On January 9th, 2024, rabbit Incorporated introduced their R one, their handheld device that would let you get away from using apps on your phone by connecting them all together through using the power of ai. The handheld device is aimed at consumers and is about half the size of an iPhone, and as the CEO claims, it is the beginning of a new era in human machine interaction.

End quote. By using what they call a large action model, or LAM, it’s supposed to interpret the user’s intention and behavior and allow them to use the apps quicker. It’s acceleration in a box. But what exactly does that box do? When you look at a new tool from the outside, it may seem odd to trust all your actions to something that you barely know how it works.

But let me ask you, can you tell me how anything you own works? Your car, your phone, your laptop, your furnace, your fridge, anything at all. What makes it run? I mean, we might have some grade school ideas from a Richard Scarry book or a past episode of How It’s Made, but But what makes any of those things that we think we know different from an AI device that nobody’s ever seen before?

They’re all effectively black boxes. And we’re going to explore what that means in this episode of the Implosipod.

Welcome to the Implausipod, a podcast about the intersection of art, technology, and popular culture. I’m your host, Dr. Implausible. And in all this discussion of black boxes, you might have already formed a particular mental image. The most common one is probably that of the airline flight recorder, the device that’s embedded in every modern airplane and becomes the subject of a frantic search in case of an accident.

Now, the thing is, they’re no longer black, they’re rather a bright orange, much like the Rabbit R1 that was demoed. But associating black boxes with the flight recorder isn’t that far off, because its origin was tied to that of the airline industry, specifically in World War II, when the massive amount of flights generated a need to find out what was going on with the planes that were flying continual missions across the English Channel.

Following World War II, the use of black boxes Boxes expanded as the industry shifted from military to commercial applications. I mean, the military still used them too. It was useful to find out what was going on with the flights, but that idea that they became embedded within commercial aircraft and were used to test the conditions and find out what happened so they could fix things and make things safer and more reliable overall.

meant that their existence and use became widely known. But, by using them to figure out the cause of accidents and increase the reliability, they were able to increase trust. To the point that air travel was less dangerous than the drive to the airport in your car, and few, if any, passengers had many qualms left about the Safety of the flight.

And while this is the origin of the black box in other areas, it can have a different meaning in fields like science or engineering or systems. Theory can be something complex where it’s just judged by its inputs and outputs. Now that could be anything from as simple as I can. Simple integrated circuit to a guitar pedal to something complex like a computer or your car or furnace or any of those devices we talked about before but it could also be something super complex like an institution or an organization or the human brain or an AI.

I think the best way to describe it is an old New Yorker cartoon that had a couple scientists in front of a blackboard filled with equations and in the middle of it says, Then a miracle occurs. It’s a good joke. Everyone thinks it’s a Far Side cartoon, but it was actually done by Sidney Harris, but The point being that right now in 2024, it looks like that miracle.

It’s called AI.

So how did we get to thinking that AI is a miracle product? I mean, aside from using the LLMs and generative art tools, things like DALL-E and Sora, and seeing the results, well, as we’ve spent the last couple episodes kinda setting up, a lot of this can occur through the mythic representations of it that we often have in pop culture.

And we have lots of choices to choose from. There’s lots of representations of AI in media in the first nearly two and a half decades of the 21st century. We can look at movies like Her from 2013, where the virtual assistant of Joaquin Phoenix becomes a romantic liaison. Or how Tony Stark’s supercomputer Jarvis is represented in the first Iron Man film in 2008.

Or, for a longer, more intimate look, the growth and development of Samaritan through the five seasons of the CBS show Person of Interest from 2011 through 2016. And I’d be remiss if I didn’t mention their granddaddy Hal from 2001 A Space Odyssey by Kubrick in 1968. But I think we’ll have to return to that one a little bit more in next episode.

The point being that we have lots of representations of AI or artificial intelligences that are not ambulatory machines, but are actually just embedded within a box. And this is why I’m mentioning these examples specifically, because they’re more directly relevant to our current AI tools that we have access to.

The way that these ones are presented not only shapes the cultural form of them, but our expected patterns of use. And that shaping of technology is key by treating AI as a black box, something that can take almost anything from us and output something magical. We project a lot of our hopes and fears upon what it might actually be capable of accomplishing.

What we’re seeing with extended use is that the capabilities might be a little bit more limited than originally anticipated. But every time something new gets shown off, like Sora or the rabbit or what have you, then that expectation grows again, and the fears and hopes and dreams return. So because of these different interpretations, we end up effectively putting another black box around the AI technology itself, which to reiterate is still pretty opaque, but it means our interpretation of it is going to be very contextual.

Our interpretation of the technology is going to be very different based on our particular position or our goals, what we’re hoping to do with the technology or what problems we’re looking for it to solve. That’s something we might call interpretive flexibility, and that leads us into another black box, the black box of the social construction of technology, or SCOT.

So SCOT is one of a cluster of theories or models within the field of science and technology studies that aims to have a sociological understanding of technology in this case. Originally presented in 1987 by Wiebe Biejker and Trevor Pinch, a lot of work was being done within the field throughout the 80s, 90s, and early 2000s when I entered grad school.

So, so if you studied technology as I was, you’d have to grapple with Scott and the STS field in general. One of the arguments that Pinch and Biejker were making was that Science and technology were both often treated as black boxes within their field of study. Now, they were drawing on earlier scholarship for this.

One of their key sources was Leighton, who in 1977 wrote, What is needed is an understanding of technology from inside. Both as a body of knowledge and as a social system. Instead, technology is often treated as a black box whose contents and behavior may be assumed to be common knowledge. End quote. So whether the study was the field of science and the science itself was.

irrelevant, it didn’t have to be known, it could just be treated as a black box and the theory applied to whatever particular thing was being studied. Or people studying innovation that had all the interest in the inputs to innovation but had no particular interest or insight into the technology on its own.

So obviously the studies up to 1987 had a bit of a blind spot in what they were looking at. And Pinch and Becker are arguing that it’s more than just the users and producers, but any relevant social group that might be involved with a particular artifact needs to be examined when we’re trying to understand what’s going on.

Now, their arguments about interpretive flexibility in relevant social groups is just another way of saying, this street finds its own uses for things, the quote from William Gibson in But their main point is that even during the early stages, all these technologies have different groups that are using them in different ways, according to their own needs.

Over time, it kind of becomes rationalized. It’s something that they call closure. And that the technology becomes, you know, what we all think of it. We could look at, say, an iPhone, to use one recent example, as being pretty much static now. There’s some small innovations, incremental innovations, that happen on a regular basis.

But, by and large, the smartphone as it stands is kind of closed. It’s just the thing that it is now. And there isn’t a lot of innovation happening there anymore. But, Perhaps I’ve said too much and we’ll get to the iPhone and the details of that at a later date. But the thing is that once the technology becomes closed like that, it returns to being a black box.

It is what we thought it is, you know? And so if you ask somebody what a smartphone is and how does it work, those are kind of irrelevant questions. A smartphone is what a smartphone is, and it doesn’t really matter how the insides work, its product is its output. It’s what it’s used for. Now, this model of a black box with respect to technology isn’t without its critiques.

Six years after its publication, in 1993, the academic Langdon Winner wrote a critique of Scott in the works of Pinch and Biker. It was called Upon Opening the Black Box and Finding it Empty. Now, Langdon Winner is well known for his 1980 article, Do Artifacts Have Politics? And I think that that text in particular is, like, required reading.

So let’s bust that out in a future episode and take a deep dive on it. But in the meantime, the critique that he had with respect to social constructivism is In four main areas. The first one is the consequences. This is from like page 368 of his article. And he says, the problem there is that they’re so focused on what shapes the technology, what brings it into being that they don’t look at anything that happens afterwards, the consequences.

And we can see that with respect to AI, where there’s a lot of work on the development, but now people are actually going, Hey, what are the impacts of this getting introduced large scale throughout our society? So we can see how our own discourse about technology is actually looking at the impacts. And this is something that was kind of missing from the theory.

theoretical point of view back in like 1987. Now I’ll argue that there’s value in understanding how we came up with a particular technology with how it’s formed so that you can see those signs again, when they happen. And one of the challenges whenever you’re studying technology is looking at something that’s incipient or under development and being able to pick the next big one.

Well, what? AI, we’re already past that point. We know it’s going to have a massive impact. The question is what are going to be the consequences of that impact? How big of a crater is that meteorite going to leave? Now for Winner, a second critique is that Scot looks at all the people that are involved in the production of a technology, but not necessarily at the groups that are excluded from that production.

For AI, we can look at the tech giants and the CEOs, the people doing a lot to promote and roll out this technology as well as those companies that are adopting it, but we’re often not seeing the impacts on those who are going to be directly affected by the large scale. introduction of AI into our economy.

We saw it a little bit with the Hollywood Strikes of 2023, but again, those are the high profile cases and not the vast majority of people that will be impacted by the deployment of a new technology. And this feeds right into Scot’s third critique, that Scot focuses on certain social groups but misses the larger impact or even like the dynamics of what’s going on.

How technological change may impact much wider across our, you know, civilization. And by ignoring these larger scale social processes, the deeper, as Langdon Winters says, the deeper cultural, intellectual, or economic regions of social choices about technology, these things remain hidden, they remain obfuscated, they remain part of the black box and closed off.

And this ties directly into Wiener’s fourth critique as well, is that when Scottis looking at particular technology it doesn’t necessarily make a claim about what it all means. Now in some cases that’s fine because it’s happening in the moment, the technology is dynamic and it’s currently under development like what we’re seeing with AI.

But if you’re looking at something historical that’s been going on for decades and decades and decades, like Oh, the black boxes we mentioned at the beginning, the flight recorders that we started the episode with. That’s pretty much a set thing now. And the only question is, you know, when, say, a new accident happens and we have a search for it.

But by and large, that’s a set technology. Can’t we make an evaluative claim about that, what that means for us as a society? I mean, there’s value in an analysis of maintaining some objectivity and distance, but at some point you have to be able to make a claim. Because if you don’t, you may just end up providing some cover by saying that the construction of a given technology is value neutral, which is what that interpretive flexibility is basically saying.

Near the end of the paper, in his critique of another scholar by the name of Stephen Woolgar, Langdon Winner states, Quote, power holders who have technological megaprojects in mind could well find comfort in a vision like that now offered by the social constructivists. Unlike the inquiries of previous generations of critical social thinkers, social constructivism provides no solid systematic standpoint or core of moral concerns from which to criticize or oppose any particular patterns of technical development.

end quote. And to be absolutely clear, the current development of AI tools around the globe are absolutely technological mega projects. We discussed this back in episode 12 when we looked at Nick Bostrom’s work on superintelligence. So as this global race to develop AI or AGI is taking place, it would serve us well to have a theory of technology that allows us to provide some critique.

Now that Steve Woolgar guy that Winder was critiquing had a writing partner back in the seventies, and they started looking at science from an anthropological perspective in their study of laboratory life. And he wrote that with Bruno Latour. And Bruno Latour was working with another set of theorists who studied technology as a black box and that was called Actor Network Theory.

And that had a couple key components that might help us out. Now, the other people involved were like John Law and Michel Callon, and I think we might have mentioned both of them before. But one of the basic things about actor network theory is that it looks at things involved in a given technology symmetrically.

That means it doesn’t matter whether it’s an artifact, or a creature, or a set of documents, or a person, they’re all actors, and they can be looked at through the actions that they have. Latour calls it a sociology of translation. It’s more about the relationships between the various elements within the network rather than the attributes of any one given thing.

So it’s the study of power relationships between various types of things. It’s what Nick Bostrom would call a flat ontology, but I know as I’m saying those words out loud I’m probably losing, you know, listeners by the droves here. So we’ll just keep it simple and state that a person using a tool is going to have normative expectancy.

About how it works. Like they’re gonna have some basic assumptions, right? If you grab a hammer, it’s gonna have a handle and a head and, and depending on its size or its shape or material, it might, you know, determine its use. It might also have some affordances that suggest how it could be used, but generally that assemblage, that conjunction of the hammer and the user.

I don’t know, we’ll call him Hammer Guy, is going to be different than a guy without a hammer, right? We’re going to say, hey, Hammer Guy, put some nails in that board there, put that thing together, rather than, you know, please hammer, don’t hurt him, or whatever. All right, I might be recording this too late at night, but the point being is that people with tools will have expectations about how they get used, and some of that goes into how those tools are constructed, and that can be shaped by the construction of the technology, but it can also be shaped by our relation to that technology.

And that’s what we’re seeing with AI, as we argued way back in episode 12 that, you know, AI is a assistive technology. It does allow for us to do certain things and extends our reach in certain areas. But here’s the problem. Generally, we can see what kind of condition the hammer’s in. And we can have a good idea of how it’s going to work for us, right?

But we can’t say that with AI. We can maybe trust the hammer or the tools that we become accustomed to using through practice and trial and error. But AI is both too new and too opaque. The black box is too dark that we really don’t know what’s going on. And while we might put in inputs, we can’t trust the output.

And that brings us to the last part of our story.

In the previous section, the authors that we were mentioning, Latour and Woolgar, like winner pitch biker, are key figures, not just in the study of technology, but also in the philosophy of science. Latour and Woolgar’s Laboratory Life from 1977 is a key text and it really sent shockwaves through the whole study of science and is a foundational text within that field.

And part of that is recognizing. Even from a cursory glance, once you start looking at science from a anthropological point of view, is the unique relationship that scientists have with their instruments. And the author Inkeri Koskinen sums up a lot of this in an article from 2023, and they termed the relationship that scientists have with their tools the necessary trust view.

Trust is necessary because collective knowledge production is characterized by relationships of epistemic dependence. Not everything scientists do can be double checked. Scientific collaborations are in practice possible only if its members accept it. Teach other’s contributions without such checks.

Not only does a scientist have to rely on the skills of their colleagues, but they must also trust that the colleagues are honest and will not betray them. For instance, by intentionally or recklessly breaching the standards of practices accepted in the field or by plagiarizing them or someone else.

End quote. And we could probably all think of examples where this relationship of trust is breached, but. The point being is that science, as it normally operates, relies on relative levels of trust between the actors that are involved, in this case scientists and their tools as well. And that’s embedded in the practice throughout science, that idea of peer review of, or of reproducibility or verifiability.

It’s part of the whole process. But the challenge is, especially for large projects, you can’t know how everything works. So you’re dependent in some way that the material or products or tools that you’re using has been verified or checked by at least somebody else that you have that trust with. And this trust is the same that a mountain climber might have in their tools or an airline pilot might have in their instruments.

You know, trust, but verify, because your life might depend on it. And that brings us all the way around to our black boxes that we started the discussion with. Now, scientists lives might not depend on that trust the same way that it would with airline pilots and mountain climbers, but, you know, if they’re working with dangerous materials, it absolutely does, because, you know, chemicals being what they are, we’ve all seen some Mythbusters episodes where things go foosh rather rapidly.

But for most scientists, what Koskinen notes that this trust in their instruments is really kind of a quasi trust, in that they have normative expectations about how the tools they use are going to function. And moreover, this quasi trust is based on rational expectations. They’re rationally grounded.

And this brings us back full circle. How does your AI work? Can you trust it? Is that trust rationally grounded? Now, this has been an ongoing issue in the study of science for a while now, as computer simulations and related tools have been a bigger, bigger part of the way science is conducted, especially in certain disciplines.

Now, Humphrey’s argument is that, quote, computational processes have already become so fast and complex that it was beyond our human cognitive capabilities to understand their details. Basically, computational intensive science is more reliant on the tools than ever before. And those tools are What he calls epistemically opaque.

That means it’s impossible to know all the elements of the process that go into the knowledge production. So this is becoming a challenge for the way science is conducted. And this goes way before the release of ChatGPT. Much of the research that Koskinen is quoting comes from the 20 teens. Research that’s heavily reliant on machine learning or on, say, automatic image classifiers, fields like astronomy or biology, have been finding challenges in the use of these tools.

Now, some are arguing that even though those tools are opaque, they’re black boxed, they can be relied on, and they’re used justified because we can work on the processes surrounding them. They can be tested, verified, and validated, and thus a chain of reliability can be established. This is something that some authors call computational reliabilism, which is a bit of a mouthful for me to say, but it’s basically saying that the use of the tools is grounded through validation.

Basically, it’s performing within acceptable boundaries for whatever that field is. And this gets the idea of thinking of the scientist as not just the person themselves, but also their tools. So they’re an extended agent, the same as, you know, the dude with the hammer that we discussed earlier. Or chainsaw man.

You can think about how they’re one and the same. One of the challenges there is that When a scientist is familiar with the tool, they might not be checking it constantly, you know, so again, it might start pushing out some weird results. So it’s hard to reconcile that trust we have in the combined scientist using AI.

They become, effectively, a black box. And this issue is by no means resolved. It’s still early days, and it’s changing constantly. Weekly, it seems, sometimes. And to show what some of the impacts of AI might be, I’ll take you to a 1998 paper by Martin Weitzman. Now, this is in economics, but it’s a paper that’s titled Recombinant Growth.

And this isn’t the last paper in my database that mentions black boxes, but it is one of them. What Weitzman is arguing is that when we’re looking at innovation, R& D, or Knowledge production is often treated as a black box. And if we look at how new ideas are generated, one of those is through the combination of various elements that are already existing.

If AI tools can take a much larger set of existing knowledge, far more than any one person, or even teams of people can bring together at any one point in time and put those together in new ways. then the ability to come up with new ideas far exceeds that that exists today. This directly challenges a lot of the current arguments going on, on AI and creativity, and that those arguments completely miss the point of what creativity is and how it operates.

Weitzman states that new ideas arise out of existing ideas and some kind of cumulative interactive process. And we know that there’s a lot of stuff out there that we’ve never tried before. So the field of possibilities is exceedingly vast. And the future of AI assisted science could potentially lead to some fantastic discoveries.

But we’re going to need to come to terms with how we relate to the black box of scientist and AI tool. And when it comes to AI, our relationship to our tools has not always been cordial. In our imagination, from everything from Terminator to The Matrix to Dune, it always seems to come down to violence.

So in our next episode, we’re going to look into that, into why it always comes down to a Butlerian Jihad.

Once again, thanks for joining us here on the Implausipod. I’m your host, Dr. Implausible, and the research and editing, mixing, and writing has been by me. If you have any questions, comments, or there’s elements you’d like us to go into additional detail on, please feel free to contact the show at drimplausible at implausipod dot com. And if you made it this far, you’re awesome. Thank you. A brief request. There’s no advertisement, no cost for this show. but it only grows through word of mouth. So, if you like this show, share it with a friend, or mention it elsewhere on social media. We’d appreciate that so much. Until next time, it’s been fantastic.

Take care, have fun.

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