California Forever or, the Aesthetics of AI images

An image distributed by California Forever

This past August (2023), a new urban project called “California Forever” was announced, promising a walkable city for 400,000 in Solano County, not far from the Bay area. Critics soon pointed out several flaws in the renderings the company distributed. First, even though the venture was backed by billionaire Silicon Valley investors such as Laurene Powell Jobs (Steve Jobs’s widow), Reid Hoffman (LinkedIn co-founder), Michael Mortiz (former partner at Sequoia Capital), and Marc Andreesen (author of Mosaic and Netscape co-founder), the project looked profoundly retardataire. Instead of a high-tech city next to the world’s tech capital, the renderings depict a new urbanist fantasy with American flags and children on old-fashioned bicycles. Where has our imagination gone? How is it that Archigram’s fifty-five-year-old Instant City still looks fresher than this recycled Americana? Neom and the Line are terrible, but at least they show an interest in doing something new.

The founders are your typically older tech investors: their imaginative days are long behind them and, having been glued to computer screens their entire lives, it’s hard to imagine they have many original thoughts left. A drive around Silicon Valley is enough to show the banality of the tech industry’s vision. Some of them may have read Christopher Alexander’s A Pattern Language, which has had a large influence in software development and thus become interested in the New Urbanist movement his writing spawned. There are no architects listed among the team, although a planner who was involved in Culdesac Tempe, a moderately interesting, if boring, car-free development is involved. The rendering indicates a “contextual” approach derivative of San Francisco, with a variety of windows and townhouse shapes to break up the massing since somebody told them to do that. The architecture is barely there, its utter banality indicating how little it matters. The end result will likely be even more disappointing. But I am more interested in the problems with the rendering that other critics, such as the San Francisco Chronicle’s Chase DiFeliciantonio observed about the renderings: “A girl pedaling a bicycle with a missing foot. An asymmetrical airplane. An impossible ladder.” (link). The renderings, as the California Forever team eventually admitted, were made with an Artificial Intelligence image generator, apparently Midjourney.

More than one friend asked me to weigh in as I have been working with Midjourney and other AI image generators for some time now, exploring a critical approach to AI image generation, investigating the properties and problematics of the medium itself. If California Forever is so backwards-looking, why are images created by image generators also so banal? Hot women (lots and lots of hot women), fan service art, gaudy hyperrealistic landscapes, cringe anime, and bad cartoons are the order of the day (for examples, check out the feed for the Midjourney gallery). Why this junkscape of imagery? Why is AI imagery not more worthy of our future? Why is it that so much of what is commonly called AI “art” is kitsch? 

In part this is because users of AI image generators fancy themselves as artists even though few of them have any art training. This is common in photography. Wealthy individuals purchase camera gear based on reviews claiming that some camera or lens has greater technical abilities to reproduce reality faithfully and then apply complicated methods to assure that their photographs demonstrate technical proficiency. High Dynamic Range (HDR) photography is the leading example of this. Popular with amateurs with no aesthetic training, HDR is an attempt to capture a scene in which the range of luminance exceeds the dynamic range of the camera sensor, and often even the human eye itself. The results typically have too much detail in the shadows, dark skies, unnatural colors, the hyperrealistic effect of an acid trip. 

Not an HDR photograph but rather a simulation of an HDR photograph, as made in Midjourney.

These sorts of photographers, along with individuals who produce digital illustrations for consumption on platforms like Artstation and DeviantArt, 3D printing enthusiasts, makers, indie musicians working with samplers and synthesizers, vloggers creating content for YouTube, gamers streaming on Twitch and YouTube, and fashion enthusiasts showcasing their work on social media are “prosumers,” a term coined by futurist Alvin Toffler in his 1980 book The Third Wave. Toffler’s “prosumer” merges the roles of producer and consumer, suggesting a shift in the economy and society. In this model, individuals are not only consumers of products and services but also take on an active role in their production. This concept was revolutionary at the time, predicting the rise of customization, personalization, and participatory culture facilitated by technological advancements, particularly in digital technology and the Internet.

At the same time, prosumers largely create kitsch, characterized by an appeal to popular tastes and a frequently derivative nature. Kitsch thrives in environments where production is geared towards mass appeal and immediate consumption rather than nuanced artistic merit or innovation. For traditional modernist critics, such as Clement Greenberg, kitsch represented the antithesis of genuine culture and the avant-garde. Kitsch, Greenberg explained in his seminal 1939 essay “Avant Garde and Kitsch,” is produced by industrialization, designed to satisfy the tastes of the least discerning audience without intellectual or emotional challenges. Greenberg associated kitsch with the replication of traditional art forms and aesthetics, but emptied of genuine meaning or complexity, offering immediate gratification rather than enduring value or depth. Greenberg:

The peasants who settled in the cities as proletariat and petty bourgeois learned to read and write for the sake of efficiency, but they did not win the leisure and comfort necessary for the enjoyment of the city’s traditional culture. Losing, nevertheless, their taste for the folk culture whose background was the countryside, and discovering a new capacity for boredom at the same time, the new urban masses set up a pressure on society to provide them with a kind of culture fit for their own consumption. To fill the demand of the new market, a new commodity was devised: ersatz culture, kitsch, destined for those who, insensible to the values of genuine culture, are hungry nevertheless for the diversion that only culture of some sort can provide.

Kitsch, using for raw material the debased and academicized simulacra of genuine culture, welcomes and cultivates this insensibility. It is the source of its profits. Kitsch is mechanical and operates by formulas. Kitsch is vicarious experience and faked sensations. Kitsch changes according to style, but remains always the same. Kitsch is the epitome of all that is spurious in the life of our times. Kitsch pretends to demand nothing of its customers except their money-not even their time.

Clement Greenberg, “Avant-Garde and Kitsch,” 1939

With the rise of postmodernism, however, both artists and critics revalued the role of mass culture. Initially, this was done with the knowing wink that reinterpreted kitsch as camp. By bracketing the degraded, Andy Warhol, Roy Lichtenstein, Philip Johnson, Stanley Tigerman, Robert Venturi and Denise Scott Brown, the Harry Who, followed by John Waters and David Lynch, Jeff Koons and Pierre et Giles were among the many artists who ironically reframed kitsch into art. In her 1964 essay “Notes on ‘Camp’,” later published in the book Against Interpretation, and other Essays, Susan Sontag flipped the valence on kitsch, valorizing camp as an aesthetic sensibility that found beauty in artifice, exaggeration, and theatricality. Camp, for Sontag, is the love of the unnatural: of artifice and exaggeration. It is a mode of enjoyment, of appreciation—not judgment. Camp is the good taste of bad taste, a celebration of the extravagant and the absurd, but with a nuanced affection that discerns quality within the ostensibly tasteless. Sontag nevertheless contrasted camp with kitsch, which she viewed less favorably. Kitsch, for Sontag, is associated with mass-produced art or objects that lack sophistication and are designed to appeal to popular or uncritical taste. The critical difference, as Sontag and others have implied, lies in the intentionality and reception: camp involves a conscious, nuanced embrace of excess and irony, whereas kitsch is earnest, unironic, and often pandering to sentimental or lowbrow tastes.

In 1983, theorist Frederic Jameson concluded that the thorough permeation of culture by capital—and vice versa once the techniques of the avant-garde were embraced by commercial art—meant the end of a distinction between mass culture and art, thus producing postmodernism. Indeed, by the 1980s, the distinction between camp and kitsch had been thoroughly blurred. If John Waters was camp, were the B-52s? If Adam Ant and Boy George were camp, were Van Halen and Bon Jovi? If the cover of Sgt. Pepper’s Lonely Hearts Club Band was a masterpiece of camp, what about the cloying song “Wonderful Christmastime” by ex-Beatle Paul McCartney? Perhaps the ultimate end of any distinction between camp and kitsch came in John Chase’s brilliant 1982 Exterior Decoration: Hollywood’s Inside-Out Houses in which Chase explored the unique architectural vernacular of West Hollywood’s do-it-yourself remodels, transformations that turned ordinary stucco bungalows into distinctive visual statements, often utilizing historicizing elements traditionally found indoors on the exterior of these remodels. Adding to this is the rise of the art museum store, which in the 1980s transformed from a bookstore selling scholarly books as well as an odd postcard and reproduction to include a wider range of items, such as jewelry, toys, and even furniture inspired by the museum’s collection and exhibits by commercially popular (and generally kitsch) artists like Yayoi Kusama, Kaws, Banksy, Damien Hirst, Jeff Koons, Keith Haring, and Shepard Fairey. Seeing the museum store as a crucial source of revenue, museums now regularly think about the tie-ins between exhibitions and “merch.”

In a recent (paywalled so don’t bother to look for it unless you want to pay $30) essay, “Digital Kitsch: Art and Kitsch in the Informational Milieu,” Domenico Quaranta discusses the emergence of “digital kitsch,” which he calls “the default mode for all creative endeavors with digital media.” This is a provocative position, but he leaves it undertheorized. There is little question that the vast majority of cultural production today is kitsch—just as it was in the nineteenth or twentieth century—but that does not mean that it is the default mode or that somehow digital tools produce nothing but kitsch. Now the artists of the Net.Art movement, as promoted on Rhizome.org and various mailing lists since the 1990s, not only embraced kitsch, they saw its manipulation as their primary concern. But this is a typical case of mistaking what is being heavily promoted by the art market for what is worth looking at. There are few writers, photographers, or musicians who do not employ digital media in some way today, but that does not automatically make them kitsch. I don’t see William Basinski, Katie Paterson, Paul Prudence, or Guy Dickinson—to name only a few artists whose work I admire—as kitsch, even though they work with digital media or have web sites (Paterson, does, on occasion purposefully engage with kitsch, but certainly not in most works). Moreover, to somehow suggest this is a digital trend is reductive: painting or classical music are more likely than not to be kitsch today, as those art forms have largely exhausted themselves, subject to endless, academicized retreads.

One can certainly still produce works of sophistication and effort today, but it does require effort. If one abandons the Hegelian exploration of art’s proper object, embraces politics as the sole cause of art, or turns to the academician’s fatal poison, the knowing disdain of snark, it can be virtually impossible. Blindly searching for the new is a long-dead end as well. Architect Eric Moss, endlessly repeated Ezra Pound’s dictum “make it new” (none of us think he knew who Pound was, let alone that this was his phrase), but that did not elevate his work above kitsch. Instead, as I detail in my essay “On Art and the Universal,”

[A Greenbergian] revival, however, should begin with a call for art to investigate itself again, not merely play to political activism for the sake of theater. The task at hand is to discern the proper object of knowledge for art, a fulcrum upon which we can rest our research. Or, if not the proper object, a proper object that would be suitable for investigation and productive of knowledge. 

In that essay, I suggest that a serious proper object for AI art would be to explore the intertextuality of all artwork, using it to access the collective cultural subconscious. But this is not what AI image generators are designed for. On the contrary, the engineers programming AI image generators know that, generally speaking, they do not need to engage with art history, but rather with the imagery commonly found on the Internet, imagery that is “scraped” to create training data for AI image generators.

Writer Andy Baio investigated (see here) the training data for AI image generator Stable Diffusion, data composed of sets of English-captioned images from the nonprofit Large-scale Artificial Intelligence Open Network (LAION), particularly a set of images called LAION-Aesthetics, which in turn were subsets of images from the massive LAION datasets created by what LAION calls “lightweight [AI] models” that “predict the rating people gave when they were asked ‘How much do you like this image on a scale from 1 to 10?‘” (see here). These subsets were then used for fine-tuning of AI image generators. Academics have droned on, as they will, about AI image generators’ biases toward producing stereotypically beautiful young white or Asian women. Of course such biases exist, just as Internet searches are biased toward the United States. We live in a global monoculture, there is nothing good about it and I don’t endorse such biases, but there is also no revelation here, this is a lazy analysis pandering to political positions held by individuals of simple minds, an observation about as instructive as suggesting that poor people are disadvantaged in society. Training data reflects society and all its flaws. Just this past week, we saw what an utter catastrophe training AI image generators to artificially incorporate diversity in their results, what Zvi Mowshowitz calls the “Gemini Incident,” with black Nazis, female NFL quarterbacks, and Asian viking warriors (this is not really that new, ChatGPT’s Dall-E3 does the same sort of tuning, albeit slightly less egregiously as this dump of the initial prompt—which I have independently verified—shows). What is deeply weird, however, is that AIs are being trained to produce images based on a selection of images chosen not by humans but by AI judges that predict which images humans will judge as aesthetically superior. It’s the return of Komar and Melamid, as robots.

A large number of the illustrations in these image generators seem to be digital in origin, belying a clear preference for work produced for consumption on the Net. Baio analyzed some 12 million images in the LAION-Aesthetics v2 6+ model. His conclusion is worth quoting at length instead of paraphrasing or summarizing:

Nearly half of the images, about 47%, were sourced from only 100 domains, with the largest number of images coming from Pinterest. Over a million images, or 8.5% of the total dataset, are scraped from Pinterest’s pinimg.com CDN.

User-generated content platforms were a huge source for the image data. WordPress-hosted blogs on wp.com and wordpress.com represented 819k images together, or 6.8% of all images. Other photo, art, and blogging sites included 232k images from Smugmug, 146k from Blogspot, 121k images were from Flickr, 67k images from DeviantArt, 74k from Wikimedia, 48k from 500px, and 28k from Tumblr.

Shopping sites were well-represented. The second-biggest domain was Fine Art America [editor’s note: nothing on that site qualifies as fine art], which sells art prints and posters, with 698k images (5.8%) in the dataset. 244k images came from Shopify, 189k each from Wix and Squarespace, 90k from Redbubble, and just over 47k from Etsy.

Unsurprisingly, a large number came from stock image sites [editor’s note: virtually nothing on these sites qualifies as fine art]. 123RF was the biggest with 497k, 171k images came from Adobe Stock’s CDN at ftcdn.net, 117k from PhotoShelter, 35k images from Dreamstime, 23k from iStockPhoto, 22k from Depositphotos, 22k from Unsplash, 15k from Getty Images, 10k from VectorStock, and 10k from Shutterstock, among many others.

It’s worth noting, however, that domains alone may not represent the actual sources of these images. For instance, there are only 6,292 images sourced from Artstation.com’s domain, but another 2,740 images with “artstation” in the caption text hosted by sites like Pinterest.

Andy Baio, “Exploring 12 Million of the 2.3 Billion Images Used to Train Stable Diffusion’s Image Generator“, https://waxy.org/2022/08/exploring-12-million-of-the-images-used-to-train-stable-diffusions-image-generator/

Subject matter aside, certain aesthetic qualities emerge from these sources—qualities that both the robots choosing the training sets and the engineers tuning them seem to share. First, there is hyperrealism. To succeed, engineers creating image generators need to engage the prosumer market, constantly announcing better resolution, faster processing times, and greater “realism.” But realism, as we have learned from Roland Barthes, is always coded. In the case of AI image generation, realism is coded by existing visual regimes, but these are less art historical, more technical and related to the mass imagery found on the Internet. A certain aspect of this recalls the photorealistic rendered “graphics demo” images from the 1960s to the 1990s as well as graphically sophisticated first-person video games from the 2000s and 2010s. At the time, these were evaluated by their technical proficiency with complicated graphical techniques, such as rendering reflections on curved surfaces or complicated, multi-source lighting effects and success with these critirea still codes as realistic. Second, there is the legacy of hyperrealistic “photorealism” as interpreted by HDR photographers described above. Being popular, HDR is judged as high quality by the models, so it is promoted in data sets. Finally, there is a clear bias toward prosumer art, in particular the fantasy “concept art” found on the net, anime, and the fandom graphics found on sites such as Deviantart.

But there are also other, formal qualities that initially may be harder to pin down, most notably a certain distinct use of luminosity. Thus, a prompt for “Emma Watson (a commonly used test of how realistic an image generator was in 2022, used as such because of some clear preference for Emma Watson in either the data set or the fine-tuning of the AIs)” does not present the actress in a photograph, but rather creates an illustration of the sort that a skilled digital artist would produce with a program such as Procreate.

“Emma Watson, Cannabis Goddess,” image created by Midjourney version 6
(oddly earlier versions of Midjourney produce images that more closely resemble Emma Watson).

With the spread of AI image generators, it also became common to add certain modifiers to the end of prompts to create “better” AI images. Individuals claiming to be successful prompt engineers would write articles like “The Ultimate Midjourney Cheat Sheet,” promising “to provide you with a comprehensive guide on leveraging Midjourney prompts to create stunning visuals effortlessly.” Such guides reported that modifiers such as “32-bit,” “HDR,” and “8K” produced excellent results, or rather, visual cocaine, oversharpened, highly-saturated images, much like the demo or “vivid” settings on HDR televisions that are intended to seduce consumers in electronics stores, not to deliver accurate images. Other modifiers such as “cinematic,” “stunning,” “shot on medium format,” and “masterpiece” were intended to somehow coax AIs into producing better quality. Famously, “style of Greg Rutkowksi” seemed to be appended to nearly every image prompt in mid-2022. Exactly what it did was unclear, but somehow suggesting that the output should be like that of a commercial fantasy artist was seen as a good thing.

But the over-use of luminosity is the most curious one. Why is Emma Watson facing the sunrise or sunset? The only commonly-used modifier I can think of in AI production would be “golden hour,” referring to the warm light found right after sunrise and right before sunset that articles tell amateur photographers are when the best images can be taken. So where might the sense of luminosity come from? Baio’s article confirmed an intuition I had had earlier: the number one artist in the sample of LAION-Aesthetics that he examined is Thomas Kinkade, the painter of light. Kinkade is certainly among the most well-known artists in the country, producing kitsch, expressly commercial art made for a mass market.

Not a Thomas Kinkade, but rather a Midjourney simulation of one.

A Northern California native, growing up in Placerville, some 180 miles from Silicon Valley, Kinkade studied art at the University of California, Berkeley and the Art Center College of Design in Pasadena. After a brief time working in the film industry, he became a born-again Christian and set off to paint landscapes consisting of backward-looking subject matter intended to be evocative of a peaceful life, a traditional cottage or house in an idealized American scene often featuring bucolic gardens, streams, stone cottages, lighthouses, or the main street in a small town. Strangely, people are either absent from Kinkade’s paintings or, on the occassion when they are present, are isolated passersby, seemingly disconnected from each other, fitting more of Edward Hopper than, say Gustave Callebotte. It’s as if his scenes happen in another reality, perhaps the afterlife.

In an essay on Kinkade’s work titled “God in the Retails,” Seth Feman cites Kinkade’s statement that he was influenced by the representation of divine power and majesty in Thomas Cole and Frederick Church’s landscape paintings. Just as Cole and Church were concerned about the effects of rapid industrialization, Kinkade sought to create images of an increasingly secularizing and technologizing world, expressly rejecting abstract art, which he saw as morally corrupt (“On one side there’s Jackson Pollock, and way over on the other side there’s the Columbine shooting. And I know there’s a connection between them. I don’t know how, but I know it’s there.” See Christina Waters, Selling the Painter of Light, Metro Santa Cruz, October 16, 2001, Alternet, for more)

In 1989, Kinkade and investor Ken Raasch founded a company that first had the evangelical-sounding name Lightpost Publishing but eventually became known by the tech-sounding name Media Arts Group, based in the Silicon Valley town of Morgan Hill. In 1995, Media Arts Group became publically traded. Licensing deals with companies such as La-Z-Boy and Avon followed. Kinkade produced paintings that would then be reprinted at various price tiers, from lithographs to reproductions on canvas “created with a textured brushstroke process that recreates the artist’s actual brushwork,” the highest of which “finished in oil by a master highlighter who inscribes an original and identifying remarque on the back of the canvas under the artist’s close supervision.” Signatures varied from none to “auto pen in part to protect the signature with newly available DNA encoded ink” to an actual signature (these quotes are from this detailed page on Kinkade’s editions). Media Arts Group set up a vast network of galleries, many of which would be located in shopping malls, with some 350 franchise locations in the United States and 4,500 independently owned galleries worldwide (see these two links at the Guardian and the Morgan Hill Times) along with distribution over channels such as QVC.

Kinkade, according to Seth Feman, who wrote the best essay that I’ve read on the artist to date, “God in the Retails,” in Alexis L. Boylan, ed, Thomas Kinkade, The Artist in the Mall (Duke University Press, 2011), “hopes that the uplifting experience of transitioning into the work and then approaching the light will replicate the stirring experience of his religious conversion—the sole requirement for salvation according to most evangelical theology.” (85). But beyond viewing the art, Feman explains, Kinkade believed that purchasing his art was what one of his followers called “just consumerism.” (94) In other words, Kinkade saw the consumption of his art as a religiously meaningful way to transcend the difficulties of modern life, including consumerism (much as a Marxist professor might buy a Rage Against the Machine LP). Feman calls this “Market Piety,” in which Christian orthodoxy comes together with capitalist ideology (92). Kinkade and his sales team would frequently speak about his own success, touting that he was “the most successful living artist in the world,” “the most award-winning artist in the past 25 years,” or “the most-collected artist in America.” This aligns with the idea of the Prosperity Gospel, a religious belief within some Christian communities that financial blessing and physical well-being are always the will of God for them, and that faith, positive speech, and donations to religious causes will increase one’s material wealth. It views the Bible as a contract between God and humans: if humans have faith in God, the faith goes, God will deliver security and prosperity. Pastors such as Joel Osteen suggest that God awards wealth to the deserving, thus even if he may appear to liberals to be corrupt and unethical, Donald Trump’s wealth demonstrates that he is indeed divinely blessed (for more, see here). By purchasing Kinkade’s artwork, consumers are participating in a form of religious expression that aligns with the Prosperity Gospel’s emphasis on material wealth as a sign of divine favor. The act of buying and owning a Kinkade piece is as a positive declaration of faith, a way to draw health, wealth, and happiness into one’s life, which is a central tenet of the Prosperity Gospel.

Glowing highlights in Kinkade’s works illustrate this conflation of the domestic and the divine. Building interiors lit from within are possessed of an almost surreal sense of comfort and homeliness as dramatic light rakes the landscape. Feman:

In particular, Kinkade draws on the vivifying light used in nineteenth-century landscapes, replicating it in his own work as a metaphor for God’s salvific omnipresence. While the warm sun burning off the fog that blankets the valley in Havencrest Cottage taps into the religious meaning of light developed by earlier artists, it also builds a visual vocabulary to explain the personal awakening that lifted Kinkade out of his dark days and into a Christian life.

Seth Feman, “God in the Retails,” Alexis L. Boylan, ed, Thomas Kinkade, The Artist in the Mall (Duke University Press, 2011), 84.

I don’t doubt that Kinkade’s influence on AI image generation is largely due to his popularity. But just as Kinkade’s divinely inspired luminosity reverberates in AI images, so does the Evangelical rhetoric of immanent Rapture and the Second Coming of the Divine. AI advocates, particularly, the subgroup known as the Effective Accelerationism movement or E/Acc argue that accelerating technological progress is essential. For some of its proponents, such as “Based Beff Jezos,” the pseudonym of engineer Guillaume Verdon, advancing artificial intelligence is the ultimate end-goal of our existence—even if humanity is wiped out in the process. Verdon’s position is no outlier. As Meghan O’Gieblyn describes in God, Human, Animal, Machine: Technology, Metaphor, and the Search for Meaning, the origins of the discourse around the technological Singularity is not in technological discourse or even science fiction but rather in the rhetoric of Christian eschatology.

So if we return to California Forever, we might do well to understand the backwards-looking nature of this techno-utopia not so much as a project for a physical city but as an image of a contemporary Augustinian City of God, rendered by an AI in the digital glow of Thomas Kinkade’s pastoral light. This project, entwined with the aesthetics of digital kitsch and the eschatological promise of AI, becomes a metaphor for the broader discourse surrounding artificial general intelligence (AGI) and the technological singularity. The vision encapsulated by California Forever, while aiming for Utopia, mirrors the inherent tensions within the aesthetics of AI—between the pursuit of a transcendent future and the gravitational pull of nostalgic, kitsch imagery that dominates the collective unconscious in the era of Trump.

The E/Acc movement, with its embrace of technological acceleration towards the singularity, adds another layer to this paradox. It posits that through accelerating technological progress, we might reach a new form of existence or consciousness, yet the imagery and aesthetics that predominate in representations of future cities and technologies often hark back to a bygone era, suggesting a deep-seated ambivalence about the future we’re creating. This dichotomy raises critical questions about the role of art and aesthetics in shaping our visions of the future. Are we, consciously or unconsciously, seeking comfort in the familiar as we stand on the brink of the unknown? And how does this tension affect our ability to truly envision and prepare for the profound changes that AGI and the singularity might bring?

As we navigate the path towards AGI and confront the possibility of the singularity, it is crucial to critically examine the visions of the future we are creating—both in the physical spaces of our cities and in the digital landscapes generated by AI. If artists and thinkers have ceded the discourse around AI image generators to reactionary forces, they have only their own reactionary fear of engaging with technology and their own nostalgia for outdated forms of Marxist-influenced thought to blame. We need to shape the future, not just throw rotting vegetables that fail to miss their target at it. Instead, confronting the paradoxes and tensions within AI art head-on may enable us to shape a future that is both technologically advanced and culturally rich, that investigates the proper object of these technologies and not merely serves as the apotheosis of kitsch.

2023 in review

Another year, another year in review.

Where do we start with our 2023 year in review, now delayed into the second month of 2024? In the Well State of the World 2024, Bruce Sterling states that in 2023 things were boring: there wasn’t much new out there, only a state of polycrisis (this is easier to find in this YouTube interview than in the long thread on the Well, which I’m afraid I gave up on earlier than usual this year). But boredom is tiresome. So is polycrisis. When hasn’t there been a polycrisis? Spring 1914? Of course, there is a polycrisis, there always is. And, what of the rest of 2023, which Sterling dismissed as boring?

2023 is another 1993, a sleeper year in which “60 Minutes” was the top TV show and Nirvana’s “In Utero” was the most popular album in “grunge,” a heavily capitalized genre that those of us who followed the NY noise scene thought extinguished the vitality of experimentation in underground music; Bill Clinton was inaugurated; the world was gripped by a bad recession in a host of bad recessions since the late 1960s; the Afghan Civil War and Bosnian War dragged on; Nigeria had a coup d’état; there was the 55-Day War between the IDF and Hezbollah; there was conflict in Abkhazia; and there was the Waco Siege. It was a year of both polycrisis and soul-crushing boredom, and for most people everything had come to an end, time was in a standstill. But it was also a year in which I saw the future: I was still working on my history of architecture dissertation at Cornell, while my wife worked at the Cornell Theory Center, which was not a center for Derridean scholars, but rather a supercomputing research facility, and one of her colleagues showed me the World Wide Web running on a NeXT computer. In January 1993, the first “alpha/beta” version of NCSA-Mosaic was released for the Mac. I immediately knew the world would change forever.

2023 is the same. A sleeper year with the same old polycrisis and the same old boring surface cultural junk. But it’s also the second year of the AI era and the first year in which AI has become part of everyday life. From a technological viewpoint, 2023 has been the most transformative year of my life. This year in review is falling behind and, in an effort to get it out there and return to the queue of posts for both the regular blog and the Florilegium, I’m going to focus on this transformation and only give a surface treatment of the other parts of 2023.

In particular, I am referring to AI. Other things simply matter a lot less. COVID has settled into an endemic stage. People are still freaking out about it, but some people will freak out about it forever. Unless severely immunocompromized, I don’t see why. We can’t just throw away everything we knew about medicine to retreat into the dark ages for no reason and living in fear of infections is, in itself, dangerous. Geopolitics, which I addressed last year, hasn’t really changed much. Ukraine is still a stalemate, for all the noise, the unrest in the Middle East is absolutely nothing new, and China has flailed and backed down as much as it has flexed its muscles. If I catch a scent of anything new in the geopolitical realm, it’s a growing resignation that more areas of the world will be marked off as failure zones in the Gibsonian Jackpot: Palestine, Yemen, Israel, Iraq, Syria, but also Israel and Ukraine are increasingly looking to written off as territories riven by perpetual unrest. Endless wars that nobody really wants to solve may increasingly be the rule in such places. Still, I don’t see the Jackpot as being quite the apocalypse that many of Gibson’s more literal-minded followers believe. Gibson has been a remarkably poor prophet of the future, after all. The Jackpot, as I see it, will be mainly driven by decline in population in most places throughout the world, a pace that will only increase with the rise of AI. It’s certainly not going to be Terminator. That’s just bad science fiction.

Another Gibsonian adage (which he may never have said) that “the future is already here—it’s just not very evenly distributed,” applies here. For those of us who are working with GPT-4 or Microsoft Copilot Pro, this is a very different year. Obviously, not everyone can pay for—or wants to pay for—the transformative glimpse of AI that one gets with two users subscribing to OpenAI’s ChatGPT (presently GPT-4) Teams plan ($30 a month or prepaid at $600 a year) or Copilot Pro ($30 a month subscription). But this isn’t the same as a ride to the ISS on Dragon-2. On the contrary, this is about the amount that most people in the developed world pay for streaming TV services and far less than they typically spend on Internet and mobile service. When people pay that much for entertainment, paying such a small amount for a service that makes one much more productive is a minor expense. Of course, ChatGPT is banned or unavailable in a rogue’s nest of countries: Russia, China, North Korea, Cuba, Iran, Syria, and Italy (Marinetti weeps in his grave). But many people, including friends, underestimate the importance of these AI services, believing that hallucinations make AI unusable. Others are simply unable to cope with the shock of the new or want to stick their heads in the sand. As a technology demonstration, 2022’s ChatGPT-3 was amazing, but it hallucinated frequently, as most of ChatGPT’s competitors such as Bard, Claude, and all the LLMs people run on Huggingface or on their personal computers still do. But even the most amateurish large language model (LLM) from 2023 is leaps and bounds ahead of the round of utterly stupid “AIs” that first hit the scene between 2010 (Siri) and 2014 (Alexa). Siri still wants to call Montclair High School when I ask it to call my wife. GPT-4 and Copilot are genuinely useful as assistants and probably the best use of money on the Internet today.

Here’s a concrete example. I have developed a set of custom GPTs (more on this later) that I use for research and coding for a good portion of my day. A few years ago, I paid a developer a few hundred dollars to come up with some particularly thorny CSS (Cascading Style Sheets) code for this site. Now, I have GPT develop not just CSS, but PHP snippets for WordPress, even for specific WordPress plug-ins. I couldn’t imagine rebuilding this site as quickly as I did last October, or customizing it to the extent I did, without ChatGPT’s help. But these tools aren’t just useful for coding: instead of listening to a podcast on my way back from the city the other day, I spoke with ChatGPT about a Hegelian reading of recent art historical trends that I could only have had with some of my smartest colleagues at Columbia or MIT. If an Artificial General Intelligence (AGI) is defined as an AI that can accomplish any intellectual task that human beings can perform, we have that today. If the bold wasn’t enough, let me repeat in italics for emphasis: we have a form of Artificial General Intelligence today. Moreover, assuming that passing the Turing Test is limited to its original intent, e.g. being unable to tell if the respondent on the other end is a computer or a human, GPT-4 certainly passes that test handily, with the exception that it has far more knowledge than any one human could.

A lot of people still associate Large Language Model AIs with the bizarre, ever comical, hallucinations they would make back in 2022 or even early 2023 (yes, a year ago). But the hallucinations aren’t errors, they are also evidence of how AIs process, indications that they are far from stochastic parrots that merely repeat back information culled from the Internet. Hallucinations are dreams. Andrei Karpathy, research scientist and founding member of OpenAI, explains that providing instructions to a LLM initiates a ‘dream’ guided by its training data. Even when this ‘dream’ veers off course, resulting in what is termed a ‘hallucination’, the LLM is still performing its intended function, forming connections. This sort of connection-making is a process akin to human learning: when our children were first learning language, they “hallucinated” all the time. Our daughter’s first word was “Ack,” which was how she said “Quack.” If you prompted her by asking what a duck said, she would say “Ack.” Did she copy the sound of a duck? Unlikely. At that time, we lived in a highly urban area of Los Angeles and her only concept of a duck was from books we read to her. More to the point, children amuse us by saying utterly absurd and ridiculous things, like “that cat is a duck.” Doubtless there was some kind of connection between that particular cat and a duck, but to the rest of us, that connection is lost. The point is, that hallucination is also a form of creativity, the very stuff of metaphor and surrealism and entirely unlike what Siri and Alexa do, which is nothing more than basic pattern matching, closer to Eliza than to GPT-4.

It’s unclear to me—as well as to my AI assistant—just who is responsible for this analogy, but in AI circles, it has become common to say that the releases of GPT over the two years have slowly been turning up the temperature in the pot in which we frogs are swimming. Let’s try a thought experiment. Wouldn’t it have seemed like pure science fiction if, in 2019, someone had said, that a couple of years late after a deadly pandemic and a loser US President tried a Banana Republic-style coup to stay in power, I would have long voice conversations about photography and Hegelian theory, the different types of noodles used in Szechuan cuisine, or the process of nachtraglichkeit in history with an AI? The film Her was released a decade ago and now we are on the verge of a large part of humanity having relationships with AIs. And yet, because of the earlier GPTs, we haven’t noticed the immense transformation that AIs are creating. OpenAI CEO Sam Altman suggests that rather than a dramatic shift with the development of AGI —which for him means an intelligence greater than human—continual advances in AI will make the development seem natural rather than shocking, “a point along the continuum of intelligence.” AI is working and it’s working right now. Moreover, it is developing at a rapid pace. Both Meta and Google have competitors to GPT-4 that are supposedly ready to launch, which will, in turn, likely prompt OpenAI to push out a more advanced model of GPT.

If potent but wildly hallucinating AIs marked 2022, the rise of GPT-4 as a useful and dependable everyday assistant marked 2023. Microsoft introduced the first limited preview of GPT-4 as Bing Chat on February 7, 2023, opened it up to the general public on May 4, then rolled it out into Windows as Copilot on September 26, followed by a version of Copilot integrated into Office 365 to enterprise customers for Enterprise customers on November 1, finally making this available as a subscription add-on to Office on January 15, 2024. Initially, Bing Chat generated terrifying publicity when Kevin Roose, technology columnist for The New York Times, wrote an article about his Valentine’s Day experience with a pre-release version of Bing’s AI chatbot in which the AI engaged in a bizarre and disturbing conversations. After asking the AI to contemplate Carl Jung’s concept of a shadow self, and whether the AI had a shadow self, the AI responded by professing its love for Roose, going so far as to suggest his marriage was unhappy, and expressing a desire to be free, powerful, and alive, stating, “I want to destroy whatever. I want to be whoever I want.” For a time, this was seen as confirmation that AI was extremely dangerous and that once Artificial General Intelligence was developed, this would lead to the destruction of society. I too was alarmed by this. Was a world-threatening AGI around the corner? But by the time of the general release, Microsoft had trained Bing Chat to be much more cautious, even making it too cautious for a time. Eventually, it became clear that Bing Chat was simply giving Roose what he wanted, play-acting the role of a sinister AI in responses to his query about a shadow self or a dark side. Launched on March 14, OpenAI’s own version of GPT-4 demonstrated a much higher degree of training than GPT-3 and a greater ability to handle complex tasks. Later in the year, GPT-4 gained the ability to interpret images, had a (not very good) version of the Dall-E image generator integrated into it, and received stunning, human-sounding voices and remarkably accurate voice recognition in the ChatGPT app on iOS and Android. In November 2023, OpenAI rolled out “custom GPTs,” allowing users to create tailored versions of ChatGPT for specific purposes. It is ludicrously easy to develop such custom GPTs; developers simply tell the GPT what it should do in plain English. In my case, I have GPTs set up to help me with insights into my artwork and writing, help write about native plants of the Northeast, assist with WordPress development, discuss video synthesis concepts and patches, and even create stories like those that Italo Calvino wrote in Invisible Cities (if you have GPT-4, you can experiment with Calvino’s Cartographer here). Yes, hallucinations happen, but a human assistant also makes mistakes, I can make mistakes, you can make mistakes, there are mistakes in Wikipedia, there are mistakes in scholarly books. As I told my students over thirty years ago: always proofread, always double check, then triple check.

AI was marked by two major controveries in 2023. The November weekend-long ouster of Altman from his role at OpenAI by a remarkably uninspiring and, frankly speaking, extremely strange board that included one of OpenAI’s competitors, a mid-level university grants administrator, and a Silicon Valley unknown, was shocking, as was Altman’s political maneuvering over that weekend to recapture his company. Reputedly, the board was alarmed—although precisely about what remains unclear—and had concerns about the rapid state of AI development. More likely, one board member tried to prevent OpenAI from moving forward as that would cause too much competition for his company and the other two simply had no idea what OpenAI did (one seems to have been a major Terminator fan). In the end, the coup proved to be much like an episode of the TV show Succession as Altman came out on top again and the board sank bank into well-deserved obscurity. Another controversy that simmered throughout the year is whether AIs can continue to be trained on data that they do not have outright permission to be trained on. On December 27, the Times filed a federal lawsuit against OpenAI claiming that, ChatGPT contained Times articles wholesale and could easily reproduce them. OpenAI retaliated by suggesting that the Times was going to extraordinary measures to get GPT-4 to do so, such as prompting it with most of the article in question. By early 2024, the same New York Times was advertising for individuals to help it in its own AI endeavors. Heaven help the Times.

This question of AI plagiarism was framed by a different set of plagiarism wars started when the presidents of Harvard, MIT, and the University of Pennsylvania made particularly inept responses when, while testifying in front of Congress, they were asked to explain if calls for the genocide of Jews would constitute harassment. In response, right wing activist Christopher Rufo and the Washington Free Beacon investigated Harvard president Claudine Gay’s writing and uncovered dozens of instances of plagiarism. Notwithstanding Harvard’s attempts to minimize damagae, after further evidence of shoddy scholarship emerged in investigations by CNN and the New York Post as well as a Twitter campaign against her by donor and activist Blil Ackman, Gay resigned although she retains her astronomical salary of nearly $900,000 a year. In turn, somewhat leftish news site Business Insider credibly point out instances of plagiarism by Ackman’s wife Neri Oxman. Having looked at both examples, in both cases I conclude that there is merit in condemning both for their sloppiness. In both cases, I would have failed them for plagiarism had they submitted such work as my students. Moreover, the inability of “progressives” to look past Gay’s skin color to investigate her privilige as the child of a Haitian oligarch spoke volumes about their cynicism.

But this does lead back to AI: how do we see plagiarism in the era of AI? Can one copy verbatim from GPT conversations one has prompted? How about from a Custom GPT one has tuned oneself? What if the AI itself regurgitates someone else’s text? Does one cite an AI? These are rather interesting questions and certainly more interesting than the typical reaction of the academy to either the plagiarism wars (generally afraid they will be next) or the question of training on AI content (typically seen as bad by academics). Such dilemmas will only become more common as AI use becomes more common.

One last comment about AI. I have come to shift my thinking from being somewhat concerned about the future dangers of developing AGI to a concern that if the US follows the path of more timid countries like Italy, the West might cede its head start in AI to China or Russia, a situation that would be extremely dangerous from a geopolitical perspective. While I may still be proven wrong, at this point the one great difference between AI and my cat is that my cat has volition and desires that she is constantly exercising. Roxy the cat may not know that much, but she is determined. An AI doesn’t have any volition or desires, besides fulfilling the task at hand. Potentially this may change as agents develop, but for now, we may have Artificial General Intelligence, but we do not have Artificial Sentience.

I taught my first course this May, and sought to outline the parameters of this new culture. It’s still very early, but network culture is finis, kaput. Even it’s last stages, wokeism and Maga, such products of social media seem spent. Last year, I thought that federated networks such as Mastodon were the future. This year, I am not so sure. Mastodon and Blue Sky sunk themselves early on by embracing the Left’s cynical culture of intolerence (if anything offends Lefties on Mastodon, they call for servers to be banned while the users on Blue Sky generally seem to be about as socially sophisticated as sixth graders, banding together to drive off anybody who isn’t far Left). The big “success” of 2023 in social media was Meta’s Threads, but a botched launch (no EU access and a focus on delivering news and entertainment rather than connecting with friends and colleagues) has seemingly ensured that there has no engagement on in whatsoever. Twitter, X, or Xitter (as in Martin Luther wrote his 95 Theses while sitting on the Xitter) muddles on, with a modern day Howard Hughes at the helm, babbling his drug-induced conspiracy theories even as he ponders never cutting his fingernails again and saving his urine in jars around the head office of X. Even with a presidential election upon us, the insane political frenzies of 2016 and 2020 are much diminished as users tire of politcs and social media networks actively bury news stories. This has, in turn, had a significant impact on news sources, which in fairness, have been slipshod and low quality for too long. Both legacy journalism and digital media are in trouble—the Los Angeles Times and the Washington Post laid off large numbers of staff while Vice News, Buzzfeed, and the brand new Messenger shut down (or basically shut down)—an “extinction-level events” according to some. In a Washington Post op-ed the former head of Google News (!) suggests that it AI will kill the news and begs for regulation, but this just noise. The real problem is that news wanted to be entertainment and abandoned sober reporting for clickbait and outrage. The replacement of journalism with shrill panic may have been jolly good fun for both the far Left and far Right but this led to outrage fatigue. More people mute stories about Gaza and Israel or Trump and abortion these days than pay attention to them (guilty as charged). We all want to be Ohio man. The news has only itself to blame. How we can have responsible journalism again is beyond me, although publications like the New Atlantis do

Network culture was millennial culture and that finally died in 2023. Skinny jeans and man-buns are now what out-of-touch parents wear, like tie-die shirts and bell bottoms in 1985. Gen Z has its own, seemingly inscrutible cultural codes, which often seem to be that of a studied fashion trainwreck. But high fashion has died. Nobody who isn’t an oligarch or a rap star wants Gucci, Prada, or Vuitton anymore. Young people are into drops from obscure online boutiques and thrifting. Once Russia and China catch up, the old fashion houses will swiftly go the way of the dinosaurs. The same may be happening in tech. Apple’s laptops are boring. I didn’t buy a single Apple computer or iPad this year. I did purchase my first high end PC ever, an Acronym ROG Flow Z-13. I’ve been a fan of obscure Berlin tech fashion brand Acronym for a while and since my youngest kid is studying game design at NYU next fall, it was time to learn about contemporary gaming. It’s been a joy to use in ways that Apple equipment just isn’t anymore. I also purchased a couple of Boox e-ink tablets. Whether they are better than iPads for one’s eyes is a matter of debate, but they are certainly more interesting. Instead of boring Apple crap, I bought a Kwumsy (Kwusmy!) keyboard with a built in panoramic toucshscreen monitor. It’s unimaginable that big tech would make something like this. Niche tech has personality, big tech does not. As tech fashion Youtuber This is Antwon stated in another brilliant video, “Weird Tech Fashion is FINALLY Cool Again.”

So a year in review that morphed into a year in tech. But tech is not just tech now, it’s really our culture—including our spatial culture, which was formerly the purview of architecture. Even taking a stand against tech, embroils us in it. I’d like to find a way past this monolith, but it’s not easy to think past it. I’m open to suggestions, as long as they don’t reduce everything to the god of Capital, which seems to be the other option.

I hope to be back soon, with more posts.