As conversations about NFTs proliferate, lessons about algorithmic collaboration abound

On the main east-west thoroughfare in Marfa, Texas, the Art blocks house/gallery sits between an upscale prix fixe restaurant and a church. With four bedrooms, three bathrooms, a large yard and an independent garage, it is a house big enough for the city. It would be rather understated if not for the large mural painted on the north wall of the garage, featuring bright colors and wavy abstract figures floating against a whitewashed wall. Although hand painted by the artist Tyler Hobbsthe mural is part of a series of computer generated abstract artworks called fidenza, a set of 999 unique two-dimensional graphic compositions stored as JavaScript code and rendered using a web browser. The name might sound familiar to those who followed the artistic craze for non-fungible tokens (NFTs) last year.

by Hobbs fidenza has made headlines for exploding the digital art market and earning over $177 million in secondary sales to date. The current lowest price for a Hobbs edition fidenza is 66 Ethereumor around $183,000, putting the work’s value on par with high-priced artists like Jean-Michel Basquiat and David Hockney.

Why is there a physical fidenza mural on a garage wall in Marfa? Because Art Blocks facilitated Hobbs’ generative project. Art Blocks is both a broker and curator for code-based NFT artworks as well as a platform to facilitate specifically “on-chain” generative art projects. This not only means that these digital works are associated with blockchain transactions as a receipt of ownership, but they use the blockchain transaction as a “seed” to generate an entirely unique composition. In the case of Hobbs fidenza, each purchase transaction (called a “strike”) generates a new composition whose characteristics such as color palette, shape direction, and density are all controlled by an algorithm that filters out parts of the transaction ID (the token) and uses it to change the parameters of the final output. Like a Kinder Egg surprise, buyers don’t know what their fidenza will look like until the end of the transaction.

Some of this will not seem new to an architect or designer who has used parametric tools or programmed algorithms. Code-based design methods have been around since at least the 1960s and have seen waves of popularity. In the late 1970s and early 1980s, computer-generated art began to gain legitimacy as a discipline, leading to publications such as Infographics and Art magazine (1976-1978) and Herbert Franke Computer Graphics, Computer Art (1971). The aesthetic spawned by these experiments was geometric and entropic, with artists taking advantage of the ability of computation to produce controlled yet unexpected effects. In this search for new visual forms and illusions, the computer becomes the creative collaborator of the artist.

In the 1990s, Net Art (the movement that celebrated the early aesthetics of the Internet) somewhat eclipsed generative art, but it would see a resurgence in the post-2000 creative coding boom associated with DIY programming tools such than Processing and openFrameworks. These open source initiatives introduced a new generation to visual mathematics and the legacy of generative art, resulting in a group of artists focused on producing not only algorithm-based artwork, but also freely available tools and knowledge. Some architects have embraced this new knowledge and collaborated with generative artists to explore the architecture of computational methods, many of which were cataloged in the seminal 2010 book. Form + Code in design, art and architecturewritten by Casey Reas and Chandler McWilliams and published by Princeton Architectural Press.

Today’s digital design methods are directly inherited from this lineage. Grasshopper and other parametric design tools have integrated popular techniques into their interfaces and produced workflows for generating architectural elements from triangulation, geometric conditioning, and recursive algorithms. Eventually, what characterized the parametric turn of the early 2010s became a default formal language associated with specific visions of what futuristic computer-designed architecture should look like.

What I find particularly exciting about the recent generative art movement is the wide variety of effects produced. Unlike the previous wave of generative design in architecture that was characterized by an overuse of Voronoi algorithms and smooth parametric surfaces, the visual landscape created today is much more diverse and entropic. Meaning: There is no singular style associated with contemporary generative design. And this is a good thing.

Computer design does not require a specific language or visual style. Take, for example, a recent Art Blocks project titled Free plan by the Turkish architect known as XNMTRC, a series of Miesian pavilion plans that explore his eponymous architectural concept. XNMTRC’s project is a “chain” algorithm that generates unique shots according to modernist principles, resulting in compositions reminiscent of the Barcelona Pavilion and Mies van der Rohe’s Farnsworth House. While outsiders to the discipline may view the results generated as striking geometric compositions, architects arrive with disciplinary interpretations. In other words, Free plan is a computer project that goes far beyond computer interpretation. From an academic point of view, Free plan contributes to a larger dialogue that blends both the history and theory of architecture and computing (think Mies meets Vera Molnár). From a techno-economic perspective, it fits provocatively into the debates around labor and automation in architectural design.

Free plan also illustrates how drawings and images can have speculative value in the tradition of “paper architecture”, reviving a prior art market interest in architectural drawings. Similar to OMA selling paintings by Madelon Vriesendorp for extra income in the 1970s, some architects can now market their media to a wider audience. The current price, for example, of an iteration of Free plan in the secondary market is 0.2 Ethereum or ~$500. The advent of NFT technology has made it possible for artists whose medium is primarily digital to sell and distribute their work much like physical media artists. This, in turn, has catalyzed a resurgence of interest in generative art as a commodity, as evidenced by the emergence of Art Blocks and other blockchain-based generative art platforms. This year’s Venice Art Biennale even created a Decentralized art pavilionwhich hosted works by several prominent generative artists.

While volatile market speculation around art has always existed and architects have sometimes benefited from an art market that values ​​architectural media, it is possible that what current generative art and the The broader digital art movement offers us new insights into algorithmic collaboration. These should not be purely technical; they can be conceptual, theoretical, economic or cultural. I’ve personally had some fascinating debates online with artists around retrograde aesthetics in emerging artwork. During these conversations, we discussed why, for example, some generative projects use nostalgic effects such as artificial grain in coded images or why some artists insist on reproducing hand-drawn effects. As a stranger to the world of generative art history, I learned from both curators and artists, which in turn affected how I approach generative design.

It’s easy to be seduced by the striking and imaginative imagery from NFT generative art platforms. But it’s important to understand that these artists worked on this medium long before it was fashionable and long before it was financially viable. Generative art is an autonomous discipline with its own history and cultural values. Sometimes these values ​​align with those of the architects and fruitful collaborations can emerge. Architects could also learn something about the generosity of the current wave of generative art. The generosity of coders, programmers, artists, and technologists making their knowledge freely available is abundant in these growing communities. It led to record donations for the treatment foundation, which supports coding camps for students, grants for artists and researchers and, of course, the development of processing tools. Programming has become much more accessible thanks to this generosity, while architecture remains a very exclusive and often inaccessible knowledge. Perhaps the lesson here is neither purely visual, nor formal, nor technical: these developments offer lessons in sharing expertise as well as opening up previously exclusive knowledge to a wider audience.

Galo Canizares is a designer, writer and educator currently studying the socio-technical networks of relationships between the softwarization of design and the architectural imagination. He is the author of D.Digital fabrications: designer stories for a software-based aircraftt, a collection of essays on software and design.