“NFT’s are birth certificates for the offspring of creators.” Dane Scarborough 

To investigate NFT in the realm of artwork, it would be valuable to investigate the production process of NFT as compared to the traditional artwork. Many of the NFTs are created from tangible or intangible materials, for example, a securitized version of crypto art, a TikTok video, or even a tweet. To some extent, NFT can act as the common middle ground for transactions rather than the actual creation of artwork.

The way of minting an NFT by uploading media to the platform requires the form of pre-existing creation. Each artwork minted on platforms such as Opensea, NiftyGate, and Foundation contains a unique identifier for the artwork providing the contract address that allows open access to the public record of provenance, price, ownership, and authenticity. The transparency of the transaction also allows artists to track them and receive royalties from future transactions. In the other words, NFT transfers the artwork from the traditional commissioned artwork trading to a free market where the artists can sell their works directly to their fans.

It is right to be concerned, will digital art assets’ rising market bring a synergy or cannibalization effect to the traditional art enterprise?

The NFT market has experienced three different stages, (1) the emergence of the art market where only a few NFT artists enter the market (Jan 2021 – July 2021), (2) the growth of the market (August 2021 – December 2021), (3) the continuous booming of the market. The sales data of NFT artwork indicates strong growth from 2021 to 2022. The exponential growth curve suggests much more potential in the future as it emerges in many market segments. There is no doubt that the art world is disturbed by the NFT art as it rapidly inflates. It is hard to predict when and how this overblown bubble will burst in the short term. Yet, in the long term, it will be an add-on value to the art enterprise by creating more opportunities. I argue that it poses an augmented effect on the art market at large.         

Decentralized NFT Business Model 

The business models and underlying logics of trading art as a form of NFT and trading physical art are very distinctive.

It is right to ask the question if NFT is the placement or extension of the art market?

There are five categories when considering the intervention of NFT in the art world, business model, product, target customers, pricing strategies, and marketing. The foundational technical difference alters the product type from physical to digital, which expands the distribution channel from offline to online. It also changes the idea of patent and copyright in trading an art piece. NFT buyers only purchase the digital copy of the work with the possibility of transferring the copyright and IP with the artists’ permission. Whereas in trading physical artworks, the collector owns the physical object of the artwork without the copyright. Most of the time, artists wouldn’t be related to the later transactions and receive the royalties. 

Like the business model shown below, the traditional art enterprise model is heavily centralized with the informal network as all the artists rely on dedicated arts institutions and organizations that have a network of collectors and resources to sell their artworks. Gallery selects artists based on their medium, art education institution, the number of gallery/museum shows, and previous collectors. This highly competitive process excludes those who may have strong artistic talent, but don’t have the required art education from renowned institutions. Or they also exclude artists who practice highly experimental art that is hard to collect, sell and maintain.

The target consumers for physical artworks are rather exclusive as they only focus on collectors who already have the credential of developing a valuable collection or have prior collecting experience. Because of the exclusivity of the collector community, the marketing of the artwork is mostly through collector’s dinner, word of mouth, and digital channels. The transaction happens privately and the artists make living out of the commission, which is around 50%.  

The NFT and the rising of web3 are interruptable and decentralized which allows people from different industries and sectors to interact. The barriers to entry are fairly low. By providing the opportunity to trade outside of the art enterprise, it interrupts the traditional art business ecosystem, such as galleries, auction houses, and individual collectors. It is a public trading platform that enables free buying and selling. Anyone with access to the internet and a digital wallet can purchase NFT artworks, at the same time, any artist can publish their artworks for sale without any qualification scannings. The success of NFT trading depends on the marketing and demand from the market. The selling of the artwork is identical to the auction business model, such as the Artnet auction. The artist lists the artworks and prices them accordingly, and the collector needs to bid to purchase them. 

It provides opportunities for emerging artists to showcase their artworks and have the opportunities to sell them. However, it is important to note that in a free market environment with many small players, it is more difficult for individuals to gain market share and make a profit. Visual artists are not only competing with other visual artists, for example, painters, sculptors, and photographers. The borderless NFT market also attracts other creators, such as graphic designers, cartoonists, musicians, and architects. A question arises, is the NFT market creates more opportunities or more competitiveness?

The social network between artists and collectors 

Many NFT platforms function as social platforms where collectors can follow NFT artists. This NFT platform business model is very similar to YouTube’s subscription model. The collector community determines the potential of NFT artists through the number of followers and their levels of popularity. Twitter is one of the main marketing channels for NFT artists, thus the relationship between Twitter and NFT marketplace has a high correlation. The visibility on social media, like Twitter has a great impact on the total earnings. It has a strong positive correlation that artists with a greater amount of followers obtain higher earnings. However, the diagram on the left indicates a stronger correlation that artists who have a greater number of followers on the NFT trading platform earn more as compared to Twitter. 

Branding and Pricing in the Digital Space 

The pattern of artist success in the traditional art business is dependent on the growing reputation of artwork and the number of sold artworks. The price and the growth are managed and maintained by the galleries. Galleries act as gatekeepers and marketing agencies to make sure artists fit into the market need and demands. This usually is done formally by press release, artist interview, and critique article. As the NFT space lacks the gatekeepers, and artists need to market themselves like YouTubers, it is curious to learn about the changes in the pattern of success. 

Can artists with no marketing resources and budget make more money out of making or turning their artwork to NFT as compared to the traditional art enterprise?

Artists need to place multiple hats on themselves to become an artist, a marketer, and a dealer in order to succeed. The heavy emphasis on marketing and commercialization embedded in the nature of NFT artwork ultimately takes away some of the artistic value. It is also difficult for those who don’t have adequate marketing experience to navigate the market. Yet, it helps develop an integrated business model like Sotheby’s NFT auction, where NFT artworks developed by visual artists are listed through Sotheby’s platform.  

Web3 has changed the value chain of pricing and valuation of an art piece. The value of artwork no longer relies heavily on artists, concepts, materials, and curatorial studies, but is closely related to consumerism, economic factors, and the demand for the object in the second-hand market. In the art world, there are three main reasons why a digital-oriented collector would like to purchase a work of art, to support the artist, to establish the social status, and to invest. The ownership of a physical artwork is both the representation of social legacy but also a form of social currency. But for NFT art, why do people need to purchase an object, if they can look at it for free?

Collecting an NFT artwork is purchasing a digital asset. Collectors purchase the version of the media as a form of NFT in the digital marketplace as an act of investment and financial parking. It is also a form of owning a virtual currency in the metaverse. 

Future of Gallery and Auction House 

After analyzing the NFT marketplace from diverse perspectives, I perceive NFT as an extension of the booming Metaverse, which can be a valuable add-on opportunity for the art world. It brings dynamic artistic products which invent a one-of-its-kind model of transaction. I think it brings in more synergy effect than cannibalization as many of the auction houses started to incorporate NFT art into their business. For instance, the video NFT artwork, Self Transcending by Sara Zucker was listed on Sotheby’s NFT auction platform and the final sale price is $22,680.      

It opens the door for multi-media artwork that seems unfavorable to many collectors, at the same time expanding the market size of the art world. It is right to forecast that the incorporation of the auction house and NFT artwork is not the only form of collaboration in the art enterprise. As the NFT marketplace becomes more prevalent along with the growth of the metaverse, more creative interventions of business innovation will appear.  

Reference

Anthony, Daniel, and Akiv Jhirad. “Commercializing NFTs – Generating Value from Digital Assets and Intellectual Property Rights,” n.d., 6.

Breen, Nick. “With New NFT Projects Granting Commercial Usage Rights and Copyright Assignments to Holders, We Are Beginning to See the Friction between the Promises of Web3 and the Rigidity of Traditional Copyright Principles. Where NFTs Are Traded like Stocks on Open Marketplaces, What Do Buyers and Sellers Need to Know? We Take a Look from an English Law Perspective.,” n.d., 5.

Conti, Robyn, and John Schmidt. “What Is An NFT? Non-Fungible Tokens Explained,” n.d., 25.

Dash, Anil. “NFTs Weren’t Supposed to End Like This.” The Atlantic, n.d., 6.

Franceschet, Massimo, Giovanni Colavizza, Tai Smith, Blake Finucane, Martin Lukas Ostachowski, Sergio Scalet, Jonathan Perkins, James Morgan, and Sebastian Hernandez. “Crypto Art: A Decentralized View.” ArXiv:1906.03263 [Cs], June 9, 2019. http://arxiv.org/abs/1906.03263.

Hammer, Sarah. “PHOTO: ALEXI ROSENFELD/GETTY IMAGES,” n.d., 4.

Khalil, Nadine. “NFTs and the Future of the Art World,” n.d., 7.

Kugler, Logan. “Non-Fungible Tokens and the Future of Art.” Communications of the ACM 64, no. 9 (September 2021): 19–20. https://doi.org/10.1145/3474355.

Romeo, Jess. “Thirty Years after the Invention of Blockchain, an Artist Sold a JPG Using That Technology for Nearly $70 Million. Huh?,” n.d., 5.

Vasan, Kishore, Milán Janosov, and Albert-László Barabási. “Quantifying NFT-Driven Networks in Crypto Art.” Scientific Reports 12, no. 1 (December 2022): 2769. https://doi.org/10.1038/s41598-022-05146-6.

Wong, Jessica. “What Are NFTs And How Do You Market Them Effectively?,” n.d., 6.

AI-generated artwork has become a popular trend in the art world in the past 5 years. It has shaped the way artists approach artistic production, critics thinking about artworks, and gallerists/collectors proceeding with pricing and collecting artworks. As AI takes on different levels of ownership in the creative process and artistic production, it disrupts the idea of aesthetics and artistic ownership and redefines the business framework for digital art.

The Fundamentals of AI-generated artwork

The idea of artificial intelligence creative generation came from the idea of training the machine to improve their behavior through experience and learning. However, AI as the tool itself is not a constraint within the realm of art when it was first invented. The history of machine-generated creative works can be traced way back to 1842, when Ada Lovelace, the mother of computer science published the first algorithm on the analytical engine. It was the time when Lovelace brought up the idea of “poetical science”. It is a turning point for machine intelligence as it no longer exists for calculation but starts to imitate humans. That was the first intersection between science and art in the field of engineering. While scientists were trying to break through the barriers of computer engineering to develop intelligent machines, the artist also started to imagine the artistic tools beyond paintbrushes and wood chisels. The first drawing robot, Aaron was created by artist Harold Cohen that allowed the machine to paint specific shapes and figures using a pen driven by a mechanical plotting machine according to the algorithms in 1973.

The relationship between machine and art is collaborative, yet complicated. “AI provides the inputs, guide the process, and filter the outputs.” Artist, in this case, is the researcher who studies and breaks down the steps of positioning, drawing, and sizing. For Aaron, Cohen is the person who designs the operational rules for the machine to function. Unlike most artists, Cohen coded the program and built the machine himself. Aaron was designed to produce artwork that was limited to Cohen’s style, which is abstract expressionism. Although Aaron was programmed to paint specific objects, the machine started to generate shapes outside of Cohen’s control. Cohen was impressed with Aaron’s unforeseen artistic decision and their ability to create. He began to commend it for further drawing the subjects besides just reproducing the same copies. It is also important to note that the audience’s interest in Cohen’s machine drawing focuses more on the machine itself rather than the drawing. It poses the question that whether, in this case, Cohen is the artist or the computer engineer? 

As AI evolves, this question no longer needs to be concerned. 27 years after Aaron is invented, artists Casey Reas and Ben Fry created “Processing“, a free graphical library and integrated programming environment for electronic arts, new media, and visual design art. This tool is created from artists’ perspectives with a more accessible tool for programming. The interdisciplinary nature of artificial intelligence and its relationship to creativity burry the line between science and art.  

The element of math and rationality involves in digital art invokes the form of constructivism in artistic production. The form of AI-generated artwork is not constrained to two-dimensional art. The constructivism of things relies heavily on the theories and implications of its value.

The engineer choice of AI is about “capturing and studying the theory of intelligence, of thinking, and rationality and ultimately of human nature”.

Considering the three foundational approaches in building AI: symbolic-computational, connectional, and neurokinetic. Artificial Intelligence is not only constrained in the engineering solution for the problems but also closely related to the realm of social choice and the risks related to it. “AI involves the translation of philosophies of mind.” During the translation process, there are always some barriers that existed. For instance, AI has perpetuated biases, but it also has the potential to expose those biases. The collective unease that technology brings to the art world, and society at large is unchangeable. 

The collective unease and criticism toward AI-generated artwork is the lack of collective rules and knowledge about the technology. What differs from Cohen and most artists who also use programming is the ability to code themselves. Many artists use programming without knowing too much about how to code and how the code functions. As AI becomes more popular and attractive, it is right to question the consciousness of AI-generated artwork given the knowledge gap in computer programming. In 1980, John Searle’s famous critique of AI and his Chinese room argument. The conversational exchange between people who know Chinese can be natural, but very impossible for people who don’t speak Chinese. To proceed with the right response, one must have the consciousness to think.

Searle argues that “an inorganic entity cannot develop intentional states and cannot become conscious”, because the machine will never think, but only act upon instructions given.

Aesthetics of AI error and reproduction 

The reproducible feature of AI-generated artwork challenges the history of aesthetics and uniqueness of the artwork. The fact that AI can mass-produce print images or music rhythms removes the personal touch of artistic creation and stimulate the criticism of this new art medium. Just like the intervention of photography replace realism in oil painting in the 19th century. The reproduction of the image replaces the cult value of the artistic production. As Walter Benjamin brings up in his iconic piece, The Work of Art in the Age of Mechanical Reproduction, mechanical reproduction reimagines artworks from the production ritual. As the technology develops to the current state, it is no longer about reproducing the work of art, but more inclined to deigning artwork for reproducibility. The fluidity of authenticity proposes more potential for artistic creation.       

The element of mechanical variance brings uniqueness to the work of art it creates. Although AI is an automotive system that can generate artworks according to its programming code, the limitation of machines creates outcomes that are, sometimes unpredicted. The aesthetic value of contemporary artworks is about their conceptuality and intentionality. When AI involves in the creative process, the unprecedented result of the artwork ultimately poses the mistranslation between its presentation and concept. Glitch art is a great example of manipulating analog errors to create an alteration of the image. The authoritative position of the artist is giving up a portion of its space to the uncontrol of the machines. Yet, just like any other art medium, many artists enjoy the “degrees of freedom” when collaborating with AI.

For this newly raised art form, artists are making their own rules. The definition and interpretation of art and technology can be varied in the field. The interpretation of art that is related to technology is deliberate. Art and technology can be seen as the umbrella term for any artwork that is related to technology to a certain extent. The terms, “computer art”, “digital art” and “kinetic art” have very different concepts and aesthetics as artwork engages with the machine in different ways. One may see that interactivity is more important than the physical representation of the art. The other may focus more on the machine itself rather than the audience engagement. The ownership of digital artwork is also up to the artistic intention. The paradigm of artistic ownership along with the constructed machine primarily serves the artistic concept that raises meaningful questions and reflects upon social issues.  

The flexible system of creation can refer to Manual Delanda’s idea of limits within the mechanical system. One example is Nam June Paik’s video sculpture, Magnet TV where he altered the television image by placing a magnet on top of the TV. It distorts the broadcast image to an abstract form and the shape changes as the magnet moves. Instead of focusing on the visual appeal of the broadcast image and its transformation, Paik challenged the notion of art as a self-identity by giving the right of alteration to its audience. The interactive nature of the artwork and its happening is the aesthetics of Magnet TV. Whether it’s performance, sculpture, or music, the creative system of developing the conceptual ideas and producing the artwork is about the control of the limit and boundaries of internal error. It is the artistic ownership that gives value to the technology to generate creative results. 

Nowadays, as technology, especially AI becomes more prevalent, AI involves more in-depth in the artistic creation processes. For example, WOMBO Dream is an app that generates text into a drawing. The easy and instant process of creation allows more people to be able to create their artworks with easily accessible apps. It simplifies the artistic creation process by turning it into an easy text to image translation. The path for artistic production is designed and instructed, the artist/user only needs to follow the guideline. Artistic production is replied fully on the machine to construct a concept and visual present by simply giving a prompt. In this case, the machine is taking much ownership of the art. The instant production of artworks increases the number of art existing in the marketplace, which results in changing the competitive landscape for the art business.

The Frictional Economies of AI-Generated Art

The increasing number of AI-powered art creation machines adds another opportunity for the art collection business. The traditional business model of selling painting, sculpture, and photography is overhauled by raising AI and NFT art. The selling of artwork is about the exchange between money and its ownership. For traditional artworks, ownership is mostly the artist, yet for AI art, ownership is very ambiguous. It is difficult to determine whether this artwork is made and owned by the artist or the machine. It all goes down to the copyright of AI art. 

Recently, the U.S. Copyright office refused to grant copyright for an artwork created by an AI machine, Creativity Machine. One of the main reasons for rejection is the lack of human spirit in the work. It raised the concern with all the AI-generated/collaborated artwork. Without the protection of copyright, it is hard to determine who gets to benefit from the art business transaction. There is friction between who makes the work, who owns it, and who gets compensated for selling the work. The denial of the copyright act for AI-generated art poses a stop to the development of AI art in the business world. If there is no fixed right and royalty, it is hard to proceed with the transaction. The question about ownership of art is rising to another level with the mass production of art and involvement of art cryptocurrency. 

As the AI-related artwork involved and the understanding of computer art continues to develop, the legal space and arts enterprises will have a more complete system to incorporate with this intervention. 

Reference

Akdag Salah, Alkim Almila. “AI Bugs and Failures: How and Why to Render AI-Algorithms More Human?” In AI for Everyone? Critical Perspectives, edited by Pieter Verdegem, 161–79. University of Westminster Press, 2021. https://doi.org/10.16997/book55.j.

Andrews, Jim. “A Philosophy of Computer Art,” n.d.

Barker, Tim. Aesthetics of the Error. Media Art, the Machine, the Unforeseen, and the Errant. Continuum, 2011. https://doi.org/10.5040/9781628927924.

Benjamin, Walter. “The Work of Art in the Age of Mechanical Reproduction,” n.d., 26.

Cohen, Harold. “Meta-Art, Artificial Intelligence and the Work of Harold Cohen,” n.d.

Hetrick, Christian. “Art Created by Artificial Intelligence Can’t Be Copyrighted, US Agency Rules,” n.d., 9.

Lea, Gary R. “Constructivism and Its Risks in Artificial Intelligence,” 2022, 26.

Lovelace, Ada. “Ada Lovelace Wrote Extensive Notes on the World’s First Computer. Her Innovations Foreshadowed Those Used in Twentieth-Century PCs.,” n.d., 6.

Mateas, Michael. “Expressive AI: A Hybrid Art and Science Practice.” Leonardo 34, no. 2 (April 2001): 147–53. https://doi.org/10.1162/002409401750184717.

Menkman, Rosa (2011), “Glitch Studies Manifesto” (PDF), in Lovink, Geert; Somers-Miles, Rachel (eds.), Video Vortex Reader II: Moving Images Beyond YouTube, Amsterdam: Institute of Network Cultures, pp. 336–347, ISBN 978-90-78146-12-4, archived from the original (PDF) on 2011-08-27

Manuel DeLanda, Intensive Science and Virtual Philosophy (London: Continuum, 2002), 13.

Rea, Naomi. “How Did A.I. Art Evolve? Here’s a 5,000-Year Timeline of Artists Employing Artificial Intelligence, From the Ancient Inca to Modern-Day GANs.” n.d., 10.

Somaya, Deepak, and Lav R Varshney. “Ownership Dilemmas in an Age of Creative Machine,” Issues in Science and Technology, 2022, 8.