3.4.4 Creativity
This section analyses how different knowledge technologies impact people’s creativity. Here creativity is intended as the ability to express themselves in a way that is both truthful to what they feel and believe, as well as the power to experiment with artistic creation. This section considers three aspects. First, the risk of standardisation of creative process and content, often to exploit them economically. Second, the section analyses how people have negotiated their creative agency with knowledge technologies, to what extent machines can be considered creative, and if this hinders or support human expression. Finally, we discuss the impact of AI and computer technologies on artistic creativity and how artists can influence their development and push for a more human-centre approach.
The threat of standardisation and economic exploitation
AI and big data
The advent of AI and big data has brought significant changes to creative industries, raising concerns about standardisation and economic exploitation (Goetze 2024).
First, the loss of jobs and opportunities for artists, coupled with copyright issues. The rise of AI-generated content has led to concerns about job displacement in creative fields (Caporusso 2023). For instance, the Writers Guild of America strike in 2023 was partly motivated by fears that AI could replace human writers (Hourigan 2023). Tools like ChatGPT and DALL-E have demonstrated the ability to generate text and images that can, in some cases, rival human-created content. This has raised questions about the future role of human artists and writers in content creation.
Futhermore, copyright issues have also come to the forefront. In 2022, Getty Images banned the upload and sale of AI-generated images due to copyright concerns (Vincent 2022). The use of existing artworks to train AI models without artists’ consent has led to legal challenges, such as the class-action lawsuit filed against Stability AI, Midjourney, and DeviantArt (Whiddington 2024).
However, generative AI doesn’t simply impact artists and creators, but also audiences. Indeed, recommendation engines, powered by AI algorithms, have become ubiquitous in how we discover and consume art. While these systems can be effective in suggesting content based on user preferences, they risk creating “filter bubbles” that limit exposure to diverse artistic expressions. This algorithmic curation may lead to a homogenisation of taste and a reduction in serendipitous discoveries that often drive artistic innovation and appreciation (Freeman et al. 2022).
Finally, the rise of AI-generated art and the increasing mediation of artistic experiences through digital platforms raise questions about the fundamental role of art in society. Traditionally, art has been viewed as a means of shared experience and interpersonal communication. However, the proliferation of AI-created content and the individualised consumption facilitated by recommendation algorithms may be shifting this paradigm.
Past examples
There are concerns that AI-generated art might lack the depth of human experience and emotion that often gives art its resonance. However, such concerns about standardisation and economic exploitation in creative industries are not new. Historical examples provide context for current debates and offer insights into potential responses to these challenges.
One of the most notorious criticisms levelled against the effects of mechanised art is Walter Benjamin’s argued seminal essay The Work of Art in the Age of Mechanical Reproduction (1936). Benjamin maintained that the “aura” of art – its uniqueness and authenticity – may be compromised by mass production and reproduction. When everyone can have a reproduction of the Mona Lisa in their home, the aura of the original painting is lost and so is its artistic power. When applying Benjamin’s reading the present, it is evident how AI-generated art takes this a step further, potentially divorcing artistic creation from human experience entirely. However, Benjamin did not fully discredited mechanical reproduced art, but instead recognised its potential for democratising artistic consumption and allowing new groups of people to enjoy something that was usually reserved to the elites.
Such optimistic view was famously challenged by the members of the Frankfurt School, who believed that the democratising effect of mechanical reproduced art simply included larger audiences for economic exploitation. Art appreciation was transformed into art consumption as creative content became indistinguishable from any other goods.
Theodor Adorno and Max Horkheimer’s critique of the "culture industry" in their work Dialectic of Enlightenment (1947) provides a framework for understanding current concerns about AI and creativity. They argued that mass-produced culture leads to standardisation and the loss of artistic authenticity.
Adorno and Horkheimer contended that the culture industry reduces art to a commodity, stripping it of its critical potential and ability to challenge societal norms. They wrote: “The culture industry perpetually cheats its consumers of what it perpetually promises” (Adorno and Horkheimer 1947: 139). This critique resonates with concerns about AI-generated art, which may produce content that is superficially appealing but lacks the depth and intentionality of human-created art, and that also may prioritise marketability over artistic expression.
However, it's important to note that the Frankfurt School’s perspective has been criticised for its elitism and failure to recognise the potential for subversion and creativity within popular culture (Busk 2020: 107-128). Similarly, a nuanced approach to AI and creativity is necessary, recognising both its potential threats and opportunities.
While standardisation and commercialisation can pose threats to creativity, historical examples show how artists as well as regular people have often turned constraints into opportunities for innovation.
The tradition of crossed letter writing in the 19th century is one such example. Crossed letter writing was a technique used to save on postal charges when people were charged by the page (Kindel 2016). Writers would fill a page with text, then turn the paper 90 degrees and write across the existing text. This practice is mentioned in Jane Austen’s Emma (1815), where Miss Bates describes a letter from Miss Fairfax: “[I]n general she fills the whole paper and crosses half. My mother often wonders that I can make it out so well” (Austen: 135). While primarily a cost-saving measure, crossed letter writing became an art form in itself. It required skill and creativity to compose legible and meaningful text within these constraints. This practice demonstrates how limitations can spark innovation and new forms of expression, a lesson that could be applied to the constraints imposed by AI and other digital technologies.
Another example of creativity flourishing within technological or economic constraints is offered by Xerox art. In the 1960s and 1970s, artists like Bruno Munari experimented with photocopiers to create new forms of visual art. Munari’s book Xerografia: Documentazione sull’uso creativo delle macchine Rank Xerox (Xerography: Documentation of the creative use of the machine Rank Xerox), produced for the XXXV Venice International Art Biennale, 1970, showcased the creative possibilities of this office technology, demonstrating how artists can repurpose standardised tools for creative expression. While the photocopier’s designed purpose was to produce identical copies of the same document, therefore ensuring standardisation, people found a way to subvert this, not just in art, but in visual communication. This is the case, for instance, of punk fanzines in the late 1970s and 1980s, which popularised a creative and subverting use of copying machines (Houston 2023).
A similar example of how standardisation and commercialisation can impact personal expression is offered by the rise of the greeting card industry in the 19th and 20th centuries. Greeting cards, with their pre-written sentiments, have been criticized for commodifying emotional expression and potentially diminishing authentic communication. Emily West (2010) notes that critics view greeting cards as "a lazy and less authentic substitute for the best form of interpersonal correspondence, which would be a handwritten note or face-to-face talk" (West 2010: 454). However, West also found that many people use greeting cards creatively, selecting cards that align with their personal style and often adding personalized messages. This suggests that even standardized forms of expression can be personalized and imbued with individual meaning, a perspective that could inform our approach to AI-generated content.
A more recent example that demonstrates how material limitations imposed by technological affordances can fuelled creative responses is the one of Twitterature or Twitter Literature (Agrawal 2023). The 280-character limit on Twitter – in place until 2023 – gave rise to new forms of micro-fiction and poetry. Writers and users embraced this constraint to create concise, impactful pieces of literature, showing how digital platforms can inspire new creative forms.
The advent of digital technologies and the Internet has led some writers to embrace what Kenneth Goldsmith calls “uncreative writing.” In his book Uncreative Writing: Managing Language in the Digital Age (2011), Goldsmith argues that in an era of information overload, the writer's role shifts from creating original content to managing existing information. Goldsmith’s work, which often involves transcribing or repurposing existing texts, challenges traditional notions of authorship and creativity. This approach resonates with some of the questions raised by AI-generated content, particularly regarding originality and the role of the human artist in an age of algorithmic creation. While Goldsmith's approach has been controversial, it offers a perspective on how people might engage with, rather than resist, the challenges posed by new technologies. It suggests that creativity in the digital age might be more about curation, contextualisation, and reframing than about generating entirely original content.
These examples suggest that while knowledge technologies may impose new constraints on creative expression, they may also inspire new forms of creativity and artistic innovation. Indeed, their impact on creativity is complex and multifaceted. While there are legitimate concerns about standardisation, job displacement, and the changing nature of artistic creation and consumption, historical examples suggest that artists have often found ways to adapt to and creatively engage with new technological constraints. As we navigate the challenges posed by AI in creative industries, it's crucial to balance concerns about economic exploitation and standardisation with an openness to new forms of creativity that may emerge. The key may lie in fostering an environment where AI is a tool for augmenting human creativity rather than replacing it, and where the unique value of human artistic expression is recognised and protected.
The rise of AI-generated creative content, and the increasing mediation of artistic experiences through digital platforms, raise questions about the fundamental role of art in society. Traditionally, art has been viewed as a means of shared experience and interpersonal communication. The proliferation of AI-created content and the individualised consumption facilitated by recommendation algorithms may risk shifting this paradigm.
Authorship and intentionality
AI and big data
Generally, the analyses of the role of the human creator are shaped around the tension between the fear that AI systems can equate human creativity and thus eventually make it redundant on one hand (Russell), and the conviction that AI-generated knowledge cannot exist without an embodied mind behind it (Elgammal; Pfeiffer; Klingemann and Spratt) on the other.
At its core, this debate grapples with fundamental questions about the nature of creativity and the role of conscious intention in the creative process. While proponents of AI authorship argue that the ability to generate novel and valuable outputs satisfies certain criteria for creativity, detractors contend that true creativity necessitates a depth of understanding and originality that current AI systems lack (Boden 1998).
The question of intentionality further complicates this discourse, as AI’s absence of conscious motivation challenges traditional notions of authorship (Searle 1980; Sueur et al. 2024). This philosophical dilemma extends into the legal and ethical realms, where existing copyright frameworks, predicated on human authorship, struggle to accommodate AI-generated works (Lee 2024). Some scholars propose reconceptualizing AI as a collaborative tool rather than an independent creator (Vinchon 2023), though this perspective raises its own set of questions regarding the threshold of human involvement required for authorship claims.
While these conundrums are impossible to be solved outside personal convictions and specific modes of knowledge production, there is another way in which A is changing our understanding of the role of the author beyond the opposition human/artificial. Precisely, there is a shift from the concept of the author as an individual, voicing their own feelings and ideas, to a more inclusive, collaborative and dispersed definition of authorship as the expression of a collective intelligence. The democratizing effect of questioning the traditional idea of the author as a lonely creator, possessing a special sensitivity and a unique creative spirit has been advocated well before the advent of AI arts (Foucault 1969). However, it is with the spreading of AI new tools and mode of knowledge creations that collective authorship has become an actual possibility.
The emergence of a ‘collective intelligence’, meaning a collaborative effort between dispersed subjects who all contribute to problem-solving and decision making, has been recognized in connection with the spread of IT and online networks (Lévy 1994; Jenkins 2006). While they could make it easier to acknowledge the creative input of larger communities, often underplayed or disregarded (Lindtner et al. 2012), AI systems could offer further tools to tackle this lack of recognition and help supporting a more democratic, collective idea of authorship. AI-generated content, relying on machine learning and data gathering, is indeed the direct product of a hive mind: if the concerns about amplifying bias and stereotypes when using AI systems in arts are indeed justified, by the same token it is also true that the very same tools give creators access to the collective experience and knowledge.
Acknowledging this would not simply be fair, but instrumental to create a more inclusive and interactive landscape. Indeed, the use of AI to serve collective intelligence has been advocated for tackling social issues (Borders 2018; Mulgan 2018; Weld et al. 2015). What has always been the case for any form of knowledge production – that it would not exist without the community in which it is produced – becomes evident when using AI systems.
As AI technology continues to advance, the parameters of this debate are likely to shift, necessitating ongoing re-evaluation of our understanding of creativity, intentionality, and authorship in the age of artificial intelligence.
Past Examples
The debate on human and machine authorship, understood as agency and intentionality, revolves around two main questions.
First, to what extent human expression depends on people’s personal sensibility and inclinations, and to what extent this instead is shaped by the tools that they use. In other words, to what extent the materiality of the media being used determine not just the style, but the very content of a message.
Second, what it means for a machine to be creative and what constitutes authorship. If authorship can only be assigned to subjects with consciousness and awareness, then only humans can be authors. Alternatively, if what matters is the level and quality of content being produced, disregarding on the process, it is plausible to consider machines as potential authors.
Many examples can be considered in regard of the first question on material constraints imposed onto human expression by knowledge technologies.
For instance, the transition from oral to written culture represents one of the earliest examples of how knowledge technologies reshape human expression. In Orality and Literacy (1982), Walter Ong argues that the invention of writing fundamentally altered human consciousness and modes of expression. The shift from oral to written poetry, for instance, changed not only how poetry was composed and transmitted but also its very nature. Epic poems like Homer’s Iliad and Odyssey, products of oral tradition, exhibit features like formulaic repetition that aided memorization – a necessity in oral cultures but less crucial in written ones (Janko 1998).
A specific and well documented instance of example of how writing technologies can influence thought and expression is the change to Friedrich Nietzsche’s style since he began using a typewriter to compose his work. In 1882, due to failing eyesight, Nietzsche began using a Malling-Hansen Writing Ball, an early typewriter. Friedrich Kittler, in his book Gramophone, Film, Typewriter (1986), argues that this technological shift had a profound impact on Nietzsche's writing style. Kittler notes that Nietzsche’s prose became more telegraphic and aphoristic after he started using the typewriter. He quotes Nietzsche as saying, “Our writing tools are also working on our thoughts” (Kittler 1986: 200). This change in Nietzsche’s style, characterized by shorter, more concise statements, coincided with what's often referred to as his “mature period,” suggesting a direct link between the constraints and affordances of the typewriter and Nietzsche's philosophical expression.
The mass diffusion of the personal computer and word processors in the early 1980s again changed people’s relationship with text (Hammond 1984). Such change is better documented in the accounts of published authors, not because they were the only ones to deal with impact of computer technologies, but because we are left with interviews and articles that openly chronicled the experience. This is the case of the authors Primo Levi. In an article originally published in January 1985 in the Italian computer magazine Genius, he described his experience with his first, desktop computer, an Apple Macintosh that he had bought the previous year:
I’ve noticed that when you write this way you tend to be wordy. The effort of the old days, when writing meant chiseling away at stone, led to a “lapidary” style. Now the opposite takes place; there is practically no handwork, and if you aren’t careful you can veer into prolixity. Fortunately, there is a word counter, and it should not be lost sight of” (Levi 1989)
Levi, while not at all opposed to using a word processor in his artistic work, was nonetheless concerned by how smooth the physical experience of writing had become and this material change, like in the case of Nietzsche, could have impact the content and style of his work.
Concerning the second issue, the one pertaining authorship and if this can indeed be granted to non-human actors, it is interesting to consider the long opposition against mechanical music.
The development of mechanical music reproduction in the late 19th and early 20th centuries sparked debates about artistic authenticity and the role of human performance (Suisman and Strasser 2010) that parallel current discussions about AI-generated art. Among the many examples of resistance against the mechanical reproduction of music, the one of sacred and military music are especially compelling. These is because in both cases music is not meant for entertainment, but is the expression of human values – be it courage or spirituality – and is tasked with inspiring people’s betterment and emotional connection.
John Philip Sousa, the American composer known primarily for American military marches, voiced strong concerns about the impact of mechanical music reproduction on culture and creativity. In his 1906 essay “The Menace of Mechanical Music,” Sousa warned that recorded music was becoming a “substitute for human skill, intelligence and soul.” He wrote: “When a mother can turn on the phonograph with the same ease that she applies to the electric light, will she croon her baby to slumber with sweet lullabies, or will the infant be put to sleep by machinery?” (Sousa 1906). While the corruption of children, brought up without the comfort of human-made music and songs was of his concern, Sousa was equally distressed at the thought of soldiers led to battle by “a huge phonograph, mounted on a 100 H. P. automobile, grinding out ‘The Girl I left Behind Me,’ ‘Dixie,’ and ‘The Stars and Stripes Forever.’ How the soldiers’ bosoms will swell at the thought that they are being led into the strife by a machine!” (Sousa 1906).
That children and soldiers were for Sousa the categories most affected by the mechanical reproduction of music, indicates that his concerns were went beyond aesthetics, and instead were due to the loss in human connection. Intentionality was for Sousa essential to the experience: without it, music would be only an empty entertainment.
Interestingly, Sousa also worried about the social implications of replacing live music with recordings, fearing a decline in amateur musicianship and the loss of music as a shared social activity. He also raised issues of copyright and fair compensation for composers, anticipating many of the legal and economic debates surrounding AI-generated content today.
The Vatican’s stance on mechanical music in religious settings provides another interesting historical parallel. In 1903, Pope Pius X issued the motu proprio “Tra le Sollecitudini” (“Among the concerns”) which, among other things, banned the use of piano and percussion instruments in church and emphasized the importance of Gregorian chant. While not directly addressing mechanical reproduction, this document, by forbidding modern music, was also excluding its admissibility. Interestingly, in those same years an Italian priest and inventor, Father Angelo Barbieri, invented a new type of automatic organ and worked hard for its invention to be accepted by the Pope. The fascinating story is reconstructed by Farabegoli and Gillin (2023) and it reflects the Vatican’s deep concern about maintaining the sanctity and human element in religious music in the face of the advent of mechanical reproduction.
After a long and intense campaign, Barbieri received the nihil obstat and his automatic organ, called Cantantibus Organis, was accepted to be used during the liturgy. What is interesting when considering this story in connection to the present debate on AI authorship and creativity, is the explanation provided by Monsignor Alfonso Carinci: “the use of this apparatus requires human action, and in many cases is able to conveniently accompany the religious services, which else would not be possible on account of the lack of an organist” (Farabegoli and Gillin 2023: 188). The automated organ was deemed acceptable because it required a human operator, and only in absence of an organist available.
Artistic creativity
AI and big data
AI system and technologies are increasingly being used to generate artworks that are indistinguishable from those made by human artists (Gangadharbatla 2021). AI-generated artworks raise questions of artistic creativity and human consciousness, thus inviting a reflection on the role of the arts in shaping our understanding of AI. Moreover, they investigate the link between artistic expression and consciousness (do we need one in order to make good art?) and invite people to empathise with AI agents, whose ‘interiority’ is in fact an art show. Some such experiments are discussed in mainstream media: this was the case, for example, of a 2018 painting created with the help of generative adversarial networks (GANs), which was auctioned for $432,500 by Christie’s (Kinsella 2018). More recently, in November 2021, the humanoid robot-artist Ai-Da, which is capable of painting, sculpting, drawing her self-portrait, made the news after the Ashmolean Museum in Oxford hosted its performance of poems “she” composed in response to Dante’s Divine Comedy (Flood 2021).
While these are only some of most sensationalist instances of artworks dealing with AI, they are nonetheless showing the extent to which the arts influence the public discourse on these themes and orient people’s understanding of AI impact and significance. Indeed, because AI is profoundly transforming a wide range of creative industries, from music and literature to fashion, the arts are today deeply invested in the debate on the need for a more ethical, human-centred, inclusive approach to AI (Srinivasan and Uchino 2021; Stark and Crawford 2019).
One of the crucial topics for discussion is the new definition of authorship in AI-generated arts (Ginsburg and Budiarjo 2019; Samuelson 2020). As AI systems are now capable of producing a painting, a song, or a novel, ethical and legal implications follow. Moreover, the cultural implications of entrusting the work of imagination to AI systems are currently being discussed. Within the current debate, one side apparently believes that meaning comes from the audience, who projects its expectations onto the work of art and interprets it against its pre-existing knowledge and experience (Miller 2019). Whether the author is human is simply immaterial. The other side does not accept the idea that we can connect, identify, and empathize with a work of art whose author is not an animate, conscious being (Kelly 2019). Beyond existential questions, concerns are being raised regarding which ethical values should guide AI-generated artistic creations, given that software and platforms are almost universally controlled by corporations (Anantrasirichai and Bull 2021). Finally, from the legal and economic perspective, many are discussing the pressing questions regarding who owns the rights of an AI-generated artistic product and who is the true author—the artist, the software engineer, the AI system, the corporation owning the system (Epstein et al. 2020).
Another central problem concerns the issue of transparency, raised in connection with the issue of Black Box AI (Bleicher 2017; Winfield and Jirotka 2017). This is a pivotal issue for artists dealing with AI, irrespective of whether they want to meaningfully engage with these technologies or if they need to use them to promote and sell their art. Understanding their functioning, as well as their economic and ethical implications, is essential. This has led many to advocate for the so-called Explainable AI (XAI) model, which allows developers as well as users to interact with the system and always have a working understanding of the running processes (Ramakrishnan 2020). In relation to transparency, the arts have the capacity to shed a light over what is otherwise invisible through any other critical lens—for example, the many latent and hidden patterns in the operation of algorithms. Thus, scholar Fabian Offert (2019), has argued that the most important explanation on how to distinguish real from AI-generated images is the one offered by the media artist Kyle McDonald in his article “How to Recognize Fake AI-Generated Images” (2018). Offert then adds that “the critical potential of AI art” is “to use AI to criticize itself, as a technology used in the real world” (2019). Transparency is thus necessary to artists to fruitfully profit from the technical resources offered by AI (XAI). At the same time transparency is also their goal, since many artworks engaging with AI aim at exposing and criticizing their hidden flawed and problematic aspects. The arts can thus be the middleman between society and AI technologies: translating concepts and ideas back and forward, pushing for innovation, warning about risks, thinking outside the box.
Finally, artists are contributing to the shaping of a more inclusive approach to AI design that can offer greater access to historically marginalised groups. A relevant precedent is the applications of AI and Augmented and Virtual Reality technologies to art creation and consumption. These technologies have the potential to reduce the need to master physical skills needed to create art (Hayes 2018). An inclusive approach to AI design can offer immense possibilities for artists in different fields, from music, to writing, and visual arts. This will be an addition to the current market since the possibilities in the purely physical world catering to the needs of people with disabilities are extremely limited.
Beside the specific applications, these questions on authorship, transparency, inclusivity, which are being raised within the art field have to do with general issues concerning the impact of AI on human agency, creativity, and identity. Their wider scope, coupled with the fact that artworks generally invite more interest and engagement from the general public than academic literature and scientific debates, explains why in the last few years there has been such a growing interest in AI art in the media as well as in the public discourse.
Past examples
The current debate on the relationship between art and technology is dominated by the issues raised by AI regarding the notion of creativity as a human prerogative and the discourse around the definition of authorship as the expression of a subjectivity endowed with consciousness and agency (Gangadharbatla 2021; McCormack et al. 2019). The origins of this critical debate, however, can be traced back to the first advent of electronic computers in the immediate post WWII period and to the birth of the related fields of investigation of Information Science and Cybernetics (Apter 1969).
This was a crucial phase. The advent of cybernetics changed the idea that only humans and animals have the ability to exchange information, learn, evolve, and self-reproduce. Machines too, cyberneticists maintained, could be programmed to do the same, at least theoretically. In 1948, Norbert Wiener laid the foundation for the new field in his pivotal book Cybernetics: Or Control and Communication in the Animal and the Machine. At the core of cybernetics, he maintained, was an equation between biological subjects—human and animal—and cybernetic machines based on their common ability to share and receive information—the ‘feedback loop’. One simple example that Wiener provided is the thermostat, which obtains information from the environment (the temperature) and responds by increasing or decreasing the heat in accordance with the pre-set temperature (its pre-existing knowledge). It was upon these foundations that, a few years later, the field of AI was officially born at the 1956 summer workshops organized at Dartmouth College (Kline 2011). For the first time in history, the equation between human and artificial actors, postulated since the 18th century on a mechanistic basis (La Mettrie 1747) was now based on the hypothesis that artificial agents could reproduce human mental activities, included the ability to display creativity and to produce art. It is telling that the father of Artificial Intelligence studies, Alan Turing, whose well-known Imitation Game was supposed to verify the effective indistinguishability between human and artificial intelligence, provocatively declared that “a sonnet written by a machine will be better appreciated by another machine” (Hodges 2012: 420). For him, the success of an AI poet was a matter of reception and not of its creative skills.
The revolutionary scope of this technological progress was immediately registered in all artistic fields. Examples of artistic approaches to intelligent systems and machines include the art installations of interactive machines by the British cybernetician Gordon Pask (Werner 2019); the research on computer and generative aesthetics accomplished by philosopher Max Bense and the Stuttgart group (Nake 2012); the collaboration between the Italian cybernetician Silvio Ceccato, writers Leonardo Sinisgalli (Pogliano 2011) and Dino Buzzati (Lima 2023a), and the visual artists of Gruppo V (Nicolini and Semprini 1998); the work on computer-generated literature and video games within the Parisian group Oulipo conducted by programmer, poet, and songwriter Paul Braffort (Blachet et al 2020; Braffort 1998); the Japanese Computer Technique Group, composed of IBM programmers who experimented with computer graphics (Gristwood 2019); the Zagreb-based collective of artists involved with the journal bit international (1968-72) (Margit 2011); the application of cybernetics to Concrete Art by the Brazilian group Noigandres (D’Ambrosio 2018: 54; Walther-Bense 1996); the collaboration between IBM and the American choreographer Jeanne Hays Beaman (Sagasti 2019).
The active involvement of the arts was facilitated by the highly interdisciplinary nature of the cybernetic field, which brought together mathematicians and linguists, computer and information scientists, social scientists, psychologists, as well as artists. Examples include the famous Macy Conferences dedicated to cybernetics (1946-1953), whose goal was to “promote meaningful communication across scientific disciplines” (von Foerster 1952: VII). The unifying goal in all these different approaches was the desire to question and problematize the distinction between human and technological actors and to analyse the systems regulating their interaction. Between the rise of cybernetics in the 1950s and its decline in 1980s (Kline 2015), several artists from all over the world, experimenting with different languages and media (visual arts, literature, music, performance arts, graphic design), were involved in pioneering collaborative projects dealing with intelligent machines and AI systems (Reichardt 1971; 2018) along with programmers and computer scientists, often sponsored by tech companies (e.g. IBM, Siemens, Bell Laboratories, Olivetti) and research institutes.
What artists offered to the nascent fields of AI was not simply a cultural commentary on the impact of ‘intelligent machines’ in art as well as on social life at large. Rather, they contributed to the development of many core issues that were, and still are, crucial to understanding the role and applications of AI role. For instance, research on the nature of human creativity and its link to intentionality and consciousness was developed through artistic experiments with combinatory logic in literature, music, dance, visual art. In these experiments, the execution was entrusted to the computer, while the artists acted as programmers setting in motion a creative process that they mastered only in part. Furthermore, studies on the functioning of the human brain, understood as a machine whose processes were identifiable and therefore reproducible, allowed some artists to conceive their works as creative experiments aimed at testing and expanding the limits of human perception on a scientific basis. Finally, the art world offered important critical analyses of some of the theoretical foundations of cybernetics. For example, the theories elaborated by Norbert Wiener and the mathematician Claude Shannon on information systems were adopted by semiotician Umberto Eco to develop his poetics of the ‘open work’ (Eco 1962). The philosophers Max Bense and Abraham Moles, founders of the Stuttgart Group, contributed to the discussion on the nature of intelligence and creativity through their research on computer and generative aesthetics (Klütsch 2012).
There were thus a multiplicity of reasons and interests that led artists from all over the world and working with different artistic languages and techniques to address the questions raised by the advent of ‘intelligent machines’ and to undertake collaborations with engineers and computer scientist that shaped AI future understanding and cultural impact.