The Medium of Generative AI as Collective Consciousness
In an earlier post, I speculated on the idea of generative AI tools as a ‘probabilities paintbrush’ as a way of thinking about the medium of generative AI itself, rather than whatever media its output is embodied in. In this article, I push that idea further, taking those probabilities as manifestations of collective consciousness.
This discussion delves into how the foundational elements of generative AI art — data drawn from extensive digital collections — serve as a modern representation of collective consciousness. By examining the generative AI artist’s role and the nature of the medium itself, we uncover a nuanced dialogue between individual creativity and collective cultural output.
Generative AI operates by synthesizing and reinterpreting data from a vast array of sources, encompassing the creative endeavors of countless individuals. This process transforms disparate data points into a cohesive whole that reflects a broader, collective human expression.
The data sets used by generative AI algorithms can be seen as digital manifestations of our collective consciousness, echoing the concept of the collective unconscious proposed by Carl Jung. However, unlike Jung’s archetypes, which are static and universal, the collective consciousness of generative AI is dynamic, continuously evolving with each piece of data added and every piece of art created.
When contrasting generative AI with traditional artistic processes, a clear distinction emerges in the source of creativity. In conventional art forms, an artist’s imagination is influenced by their cultural environment, but the creative act is fundamentally individual. Generative AI, on the other hand, embodies a shift towards a collective form of creativity. The outputs generated by AI are not just influenced by collective data; they are direct products of this collective input, offering a new perspective on artistic creation that is fundamentally collaborative.
The role of a generative AI artist extends beyond creation to include the curation and manipulation of the dataset — the collective consciousness — on which the AI operates and produces its output. This adds a layer of complexity to the artistic process, where the artist engages in a dialogue with the collective data, shaping the conditions under which the AI generates art. This act of curation and interaction positions the generative AI artist as a mediator, exploring the intersections of individual creativity and collective expression.
Through the lens of generative AI, art becomes a meeting point for the diverse streams of human cultural and creative expression. This perspective challenges traditional notions of creativity and authorship, prompting a reevaluation of the interactions between individual artists and the broader cultural context. Generative AI art thus represents a convergence of individual and collective creativity, highlighting the interconnected nature of human artistic expression.
Incorporating generative AI into the artistic process not only offers a means to channel collective consciousness into creative outputs but also provides a unique opportunity to pursue contrarian strategies. By delving into the fringes of the dataset, artists can explore outlier outputs that diverge from the central tendencies of the collective data pool. This approach enables artists to not merely replicate the dominant narratives and aesthetic norms embedded within the dataset but to actively challenge and extend the boundaries of cultural expression.
Such contrarian strategies involve a deliberate engagement with the statistical and cultural margins of the dataset. Generative AI, with its capacity to navigate vast amounts of data, allows artists to identify and amplify these marginal, less represented aspects of the collective consciousness. By doing so, artists can unearth novel expressions and perspectives that might otherwise remain obscured within the mass of conventional data points. This method of exploring the dataset aligns with a broader artistic tradition of resistance, where the act of creation is also an act of defiance against prevailing norms and expectations.
Pursuing outlier outputs through generative AI necessitates a nuanced understanding of the algorithm’s mechanics and the underlying structure of the dataset. Artists must become adept at manipulating the AI’s parameters to skew its generative processes towards the edges of the data distribution. This could involve adjusting the algorithm’s bias towards underrepresented themes, styles, or ideas, thereby fostering a creative environment where the less dominant voices within the dataset are brought to the forefront.
By focusing on the margins, artists can challenge the algorithm’s propensity to reinforce existing cultural patterns, pushing against the gravitational pull of the dataset’s central probabilities. In doing so, they contribute to a dynamic cultural evolution, where generative AI becomes not just a mirror reflecting the current state of collective consciousness but a prism that refracts and reconfigures that consciousness in new and unexpected ways.
