#computationalaesthetics

A reflective summary of Patricia Clough’s paper (of the same title).

As a result of the expansion of digital technologies and the commodification of human processes, art has become ever more entwined with the market. This poses a challenge for art insofar as it is conceived as a form of politics, as it is its very independence from the market that underwrites its capacity to provide legitimate political criticism.

In order to overcome these challenges the manner in which commodification operates must first be reconsidered in light of modern markets. Commodities are no longer simply things to be consumed, they are objects designed to transform the capacities of their users through their use. Productivity apps promise to enhance the output of those who pay the subscription; market insights increase company profits by providing them with better understanding of their customers’ behaviour. Market insights, as an example of big data, illustrate the dual aspects of the challenge: big data and the algorithmic architectures that aggregate and process it not only commodify human processes, they do so via the use of digital technologies. These algorithmic objects thus serve as instructive examples.

How might art engage with such objects? Graham Harman's metaphysics can provide us with some clues. Harman has argued that while objects are distinct from their properties, it is through their properties that objects enter into relations with one another and (in virtue of these relations) change. Indeed, what we here refer to as an object’s properties simply are its internal potentials to enter into relations with other objects, including those potentials inaccessible to human thought prior to their actualisation. That is, novelty is latent in objects regardless of how humans relate to them, and requires discovery. This is held in opposition to the view maintaining that novelty originates in human thought, requiring transmission from the originating subject to others via intermediate objects conceived as passive and malleable vehicles, devoid of potentiality in themselves.

Considering algorithmic architectures in light of Harman’s theory of objects, we must view them not only in terms of the purposes humans have created them for, but also in terms of the novel capacities they contain in themselves. Not only do algorithmic trading platforms analyse statistical patterns in markets and thus enable traders to optimise their activities, their deployment in turn affects the markets they analyse, creating feedback loops ultimately giving rise to new patterns of market activity impossible to predict from prior models.

This recognition of the autonomy of objects, given political urgency via the diffusion of digital technologies through the market, has displaced the privilege presumptively assigned to human subjectivity in the genesis of the new. In the context of this displacement art can only function as politics by engaging with objects in a way that recognises their autonomous capacity to produce novelty, and without imposing its own assumptions about what these new possibilities may be. In other words, art must become a form of exploratory play. Through play art may foment the actualisation of the potentialities contained in objects, though it will not—cannot, even in principle—be aware of what those are before it sets out.

Notes:

In 1982 Ken Perlin was tasked by producers to come up with computer graphics rendering techniques that could be used in their upcoming pseudo live action film Tron (on my my personal favourite films). Ken would later write 196 lines of C code that would earn him an Academy Award among many other accolades. The algorithm would later be known of Perlin Noise.