Project Description

Ferocious Logics: Unmaking the Algorithm – rather than beamed down from above, decision making is increasingly embedded in ubiquitous computation, governing not just who gets to fly or has a loan approved, but a much broader array of social, cultural and labor activities. This PhD project seeks to unravel these algorithms as ecologies of matter: code and data, but also interfaces and protocols, bodies and soil, minerals and architectures. Four ecologies are unpacked: Uber, Amazon Echo, Airbnb and Palantir. Alongside this theoretical strand, a practice-based strand creates new algorithmic artworks. These prototypes are objects comprised of code, rich media, and other materials presented in exhibitions or online which attempt to critique existing structures, instrumentalize errors and speculate about alternative logics.

The Objects

  • Airbnb is a “peer-to-peer online marketplace and homestay network that enables people to list or rent short-term lodging in residential properties, with the cost of such accommodation set by the property owner.”
  • Uber is an online transportation network platform which connects passengers with drivers. Drivers are termed Partners and use their own vehicles.
  • The Echo is a “hands-free speaker you control with your voice. Echo connects to the Alexa Voice Service to play music, provide information, news, sports scores, weather, and more—instantly.”
  • Palantir (Gotham) is a software platform which provides the ability to store, query and visualize extremely large data sets, allowing analysts to discover patterns and relationships.

Unmaking: Thesis-Specific Methods

The major objective for the theoretical practice is to ‘unmake’ the algorithm. Although often considered a single object, algorithms can be productively analysed as ecologies. Their operations are embodied in an array of lively and disparate materials: technical, biological, textual, organizational, and so on. Existing research is often single discipline or single scale: low-level software analysis or high-level social implications. The result is an object which swings between the merely technical or the mysteriously political. In contrast, the ‘unmaking’ practiced here aims to unpack the forces diffused across materials and spaces which collectively constitute the agency of the algorithmic ecology. In other words, it unravels the ‘microphysics’ of the “control and use of an ensemble of elements” (Foucault, 1995, p. 184). To do so, it uses an interdisciplinary mix of four methods: archival analysis, design analysis, data analysis and fieldwork.

Remaking: Practice-Based Research

Remaking draws on the errors and excesses discovered in the theoretical ‘unmaking’, creating new algorithmic artworks in a practice-based approach. These artworks are not 1:1 recreations of the previous case-studies, but instead extrapolate upon the repressed affordances within them in order to explore new and alternative models of computation. Embedded in a range of contexts and presented to various publics, they in turn offer insights back to the theoretical strand of the project. Making machines is the development of algorithmic artworks which are technically functional, favoring action above representation. By privileging doing over depiction, they operate “directly in digital culture rather than make pictures of it” (Fuller, 2015).  Making visions is the design of algorithmic artworks which are speculatively rather than technically functional, allowing the viewer to imagine new modes of computation. They involve the strategic use of visual interfaces, behaviours and animations to form a design language which stands in for protocols and platforms which do not exist.