From Text to Algorithm: Big Data’s Emerging Subject

If the 1980’s were synonymous with discussions of architecture as text - replete with accompanying language of interpretation, signs, and meaning - the 2010’s ushered in discussions of architecture and computation with a lexicon of data, algorithms and performance. The disciplinary backdrops of these frameworks differ dramatically. Textuality emerges from literary criticism, while architecture’s current guiding spirit assumes the algorithmic driven logics of Big Data. Whereas architecture as text focused on the very human-centric traits and practices of reading and reception, injecting data driven logics turns the discussion inside out to frontload information, emphasize production, and de-emphasize subjectivity. Big Data is a rapidly emerging cultural technology that goes beyond introducing new procedures into existing modes of cultural and scientific production, it embeds those into the core of operations. For architecture, this contributes something other than its next chapter in history. Rather, the advance of Big Data’s approach across disciplines disrupts settled domains of activity to raise the question: history of what? This paper seeks to discuss this historical shift through Althusser’s notion of ideology and its categorical construction of subjects. A central question in this is: What is the nature of the shift from text to algorithm and how does it transform the functioning of the subject that Althusser described as the central function of ideology. This question is of particular concern as the logic of big data moves from the sciences to redefine the arts and the humanities, potentially transforming or dislodging Althusser’s distinction between theory and ideology.