From data narratives to data fiction: against the speculative sufficiency of big data.
Lead Research Organisation:
University of Nottingham
Department Name: Culture, Film and Media
Abstract
My project studies the cultural nature and implications of big data, offering a philosophically informed,
transdisciplinary analysis of contemporary data practices, at a time when data is seen as a solution to
"everything." I explore data as a mode of mediation (rather than a form of representation), and focus on
the semiotic transformations at work in the processes by which it becomes meaningful information.
Drawing on Guattari's theorisation of mixed semiotics, I will study technological aspects of specific
data-oriented processes: surveillance, profiling, and predictive policing in order to follow the ways in
which data structures and algorithms produce meaning, generating data profiles as 'biased'
narratives. Traversing the computational and the cultural in this way, and drawing in turn on 'nonstandard'
forms of philosophy (Laruelle) and epistemology (Schmid), will then enable me to make a
more technologically informed challenge of the ethical basis for the authority granted to those data
practices.
The project draws upon research I pursued during my Master's degree as well as independent study
conducted since graduating. It will extend my discussion of Guattari's semiotic concepts in relation to
screen media (MA dissertation, paper given at Film-Philosophy Conference 2017). I have also
previously engaged in depth with the work of Laruelle (e.g. in a paper at Goldsmiths College, June
2017). The project has been informed by my participation in the Data Publics international research
project (http://datapublics.org/), which has facilitated my appreciation of the importance of the relations
between critical theory and data studies, particularly focusing on the implications of data for
contemporary geopolitics.
My project and research interests would also make a valuable contribution to, and will benefit
substantially from an involvement with the Digital Culture Research Network based at the University of
Nottingham, with whom I have already established contact.
transdisciplinary analysis of contemporary data practices, at a time when data is seen as a solution to
"everything." I explore data as a mode of mediation (rather than a form of representation), and focus on
the semiotic transformations at work in the processes by which it becomes meaningful information.
Drawing on Guattari's theorisation of mixed semiotics, I will study technological aspects of specific
data-oriented processes: surveillance, profiling, and predictive policing in order to follow the ways in
which data structures and algorithms produce meaning, generating data profiles as 'biased'
narratives. Traversing the computational and the cultural in this way, and drawing in turn on 'nonstandard'
forms of philosophy (Laruelle) and epistemology (Schmid), will then enable me to make a
more technologically informed challenge of the ethical basis for the authority granted to those data
practices.
The project draws upon research I pursued during my Master's degree as well as independent study
conducted since graduating. It will extend my discussion of Guattari's semiotic concepts in relation to
screen media (MA dissertation, paper given at Film-Philosophy Conference 2017). I have also
previously engaged in depth with the work of Laruelle (e.g. in a paper at Goldsmiths College, June
2017). The project has been informed by my participation in the Data Publics international research
project (http://datapublics.org/), which has facilitated my appreciation of the importance of the relations
between critical theory and data studies, particularly focusing on the implications of data for
contemporary geopolitics.
My project and research interests would also make a valuable contribution to, and will benefit
substantially from an involvement with the Digital Culture Research Network based at the University of
Nottingham, with whom I have already established contact.
Organisations
People |
ORCID iD |
| Andrew Goffey (Primary Supervisor) | |
| Magdalena Krysztoforska (Student) |