Cybernetic Auto-ethnography

Cybernetic Auto-ethnography

In the following explanatory statement for Critical Intervention 03, I will demonstrate that I have used Cybernetics Theory and data analysis as a qualitative research tool. In particular, I will evaluate the worthiness of data analysis as a method to interpret colour data results from a series of photographs collected over a three-week period.

In her article, ‘Beginning to Explore City Spaces’, Roanna Heller recounts a summer she spent in Berlin: ‘There I had lain on my back in Mauer Park, on short, dry grass absorbing the city through my limbs’ (Heller: 2005: 133). She goes on to explain how unappealing her hometown of Sheffield felt upon her return, and that compared to Berlin, Sheffield left her feeling unconnected and disengaged (Heller: 2005: 134). Drawing upon the work of Dr Alan Latham, a geographer at University College, London, Heller argues that some spaces are simply unengaging and lack opportunities for social interaction (Heller: 2005: 134).

I found that Heller’s argument resonated in aspects of Amanda Thomson’s lecture, ‘Landscape and Ethnography’. As such, I aimed to discover if the extent to which we engage with cities is not simply attributable to how the city presents itself, but is also dependent on our own actions (Heller: 2005: 133). In her lecture, Amanda Thomson states that,

‘Typically, The field is some place other, and archetypically anthropology is researchers from the west investigating other people, not from the west. As anthropology has evolved, the separation between self and research has become closer and closer, and sometimes its more interesting to not separate who we are and the people we are working with, suggesting a more collaborative approach. The field can be set by researchers ourselves, the parameters of which can be set by our interests’.

With this in mind, my method of exploring my hometown was to situate myself at the centre of an anthropological investigation of my city’s landscape. The intention was to focus on my surroundings in new and different ways, creating a system for observing, and feeding back observed information, in order to create a visual analysis based on cybernetics theory.

Coming from the Greek word meaning ‘the art of seeing’, cybernetics, at least in the modern era, was popularized by mathematician Norbert Weiner who wrote, Cybernetics: Communication in the Animal and Machine in 1948. Weiner described cybernetics as an: ‘analysis of society in terms of messages, in which the faculty of communication between man and machine allows us to understand the universe as a probabilistic, organic information system’ (Weiner: 1954). We can interpret cybernetics as being about epistemological goal-based objectives achieved through a system of feedback and interpretation.

In this particular instance, my goal has been to create a data based analysis of my life for twenty-one consecutive days from 1st May through 21st May 2012. Part of the feedback process was to take a photograph from my exact location, at mid-day (or as close to as was possible) facing precisely north. The tools for this endeavour were a compass and a camera, both came in the form of a smart-phone. Historically, cameras have provided anthropologists with an invaluable tool to collect and present social reality differently, ask different questions, and represent findings in new ways (Leavy: 2009: 230).

My photographs were taken using observer-as-participator research methodology (Bryman: 2004: 304). Using self-authored software, statistical sampling was used over sixteen equidistant points in each photograph to obtain accurate colour information as it was distributed about the photograph. The system dictated that the colour information for each of the sixteen points should be converted to a red (R), green (G) and blue (B) hex value. Each value had a numerical attribution between 0 and 255.  Once the data was collected and stored, the values were converted to points on an XYZ axis: R became X, G became Y, and B became Z. This process was repeated for all of the sixteen points, where a single line to create a vertex shape connected the coordinates. The resulting shape is a data visualisation of the colour contained in the photograph, or a graphical representation of a north facing direction from my position at 12 pm.

Holm (2008) notes the increasing prevalence of data-visualisation as a methodological approach to interpretation. The results of this critical intervention show that by using visual interpretation methods of analysis, the data is open to multiple interpretations and perspectives. In reflecting upon my participation in this research, I would disagree with Heller (2005) and argue that all spaces present the opportunity for engagement based on human agency and subjectivity. The requirement to take a photograph each day at a specific time stimulated a spatial awareness and provided a purpose for observing and recording my surroundings. The use of Cybernetics Theory in ethnographic research provided a visual interpretation of the social world using a system of data analysis. This produced unique visual artefacts, which represent a subjective and active engagement with the city landscape.

Bibliography

BRYMAN A, Social Research Methods, 2004, UK, Oxford University Press Inc.

(Ed) GRIMSHAW A & RAVETZ A, Visualising Anthropology, 2005, UK, Intellect Books

HOLM G, ‘Visual Research Methods’, 2008. In HESSE-BIBER S. N. & LEAVEY P (Eds), Handbook of Emergent Methods, pp. 325-342, New York, Guilford Press.

LEAVEY P, Method Meets Art, 2009, New York, The Guilford Press.

THOMPSON A, Landscape and Ethnography, 16/04/2012

WEINER N, Cybernetics: Control and the Animal and the Machine, 1948, USA, MIT Press

WEINER N, Human Use of Human Beings: Cybernetics and Society, 1954/1986, UK, Avon

 

In the spirit of Open Source, please find my Processing sketch below.

 

PImage ethno;

import processing.pdf.*;

boolean record;

void setup() {

size(640,478, P3D);

ethno = loadImage(“your_image.JPG”);

}

void draw() {

if (record) {

beginRaw(PDF, “image.pdf”);

}

background (255);

stroke(0);

strokeWeight(1);

smooth();

noFill();

camera(mouseX, mouseY, 220.0,

0.0, 0.0, 0.0,

0.0, 1.0, 0.0);

beginShape();

for (int i =80; i<width; i+=160) {

for(int j= 60; j<height; j+= 120) {

color c = ethno.get (i,j);

float valueR = red(c);

float valueG = green(c);

float valueB = blue(c);

vertex(valueR, valueG, valueB)

}

}

endShape(CLOSE);

if (record) {

endRaw();

record = false;

}

}

void keyPressed() {

if (key == ‘r’) {

record = true;

}

}

 

 

 

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