Feminist Data Politics: Quantifying Bodies
From Gender and Tech Resources
Revision as of 13:18, 12 June 2017 by Alex
|Title of the tutorial||Quantifying Bodies: From Sara Baartman to Menstruation Apps|
|Kind of learning session||Gender and Tech, Other …|
|Duration (hours)|| Two|
"Two" is not a number.
|Learning objectives||This session falls under the theme 'Feminist Data Politics'. It aims to give participants a background and orientation to how 'big data' is not new, but emerges in the 19th century. In this session participants will explore the data collection by menstruation apps and think critically about what this means for a feminist politics of big data.|
|Prerequisites|| - Presentation of history/background to what we mean by 'quantification' in the context of big data
- Menstruation apps: Select from the list here: http://arrow.org.my/wp-content/uploads/2016/08/AFC22.1-2016.pdf pages 16-21 . We used Clue, Glow, and Kindara, - Develop a list of questions you want the group to explore (listed in the next section on methodology)
|Methodology|| Begin session with giving some context to the history of quantification of bodies in 19th C Europe. Always good to customise this with a lot of local examples and contextually relevant material, for example, in the Asian GTI, we used examples from the colonial history of the region.
- Europe, 1800s-1900s – through industry, scientific advancement etc human knowledge and grasp of various anatomical realities – an idea of God was displaced. There was an explosion of ‘rationality’, ‘scientific’ truth... While mathematics is ancient, the way of cataloging and organising information is relatively modern that started in this period. Thus a growth of libraries, cataloging systems, indexing systems, field guides, and so on.
- These advancements in discovery, invention, science - These times were also marked by slavery and colonial empires - All these ideas of development, change, transformation etc changed the European mindset – they came to think of themselves as superior. This is known as Social Darwinism. - How does a society or social
The facilitator said we often think that technology is responsible for creating certain effects. But you learn to unlearn this idea – actually tech is not really shaping society but also society is shaping tech back. The facilitator said she believes that there was no such thing as ‘white people’ before technology was invented to measure bodies. The idea is that race, gender and the bodies are shaped by technologies which tell us that these are our bodies etc.
- She talked about the onset of the idea of ‘efficiency’ – and that anyone outside of being able to provide this efficiency and productivity was seen as outside normality, and outside and deviant to society. Criminals, prostitutes, the mentally unwell etc. these people were social ‘deviants’ and there was also an interest in carrying out scientific testing and experiments on these deviants to ‘understand’ them better.
- Bertillonage: started studying criminal’s bodies in prison to try and discern patterns between the physical make-up of criminals and the crimes they had committed.
- The facilitator spoke about Sarah Baartman: women like her were brought and exhibited; bodies which were considered outside ‘the norm’. MOVIE: Venus Noir
In Asia, while the above was documented more in the African context, the colonisers did census and gathered finger-prints to gather knowledge about the ‘natives’.
The facilitator spoke about the medium of photography and how it was a vital but also a volatile medium, historically speaking. Because of the way light bounces of different kinds of skin, early photography technology was built for white skin. People of color were not a part of the imagination of building this technology. She also brought up a more recent example of the new Apple watch – which was designed to bounce light off your skin and send it information. A journalist, Madrigal, discovered that it was somehow malfunctioning for people of color and then discovered that it was only tested, pre release, on the Apple CEOS all of whom are white.
The facilitator then went on to describe how these technologies have evolved and the present situation that we are in, as a basis to predict the future. We move now into the present day of technology-based quantification methods.
The body becomes the best way to prove your identity, it becomes a very clear marker. Body scanning, facial recognition, fingerprinting, biometric databases etc. India has constructed the world's largest biometric database, called Aadhaar, and has recently dicussed with Facebook about linking it together, which raises a lot of concerns. Body scanning, which is now a standard in airports, actually is optional and we can opt out, but many people simply don't know about it.
At the same time, the Quantified Self Movement sought to bring the control and power of quantification to the self; to quantify the self, to gather this knowledge as ‘self knowledge’. It started in 2007, founded by Kevin Kelly and Gary Wolff, were editors of Wired Magazine.
The tradition of gathering information about the body, for patterns, for sorting, identifying etc goes back to history – technology has changed the way we do it. The newer technologies of FitBit etc are self-tracking, self-quantifying modes and methods. If we share FitBit data with insurance companies, we can actually get lower premiums. But who owns this data? How secure is this data? To creatively counter these narratives, there are two artist projects which challenge the notions of personal quantification. 1. UnFitBits: Spoofing and asking questions? Are you your data and should you be accountable for your data? 2. Smell Dating: Everything can be quantifiedUnFitBits
The facilitator, in closing, that we must reflect on are we only our data? Are we accountable as determined by our data? And many of us feel differently about how much we want to hide / reveal.
Exercise: Exploring Menstruation Apps
Ask participants to get into as many groups as there are apps to discuss; generally, it works well to have 4-5 people per group.
Each group should be assigned one app from the list mentioned in the Arrow journal (see resources below) OR identify new/current/local apps based on your own knowledge of the landscape.
- What the app does - What kinds of data it collects about the user - Where the data is stored - Who owns the data and what they do with it - Who made the app, and what are their motivations for it?
Once the groups have completed the exercise, bring everyone back together for a feedback and review session.
|Number of facilitators involved|| 1-2|
"-2" can not be assigned to a declared number type with value 1.
|Technical needs|| Phones with apps loaded
|Theoretical and on line resources|| http://arrow.org.my/wp-content/uploads/2016/08/AFC22.1-2016.pdf
https://chupadados.codingrights.org/menstruapps-como-transformar-sua-menstruacao-em-dinheiro-para-os-outros/ ('Chupadados' by Coding Rights)