Gender and Tech Resources - User contributions [en]

DataDetox

2017-06-20T13:53:11Z

Maya: Created page with "{{Tutorial |Title of the tutorial=The Data Detox Challenge |Kind of learning session=Hands-on Tools, Other … |Tutorial category=Anonymity & Circumvention, Mobile Phones, Soc..."

{{Tutorial
|Title of the tutorial=The Data Detox Challenge
|Kind of learning session=Hands-on Tools, Other …
|Tutorial category=Anonymity & Circumvention, Mobile Phones, Social Networking
|Duration (hours)=2 hours
|Learning objectives=To introduce participants to the idea of reducing their data traces by working through the Data Detox Kit. the DDK was developed as part of the My Shadow program for use and distribution in the Glass Room
|Prerequisites=Data Detox Kit projected/ downloaded / printed.
|Methodology=Introduction: (15 mins)

Start with the disclaimer: (and this is really key!)

- If you decide to do data detox please be aware that you may find information about yourself that you did not know was online, and this may be distressing for you.

We explain that this is structured as an eight day program, but we will only be doing a two hour 'taster' session to give people a feel of what it is like, and how they can continue to use it in their own locations.

In this session, we started by giving a background to the development of the DDKit within the context of Tactical Tech's Glass Room and My Shadow program; and the objective of this intervention and program to raise awareness about 'data shadows' and 'traces', what they mean, and how to control them in the interest of privacy. There are details about the Glass Room online here: https://tacticaltech.org/projects/glass-room and about data shadows and why they matter here: https://myshadow.org However, if you don't know much about the Glass Room, you can just start with MyShadow and what it is about, and the move to the Data Detox Kit.

Activity1. Intro to the Data Detox
(15 mins)

All the participants go to https://myshadow.org/ckeditor_assets/attachments/189/datadetoxkit_optimized_01.pdf and do the personal activity listed at the start and do the activity under 'Discovery: Day 1'.
. Familiarise yourself with the kit and its layout.

Participants feedback after activity:
- what did they feel?
- what did they discover?
- how much of this was new to them?
- what was the most surprising?

Activity 2
(20 mins)

- Get participants into pairs and assign each pair one of the days of the data detox kit. If there are a lot of people, you can assign more than one group a particular day. In the GTI in Malaysia in 2017, we focused on Days 2,34,5. Depending on how long the session is, you can increase it, ie do more sections of the DDK on a second day or later session
- Alert people to the Appendix section at the end that offers some helpful tips on how to find settings on various operating systems on their devices.

Report Back – 30 mins

- Each group reports back talking about what they learned, what they could and could not do (technically), the technologies or terms they need help with.

Activity 3. Brand New You.
( 15 mins) :

- Ask participants to form new pairs, or small groups of three people max.
- Ask them to look through Day 7 of the Data Detox Kit and talk about what they think is doable, or not, what they might want to do themselves,. and how they would practically go about it, what kinds of support they would potentially need, or skills, or information.
- Ask the group to report back, but not in detail, just about their discussion.

End of the session
|Number of facilitators involved=1
|Technical needs=Data Detox Kit downloaded and / or in print
Participants should have at least one of their devices with them ie a phone or a computer, or both.
Internet connection
|Theoretical and on line resources=The Glass Room project: https://tacticaltech.org/projects/glass-room
My Shadow project: https://myshadow.org and https://myshadow.org/detox
Data Detox Kit: https://myshadow.org/ckeditor_assets/attachments/189/datadetoxkit_optimized_01.pdf
}}

Feminist Data Politics: Quantifying Bodies

2017-06-20T11:30:36Z

Maya:

{{Tutorial
|Title of the tutorial=Quantifying Bodies: From Sara Baartman to Menstruation Apps
|Kind of learning session=Gender and Tech, Other …
|Tutorial category=Discussion
|Duration (hours)=Two
|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.

Presentation:

- 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.
- The interaction between society and tech; it is not just a one-way thing,that tech creates an influence on society, but societies also shape, and re-shape technologies.
- The emphasis on measurement, classification, numbering, naming, indexing led to the identification of norms, 'the normal', and outliers. This was not just about numbers, but was extended to people based on their behaviour. 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. They were also considered as not valuable to the 'efficient' direction in which early modern European society was going.
- One example of a sub-discipline developing within criminology was Bertillonage. Andre Bertillon started studying criminal’s bodies, physiognomy etc (size of head, size of ears, placement of ears on the side of the head, size of the lips etc) in prison to try and discern patterns between the physical make-up of criminals and the crimes they had committed, as well as compared to the general population.
- Another example that connects these practices with colonialism was the story of Sarah Baartman: she was brought from South Africa as an exhibit to the paraded, measured (movie reference: 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’.
- Photography developed as a medium, a volatile medium because it is so unstable, through which bodies were documented and identified. Present day examples of how race intersects with this unstable medium : the Apple watch, the Shirley Card for lighting in photography

The session then moves on to the present day, looking at recent practices of quantification and big data.

- 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.
- 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.
- Fitbits and Unfitbits 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.

Session then moves on to an 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.

Ask the group to spend 20 minutes finding out the following based on a review of the app, the privacy policy, and online searches

- 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
|Technical needs=Phones with apps loaded
Internet connection
|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)
}}

Feminist Data Politics: Quantifying Bodies

2017-06-08T13:58:57Z

Maya: Created page with "{{Tutorial |Title of the tutorial=Quantifying Bodies: From Sara Baartman to Menstruation Apps |Kind of learning session=Gender and Tech, Other … |Tutorial category=Discussio..."

{{Tutorial
|Title of the tutorial=Quantifying Bodies: From Sara Baartman to Menstruation Apps
|Kind of learning session=Gender and Tech, Other …
|Tutorial category=Discussion
|Duration (hours)=Two hours
|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.

Presentation:

- 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 cataloguing and organising information is relatively modern that started in this period. Thus a growth of libraries, cataloguing 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 colour 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 colour 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.

Ask the group to spend 20 minutes finding out the following based on a review of the app, the privacy policy, and online searches

- 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
|Technical needs=Phones with apps loaded
Internet connection
|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)
}}