July 7 2022 GM
Glitter Meetup is the weekly town hall of the Internet Freedom community at the IFF Square on the IFF Mattermost, at 9am EST / 1pm UTC. Do you need an invite? Learn how to get one here.
Date: Thursday, July 7th
Time: 9am EDT / 1pm UTC
Who: Chenai Chair
Where: On IFF Mattermost Square Channel.
- Don't have an account to the IFF Mattermost? you can request one following the directions here.
Where my data at - Building African feminist resistance to data practices
The discussion will highlight the recent project sponsored by internews on African feminist engagement with data practices. I will unpack why the project may be deemed feminist, the methodology, findings and finally the action points. The conversation will also be used to hear back from the African community on taking on feminist methodologies and engaging the feminist community.
Chenai Chair is the Senior Program Officer - Africa Mradi Innovation at Mozilla Foundation. She is an expert on the intersection of digital technology and gender. She has built her expertise with extensive experience in work that is focused on understanding the impact of technology in society through research and public policy assessment. Her work draws on principles of feminism in assessing digital technology. She has developed projects focused on privacy, data protection and AI as Mozilla 2019/2020 fellow -available on mydatarights.africa.
To start off, can you give us a little background on your project [www.mydatarights.africa "where my data at"]? When it began, why, and What were the issues/ opportunities regarding data rights, privacy, and surveillance that inspired this project?
- The project began in 2019 as part of my Mozilla Tech policy fellowship output. I was awarded the fellowship to look at AI in the African continent. I settled for South Africa and focusing on AI, privacy and data protection from a feminist lens to center women and gender marginalised groups. I was also tired of hearing data about the new oil and the 4th industrial revolution hype.
- The issues were that I started the project pre-covid and had to adjust for covid where data was all the hype. It was also timely because there was an issue people could relate to that affected their data.
What were your key goals and objectives for this project? And how did you use feminist methodologies to assess data practices in Africa?
- My key goals were to center marginalized communities to the discourse on AI which was more so focused on capitalist gain. I also wanted to provide an African feminist perspective to the discussion. I also wanted to take the opportunity to carry out independent research without concerns of meeting funder requirements.
- I used feminist methodologies by drawing from different schools of thought to develop and approach that could somewhat work in the South African context I was focusing on. The feminist framing drew from data feminsim, intersectionality, data justice and feminist principles of the internet.
- Funding dynamics can really impact what you really care about vs what you have to deliver and that's a big challenge for people who might not have enough foundation and still need funding support to get by.
How did these framings help you contextualize the work to the location you were studying? i.e. any lessons that were particularly interesting?
- First of all I had to really nuance the context of gender inequality in South Africa. This for me is a feminist practie for centering context so that you are not writing from an abstract view. I also took on an approach of honoring the participants time by giving them an honorarium for their participation in the survey. I also approached this project as a collaborative piece of work - drawing on experts from multiple fields.
- The lessons that were interesting were about how easy it is to get swept up in technical jargon and you miss people's understanding of issues. I also saw the value of the network and feminist movements when people were comfortable with referring each other to participate in the work. Howver, it was also challenge to present this work in spaces of policy makers because of it being feminist work.
Did you find it challenging to budget for honorariums with funders?
- No, I think because Mozilla gave us a project budget that we advocated for our needs as fellows.
Is there a framework for centering context in research that you recommend?
- Intersectionality. An intersectional lens demands that you center context.
Have you been directly involved in policy conversations with big tech companies on AI & discrimination?
- I have not had direct conversations. We have shared pane stages with policy makers. I have had conversations with big tech companies. the main focus has been on women's safety and how limited their technology is in the African region
And what are in your opinion the main risks related to AI and content moderation for folks in South Africa?
- Main concerns in South Africa are replications of inequality that were in the apartheid era; increased surveillance under the guise of protection; and also limited moderation capacity that is responsive to context when it comes to hate speech and oGBV
It is amazing how many CCTV cameras exist in South Africa! Did your research look into this? And what were people's perception of privacy regarding the intense form of surveillance. Who was more surveilled?
- Oh yes, we actually did. The recent article by Karen Hao also covers this. Generally the surveillance cameras are in the high income areas and this may classify bodies seen as not belonging there as a potential threat. There also isn't enough information on how one can actually know in what database their face is showing up.
What are some of the examples of the harms caused by unregulated/unproven AI in Africa you came across in your research?
- My research looked more so at perceptions of harms. I wished I had the capacity to focus on one sector and followed through. I do want to point out that the AI/algorithm systems in the banking sector keep coming up as problematic in that they place punitive measures on historically marginalized groups when they try to access funds.
For disseminating the information on your project, you broke down the concepts and frameworks you used for the research and some of your findings. This is very creative. Why did you decide to take this approach?
- I wanted something that people could easily digest according to what they needed. This work had different audiences. I also thought, to address a problem I had - that is finding information.
What are some of the emerging African voices we should follow for work and activism focused on AI?
- Mardiya of course but I also curated this list and you can see who to follow.