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1 Dec, 9 tweets, 5 min read
Reciprocity is a key part of life. Surveillance undermines reciprocity. Every time we opt for surveillance or extractive technology, we undermine reciprocity and relationship. -- @doxtdatorb #AgainstSurveillance
Between 1971-1974, a Detroit Police Department surveillance unit called STRESS (Stop The Robberies, Enjoy Safe Streets) fatally shot 24 people, 22 of them African-American @hypervisible #AgainstSurveillance
Teach-in Against Surveillance is happening now, with livestream:
eventbrite.com/x/teach-in-aga…
We are encouraged to confuse surveillance with care.

"The lie that is central to surveillance fetishists is that you can predict the future. Each time those predictions prove wrong, it's claimed that we just need more data." @hypervisible
Sharing hopeful stories: students at @Bali_Maha's university used @SheaSwauger's article to organize against online proctoring software in their department #AgainstSurveillance

hybridpedagogy.org/our-bodies-enc…
"EdTech is Carceral Tech. Often it's the same companies, the same practices, the same goals. It's important to talk about which technology should not exist." -- @hypervisible
This event is a fundraiser for Ian @Linkletter, the professor being sued by company Proctorio for criticizing them on social media. The GoFundMe for his legal costs is here: gofundme.com/f/stand-agains…

Background on the case in this article:
@Linkletter Talk by @Jessifer:
- conflict of interest when proctoring software companies claims cheating is on the rise, w/out data
- university budgets prioritizing surveillance over faculty & students
- how anxiety, food insecurity, & other stress impacts students

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More from @math_rachel

Rachel Thomas Profile picture
3 Dec
I have long admired @timnitGebru for her brilliance, moral courage, clear voice in speaking up for what is right, & influential scholarship. It is truly terrible that Google would do this.

In this thread, I want to share some of Timnit's work I love

I've quoted "Datasheets for Datasets" (2018) in many of my talks & assign it as reading in my class. It highlights decisions that go into creating & maintaining datasets, and how standardization & regulation came to other industries

arxiv.org/abs/1803.09010
Timnit worked with @jovialjoy on the original GenderShades research, which has had a profound impact on facial recognition, led to concrete regulations, and changed our industry

Read 12 tweets
Rachel Thomas Profile picture
1 Dec
A freelance journalist in Vietnam w/ 150,000 followers & a verified Facebook account realized all his posts about a high-profile death penalty case had vanished with no notification

amnesty.org/en/latest/news… Content removed without any...
“Imagine if you spent years & years growing your Facebook account, but then in one easy act, Facebook just erases all your work"

Facebook has blocked every post a pro-democracy activist has tried to post about Communist Party, with no option to appeal Nguyen Van Trang, a pro-dem...
More background in this LA Times article:
latimes.com/world-nation/s…
Read 7 tweets
Rachel Thomas Profile picture
19 Nov
There has been some great work on framing AI ethics issues as ultimately about power.

I want to elaborate on *why* power imbalances are a problem. 1/
*Why* power imbalances are a problem:
- those most impacted often have least power, yet are the ones to identify risks earliest
- those most impacted best understand what interventions are needed
- often no motivation for the powerful to change
- power tends to be insulating 2/
The Participatory Approaches to ML workshop at #ICML2020 was fantastic. The organizers highlighted how even many efforts for fairness or ethics further *centralize power*

3/
Read 11 tweets
Rachel Thomas Profile picture
18 Nov
My impression is that some folks use machine learning to try to "solve" problems of artificial scarcity. Eg: we won't give everyone the healthcare they need, so let's use ML to decide who to deny.

Question: What have you read about this? What examples have you seen?
It's not explicitly stated in this article, but seems to be a subtext that giving everyone the healthcare they need wasn't considered an option:

To be clear, if the starting point is artificial scarcity of resources, this is a problem machine learning CAN'T solve
Read 4 tweets
Rachel Thomas Profile picture
17 Nov
I'm going to start a thread on various forms of "washing" (showy efforts to claim to care/address an issue, without doing the work or having a true impact), such as AI ethics-washing, #BlackPowerWashing, diversity-washing, greenwashing, etc

Feel free to add more articles!
"Companies seem to think that tweeting BLM will wash away the fact that they derive massive wealth from exploitation of Black labor, promotion of white anxiety about Blackness, & amplification of white supremacy."
--@hypervisible #BlackPowerWashing

Great paper on participation-washing in the machine learning community:

Read 5 tweets
Rachel Thomas Profile picture
30 Oct
Thread of some posts about diversity & inclusion I've written over the years. I still stand behind these.

(I'm resharing bc a few folks are suggesting Jeremy's CoC experience ➡️ partially our fault for promoting diversity, we should change our values, etc. Nope!)

1/
Math & CS have been my focus since high school/the late 90s, yet the sexism & toxicity of the tech industry drove me to quit. I’m not alone. 40% of women working in tech leave. (2015)

medium.com/tech-diversity… 2/
Superficial, showy efforts at diversity-washing are more harmful than doing nothing at all. Research studies confirm this (2015)

medium.com/tech-diversity… 3/
Read 8 tweets

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