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new free online course: Practical Data Ethics, from fast ai & @DataInstituteSF covering disinformation, bias, ethical foundations, privacy & surveillance, silicon valley ecosystem, and algorithmic colonialism

cc: @craignewmark

ethics.fast.ai
As @cfiesler showed w spreadsheet of >250 tech ethics syllabi & her accompanying meta-analysis, tech ethics is a sprawling subject. No single course can cover everything. And there are so many great courses out there!

medium.com/cuinfoscience/…

cmci.colorado.edu/~cafi5706/SIGC… Slide showing paper title: "What do we teach when we te
I spent a lot of time trying to cut my assigned reading list down to a reasonable length, as there are so many fantastic articles & papers on these topics. The following list is not at all exhaustive.
Some great articles on mis/disinformation:

ribbonfarm.com/2019/12/17/med… @noUpside

medium.com/@guillaumechas… @gchaslot

onezero.medium.com/the-simplest-w… @holden

slate.com/technology/201… @heyydnae

psyarxiv.com/3n9u8/ @GordPennycook
Some great articles on bias & fairness:

@random_walker

arxiv.org/abs/1803.09010 @timnitGebru

arxiv.org/abs/1901.10002 @harini824

arxiv.org/abs/1901.02547 @samirpassi

arxiv.org/abs/1901.09749 @umaivodj
Some great articles on ethical foundations:

scu.edu/ethics-in-tech… @ShannonVallor

theatlantic.com/technology/arc… @ibogost

blogs.scientificamerican.com/observations/t… @zeynep

cc.gatech.edu/~beki/cs4001/W… @langdonw
Some practical tools you can use towards tech ethics:

scu.edu/ethics-in-tech… @ShannonVallor

arxiv.org/abs/1810.03993 @mmitchell_ai

ics.uci.edu/~djp3/classes/… @EricPSB

techpolicylab.uw.edu/wp-content/upl… @megyoung0
Some great articles on privacy & surveillance:

papers.ssrn.com/sol3/papers.cf… @alvarombedoya

urbanomnibus.net/2020/01/caught… @hypervisible

web.cs.ucdavis.edu/~rogaway/paper…

nytimes.com/interactive/20…

fastcompany.com/90447583/our-c… @LAM_Barrett

fastcompany.com/90317495/anoth… @deciara
Some great articles on broader trends & factors related to data ethics:

technologyreview.com/s/611806/how-s… @zeynep

papers.ssrn.com/sol3/papers.cf… @grimmelm

qz.com/1540608/the-pr… @timoreilly

ali-alkhatib.com/blog/anthropol… @_alialkhatib

tomslee.github.io/publication/ou… @whimsley
Some great articles re algorithmic colonialism:

reallifemag.com/the-algorithmi… @Abebab

nature.com/articles/d4158… @amymaxmen

theatlantic.com/technology/arc… @AdrienneLaF

docs.google.com/document/d/1wy… @ruchowdh
You can find the lesson videos for the Applied Data Ethics course starting here. There's an icon near the top right of the video that opens lesson notes & transcript search. ethics.fast.ai/videos/?lesson… picture of an icon (with a triangle and lines) that has a bo
Here is the webpage version of my applied data ethics syllabus, which contains all the above links:

ethics.fast.ai/syllabus/
And here is a blogpost about the new applied data ethics course:

fast.ai/2020/08/19/dat…
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Rachel Thomas
@math_rachel
Videos from @StanfordAIMI Symposium are up! I spoke on why we need to expand the conversation on bias & fairness.

I will share some slides & related links in this THREAD, but please watch my 17-minute talk in full (the other talks are excellent too!) 1/

Slide saying "AI, Medicine, & Bias: Diversifying Your D
While using a diverse & representative dataset is important, there are many problems this WON'T solve, such as measurement bias

Great thread & research from @oziadias on what happens when you use healthcare *cost* as a proxy for healthcare *need* 2/

Another form of measurement bias is when there is systematic error, such as how pulse oximeters (a crucial tool in treating covid) and fitbit heart rate monitors (used in 300 clinical trials) are less accurate on people of color 3/

Read 13 tweets
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Rachel Thomas
@math_rachel
Structural racism can be combated only if there is political will, not more data. Ending racism has to begin and end with political will. Data, while helpful in guiding policy focus, are not a shortcut to creating this will.

aljazeera.com/indepth/opinio… @InterwebzNani 1/ First, "proving" that racism exists is not the sam
Data are not merely recorded or collected, they are produced. Data extraction infrastructures comprise multiple points of subjectivity: design, collection, analysis, interpretation and dissemination. All of these open the door to exploitation. 2/ Second, data extraction can pose a threat to the rights of m
In South Korea, digital COVID tracking has exacerbated hostility towards LGBTQ people.

When UK researchers set out to collect better data on Roma migrants to assess social needs, missteps in data presentation gave rise to political outcry over an "influx" of migrants. 3/ In this context, we also need to consider the precedents we
Read 5 tweets
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Rachel Thomas
@math_rachel
Things to know if you work on medical ML:
- Medical data can be incomplete, incorrect, missing, & biased
- Medical system is disempowering & often traumatic for patients
- Crucial to involve patients & to recognize risk of how ML can end up further disempowering 1/
On bias in medicine (& thus medical data): research shows that the pain of women is taken less seriously than pain of men. The pain of people of color is taken less seriously than pain of white people.

Result: longer time delays, lower quality of care, & worse outcomes 2/
A meta-analysis of 20 years of published research found that Black patients were 22% less likely than whites to get *any* pain medication and 29% less likely to be treated with opioids 3/

bbc.com/future/article… There is particularly robus...
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