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Our first data science book club in Grenoble will be on the topic of unfair algorithms. We propose to read some of the sources below and meet at this event to discuss what we have read. You are welcome to pick from this reading list, depending on your interest and the time you have:

Main Book: Cathy O’Neil - Weapons of Math Destruction

Google Talk by Cathy O’Neil on her book: https://www.youtube.com/watch?v=TQHs8SA1qpk

Slides and notes summary of her book:
https://www.seas.upenn.edu/~cis399/files/lecture/l24.pdf
https://www.seas.upenn.edu/~cis399/files/lecture/presentations/Weapons_of_Math_Destruction.pdf

Interview with Cynthia Dwork:
https://www.quantamagazine.org/making-algorithms-fair-an-interview-with-cynthia-dwork-20161123/

Article by Stephanie Wykstra - Just How Transparent Can a Criminal Justice Algorithm Be?
https://slate.com/technology/2018/07/pennsylvania-commission-on-sentencing-is-trying-to-make-its-algorithm-transparent.html

Article by Hanna Wallach - Big Data, Machine Learning, and the Social Sciences:
Fairness, Accountability, and Transparency
https://medium.com/@hannawallach/big-data-machine-learning-and-the-social-sciences-927a8e20460d

FAQs
Why are we doing this?
There's a lot of good writing out there on ethics and one of the most important principles is to discuss and debate the ethical questions that surround data science and technology.

We hope these events will help people gain the tools they need to think about ethics in their jobs or other projects, or in encountering algorithmic tools in their everyday life. But if all you get out of it is some friendly discussion, that works too :-)

Do I need to be a data scientist to participate?
No. We'll have a mix of technical and non-technical reading material. The aim is to think about data science in a context of ethical impacts and consequences - and that affects everybody!

I have a brilliant idea for reading material/a theme! Who do I tell?
We love suggestions! Tell us at dataforgoodgr @ gmail.com

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