Difference between revisions of "DATS 6450 — Data Science Ethics"
From Simson Garfinkel
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Course Materials: | =Current Course= | ||
* [https://drive.google.com/open?id= | Fall 2020 Course Materials: | ||
* [https://dashboard.wikiedu.org/courses/George_Washington_University/DATS_6450_-_Data_Science_Ethics_( | * [https://drive.google.com/open?id=1GXMASmf7x_oOMqv9mJ1z5O-o55lz3lJj Fall 2020 Syllabus] | ||
* [https://drive.google.com/open?id= | * [https://dashboard.wikiedu.org/courses/George_Washington_University/DATS_6450_-_Data_Science_Ethics_(Fall_2020) Wikipedia Course Dashboard] | ||
* [https://drive.google.com/open?id=1f00aXyFcUQvuA2wFioxFpAXaNdUPjNH3 Public Google Drive] | |||
=Sources= | |||
==Ethical Framework Sources== | ==Ethical Framework Sources== | ||
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* What should be the data science oath? | * What should be the data science oath? | ||
=Labs= | ==Labs== | ||
==Lab 1 - Word Embeddings== | ===Lab 1 - Word Embeddings=== | ||
* [https://github.com/simsong/debiaswe Debaiaswe - instructor's fork] | * [https://github.com/simsong/debiaswe Debaiaswe - instructor's fork] | ||
* [https://www.aclweb.org/anthology/D18-1521 Learning Gender-Neutral Word Embeddings], Jieyu Zhao, Yichao Zhou Zeyu Li Wei Wang Kai-Wei Chang, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 4847–4853 Brussels, Belgium, October 31 - November 4, 2018. | * [https://www.aclweb.org/anthology/D18-1521 Learning Gender-Neutral Word Embeddings], Jieyu Zhao, Yichao Zhou Zeyu Li Wei Wang Kai-Wei Chang, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 4847–4853 Brussels, Belgium, October 31 - November 4, 2018. | ||
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* https://towardsdatascience.com/gender-bias-word-embeddings-76d9806a0e17 | * https://towardsdatascience.com/gender-bias-word-embeddings-76d9806a0e17 | ||
* https://arxiv.org/pdf/1806.06301.pdf | * https://arxiv.org/pdf/1806.06301.pdf | ||
=Previous Years= | |||
==Fall 2019 Course Materials== | |||
* [https://drive.google.com/open?id=1sKO1ZIyYll0xX5m3zt_Q-joTGzvaRU92 Fall 2019 Syllabus] | |||
* [https://dashboard.wikiedu.org/courses/George_Washington_University/DATS_6450_-_Data_Science_Ethics_(Fall_2019)/home Wikipedia Course Dashboard] | |||
* [https://drive.google.com/open?id=1HTOVVErtGhaoJbasel8gWbUgAnq467o4 Public Google Drive] | |||
Revision as of 03:32, 28 April 2020
Current Course
Fall 2020 Course Materials:
Sources
Ethical Framework Sources
- ACM Code of Ethics
- IEEE Code of Ethics
- IEEE Ethically Aligned Design, First Edition, "The most comprehensive, crowd-sourced, global treatise regarding the ethics of autonomous and intelligent systems available today."
- USACM Statement on Algorithmic Transparency and Accountability, January 12, 2017
- US National Privacy Research Strategy, June 2016
Other Sources
- Against Human Exceptionalism: Environmental Ethics and the Machine Question, Migle Laukyte, Springer International Publishing
- Crash: how computers are setting us up for disaster, Tim Harford, The Guardian.
- Ten simple rules for responsible big data research, Matthew Zook , Solon Barocas, danah boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale, March 30, 2017
Questions
- What should be the data science oath?
Labs
Lab 1 - Word Embeddings
- Debaiaswe - instructor's fork
- Learning Gender-Neutral Word Embeddings, Jieyu Zhao, Yichao Zhou Zeyu Li Wei Wang Kai-Wei Chang, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 4847–4853 Brussels, Belgium, October 31 - November 4, 2018.
- Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings,
- Removing gender bias from algorithms, The Conversation, James Zou, Assistant Professor of Biomedical Data Science, Stanford University,
- https://www.technologyreview.com/s/602025/how-vector-space-mathematics-reveals-the-hidden-sexism-in-language/
- https://towardsdatascience.com/gender-bias-word-embeddings-76d9806a0e17
- https://arxiv.org/pdf/1806.06301.pdf
