What is this Reading list?
The reading list contains all the suggestions for what to read or watch, contributed by members of the Data Ethics Club community. We choose from this list what to vote on to discuss for future meetings. We’d also love it if this reading list was useful for other people in starting their own journal clubs, or for any other purpose.
🎤 = audio only
🕰️ = waiting for paper to drop
✅ = we’ve discussed it
🔒 = Not Open access
📺 = Watching/Listening material
 = A longer piece of work, we’d need to choose a chapter or section.
 = A shorter piece of work, perhaps to combine with something else
Note: reading materials appear once in the category we felt they fit best.
What is data ethics?¶
📺 AI, Ain’t I a Woman? - poem2 - suggested by Valentina Ragni
The nature of data¶
Algorithmic decision making¶
Suggested excerpt: Social Inequality Will Not Be Solved By An App
History of data science¶
Environmental costs and considerations¶
Quantifying the Carbon Emissions of Machine Learning and the ML CO2 Impact calculator - suggested by @JennyBrennan
Privacy and surveillance¶
Data ethics in the private and public sectors¶
Suggested excerpt: Executive Summary
UK Statistics Authority Landscape Review of Applied Data Ethics - :white_check_mark: 14th Apr 2021
Data science and research culture¶
ESR: Ethics and Society Review of Artificial Intelligence Research - suggested by @nataliethurlby - ✅ 8th September 2021
Ethics in action (the good and the not so good)¶
Structural injustice and individual responsibility 🎤 - suggested by Kamilla Wells
Chapter 7: “Show your work”
The description of “co-liberatory” projects in chapter 5: “Unicorns, janitors, ninjas, wizards and rock stars”
Sharing learnings about our image cropping algorithm (Twitter) - suggested by @ninadicara, see #64
Natural Language Processing (NLP)¶
Follow-up paper: Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them - suggested by @NatalieThurlby