Week 7 - Data science ethics

Misrepresentation of findings, data privacy, and algorithmic bias 👩‍💻


  • Watch the videos
  • Complete the assignments
  • Complete the readings
  • (Optional) Submit your project re-proposal by 16:00 on Friday, 6 November


You have two options for watching the course videos, on YouTube or on MediaHopper. You can also find a playlists for all course videos on YouTube here and on MediaHopper here.

Some of the videos for this week are by “guest lecturers”, they’re labeled with a 🎤. The total length of the videos add up to more than the usual amount, so I recommend watching as much as of them as you’re interested – they cover highly important topics without being highly technical. You’re welcomed to skip the Q&A parts of these videos.

01 Keeping up with IDS: Week 7 17:06
02 Misrepresentation 22:15
🎤 Alberto Cairo - How charts lie 57:23
03 Data privacy 10:01
🎤 The Guardian - Cambridge Analytica whistleblower 13:03
04 Algorithmic bias 23:29
🎤 Joy Buolamwini - How I’m fighting bias in algorithms 8:44
🎤 Cathy O’Neil - Weapons of Math Destruction 33:39
🎤 Safiya Umoja Noble - Imagining a Future Free from the Algorithms of Oppression 33:22
🎤 Kristian Lum - What’s An Algorithm Got To Do With It 12:12


Due this week
Lab 04 UoE Art Collection Tue, 3 Nov, 16:00 UK
Feedback Peer evaluation 02 (emailed via TEAMMATES) Wed, 4 Nov, 16:00 UK
Project Proposal, take 2 (Optional) Fri, 6 Nov, 16:00 UK
OQ 06 Review Sun, 8 Nov, 23:59 UK
Due next week
Lab 05 Conveying the right message through visualisation Tue, 10 Nov, 16:00 UK
HW 03 Money in politics Thur, 12 Nov, 16:00 UK


📖 MDSR: Chp 6 - Professional Ethics Required
📄 Ethical challenges in online research: Public/private perceptions Optional
🖋 Algorithmic Unfairness Without Any Bias Baked In Optional


This week we reviewed data science project workflows.


Interactive R tutorials

No new interactive R tutorials this week. If you haven’t completed last week’s, this is your chance to catch up!