Critical!

No reading this week, but a good watching. We will be talking about recommender systems, homophily, assortativity, weapons of math destruction, and more, starting from this 40 minutes (plus intro and question time) talk by Prof. Wendy H. K. Chun:

activity

  1. Prof. Chun identifies 4 key steps to overcome discriminating uses of data science. Summarise them with your own words. (< 4 lines)
  2. What is a recommender system? (< 4 lines)
  3. Prof. Chun talks in length about “homophily”:
    • What is homophily? Answer both pointing at the sociological meaning and at its algorithmic / data scientific meaning. (< 4 lines + some maths)
    • What issues (both scientific and ethical) poses the assumption of homophily in recommender systems? (< 4 lines + some maths)

additional material

(pick one of the following)

  1. Take a look at the work of Guillaume Chaslot, and the story as told in the MIT Technology Review: here
  2. Prof. Zeynep Tufkeci wrote a great piece for The New York Times about a recommender system and radicalization
  3. A great book is the one written by Prof. Safiya U. Noble, “Algorithms of oppression” (the intro is freely available here and the book is available in my office, just come get it!)
  4. Some data science: Prof. Walter Quattrociocchi and colleagues is performing extremely interesting research about the role polarization and echo chambers in social networks.