This week in Quant Humanists, we are going to do a group feedback session for our upcoming final projects (next week!).
We will also have a look at how we evaluate ourselves, from which lenses we see ourselves and the world, how data can reinforce or upend our biases, and what it means to scope our self-analyses so that they are accessible and understandable to others in the community.
- Final Project Mid-reviews
- Course Evaluations!
- SLIDES URL
- Murphy, Heather., Why Stanford researchers tried to create a ‘gaydar’ machine
- Ruckenstein, Minna., Visualized and interacted life: Personal analytics and engagements with data doubles
- Hill, Kashmir., Facebook figured out my family secrets and it won’t tell me how
- Hudson, Laura., Technology is biased too. How do we fix it?
- Simonite, Tom., Machines taught by photos to learn a sexist view of women
- Karppi, Tero., Digital Suicide and the Biopolitics of Leaving Facebook
- Propublica, Machine Bias
- Turkle, Sherry., Introduction: The things that matter (3-10)
- Lee, Kai Fu., A blueprint for coexistence with artificial intelligence
- Rahwan, Iyad., Society-in-the-loop: programming the algorithmic social contract
- Wired., Big data meets Big Brother as China moves to rate its citizens
- Foucault., Philosophical Historian // Foucault & Chomsky