Lecture 11 Flashcards
1
Q
Algorithms
A
Any evidence-based forecasting formula or rule
2
Q
Why do we use algorithms?
A
- People can be irrational and make mistakes (cognitive biases)
- People don’t know what they don’t know (Dunning-Kruger effect)
- Experts might have incentives to be entertaining, not only accurate
3
Q
Trust in algorithms..
A
- Has reduced for tasks that matter (consequential tasks)
- Has increased when consumers are familiar with the algorithm
- Has increased for objective tasks
4
Q
Algorithmic bias
A
Algorithms can lead to unintentional discrimination
5
Q
Examples of algorithmic bias:
A
- Biased healthcare decisions; discrimination against black patients
- Biased hiring decisions; person’s CV
- Biased language; “Female doctors don’t exist”
6
Q
Algorithms can be unfair with special circumstances:
A
Evaluation of teachers –>
- Changes in student’s circumstances
- Teachers of top students receive worse scores
- Incentivizes teachers to help students cheat
7
Q
Moral machine experiment
A
- 3 clusters; western, eastern and southern
- Data shows preference for sparing human lives, more lives and young lives
