Measuring Fairness
There are multiple ways to measure accuracy. No matter how we build our model, accuracy across these measures will vary when applied to different groups of people.
Measuring Fairness Explorables Measuring Fairness There are multiple ways to measure accuracy. No matter how we build our model, accuracy across these measures will vary when applied to different groups of people. Measuring Fairness How do you make sure a model works equally well for different groups of people? It turns out that in many situations, this is harder than you might think. The problem is that there are different ways to measure the accuracy of a model, and often it's mathematically impossible for them all to be equal across groups. We'll illustrate how this happens by creating a (f
related reading
- Statistical Fairness - Turing Commonsalan-turing-institute.github.io
- [arxiv] an algorithmic framework for fairness elicitationarxiv.org
- A statistical approach to model evaluations \ Anthropicanthropic.com
- 0cfc9404f89400c5ed897035e0d3748c-Paper-Conference.pdfproceedings.neurips.cc
- Can a Model Be Differentially Private and Fair?pair.withgoogle.com
- Classificationfairmlbook.org
- Precision and recallen.wikipedia.org
- Relative notions of fairnessfairmlbook.org
- How to Measure Anything — LessWronglesswrong.com
- Frontiers | On Consequentialism and Fairnessfrontiersin.org
- Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternativesarxiv.org
- Scaling Laws Do Not Scalearxiv.org