The Impossible Theorem of Fairness
@misc{Nguyen2022,
author = "Nguyen, Man",
title = {{The Impossible Theorem of Fairness}},
howpublished = "\url{https://ir.hamilton.edu/do/37a01e4c-a7a4-4106-9860-20ab1c000ec7}",
institution = {Hamilton College},
year = 2022,
month = apr,
school = {Mathematics},
}
BibTeX
@misc{Nguyen2022,
author = "Nguyen, Man",
title = {{The Impossible Theorem of Fairness}},
howpublished = "\url{https://ir.hamilton.edu/do/37a01e4c-a7a4-4106-9860-20ab1c000ec7}",
institution = {Hamilton College},
year = 2022,
month = apr,
school = {Mathematics},
}
Creator
-
Nguyen, Man
Role:AuthorInstitution:Hamilton CollegeAffiliation:StudentClass Year:2022
Date
April 1st, 2022
Description
With the growth of machine learning, there has been an increase of machine biases that can cause wrongful discrimination. In the case of implementing "fairness,” several conceptions of bias were created to target a fair system. However, statisticians have found that these conceptions contradict one another. Thus, we run into an impossible conundrum of fairness in machine learning. In cases that high risk, we want to investigate the best fairness measures if one is possible. Moreover, we would like to determine when these fairness measures fail or what conditions must be met for them to succeed.
Type of Work
Institution
Hamilton College
Area of Study
Course
Part of Collection
Rights Statement
The copyright for this work is held by its creators and Hamilton College. More information