Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints

@article{Mehrotra2022SelectionIT,
  title={Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints},
  author={Anay Mehrotra and Bary S. R. Pradelski and Nisheeth K. Vishnoi},
  journal={2022 ACM Conference on Fairness, Accountability, and Transparency},
  year={2022}
}
In selection processes such as hiring, promotion, and college admissions, implicit bias toward socially-salient attributes such as race, gender, or sexual orientation of candidates is known to produce persistent inequality and reduce aggregate utility for the decision maker. Interventions such as the Rooney Rule and its generalizations, which require the decision maker to select at least a specified number of individuals from each affected group, have been proposed to mitigate the adverse… 

Figures from this paper

Fairness in Selection Problems with Strategic Candidates
To better understand discriminations and the effect of affirmative actions in selection problems (e.g., college admission or hiring), a recent line of research proposed a model based on differential
Turtle Score - Similarity Based Developer Analyzer
TLDR
It’s been proven that theency and capability of a particular worker go higher when working with a person of a similar personality, so this will serve as a useful tool for recruiters who aim to recruit people with high productivity.

References

SHOWING 1-10 OF 112 REFERENCES
Interventions for ranking in the presence of implicit bias
TLDR
A family of simple and interpretable constraints are presented and it is proved that under natural distributional assumptions on the utilities of items, simple, Rooney Rule-like, constraints can also surprisingly recover almost all the utility lost due to implicit biases.
On fair selection in the presence of implicit and differential variance
Interventions designed to reduce implicit prejudices and implicit stereotypes in real world contexts: a systematic review
TLDR
Caution is advised when it comes to programs aiming at reducing biases, as robust data is lacking for many of these interventions, and some techniques, such as exposure to counterstereotypical exemplars, are more promising.
Gender discrimination in hiring: Intersectional effects with ethnicity and cognitive job demands.
When considering hiring discrimination, scientific research typically considers 1 applicant characteristic at a time (such as the applicant’s gender or ethnicity), despite that applicants belong to
Pursuing Quality: How Search Costs and Uncertainty Magnify Gender-based Double Standards in a Multistage Evaluation Process
Despite lab-based evidence supporting the argument that double standards—by which one group is unfairly held to stricter standards than another—explain observed gender differences in evaluations, it
Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?
TLDR
The Equal Opportunity fairness constraint combined with ERM will provably recover the Bayes Optimal Classifier under a range of bias models, and theoretical results provide additional motivation for considering fairness interventions even if an actor cares primarily about accuracy.
Impact of Bias on School Admissions and Targeted Interventions
TLDR
This first mathematical analysis of the impact of biased evaluations of students on school admissions is presented, to the best of the knowledge, and it finds that schools have little incentive to change their evaluation mechanisms when students' potentials are Pareto distributed.
Historical roots of implicit bias in slavery
TLDR
The historical roots of geographical differences in implicit bias are investigated by comparing average levels of implicit bias with the number of slaves in areas more dependent on slavery in 1860, supporting an interpretation of implicit biases as the cognitive residue of past and present structural inequalities.
Employment discrimination: the role of implicit attitudes, motivation, and a climate for racial bias.
TLDR
Results partially illustrate that motivation to control prejudice moderates the relationship between explicit and implicit attitudes and illustrate the differences between implicit and explicit racial attitudes in predicting discriminatory behavior.
Implicit Bias in the Courtroom
Given the substantial and growing scientific literature on implicit bias, the time has now come to confront a critical question: What, if anything, should we do about implicit bias in the courtroom?
...
...