Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrines

07/06/2022
by   Falaah Arif Khan, et al.
0

In this work we use Equal Oppportunity (EO) doctrines from political philosophy to make explicit the normative judgements embedded in different conceptions of algorithmic fairness. We contrast formal EO approaches that narrowly focus on fair contests at discrete decision points, with substantive EO doctrines that look at people's fair life chances more holistically over the course of a lifetime. We use this taxonomy to provide a moral interpretation of the impossibility results as the incompatibility between different conceptions of a fair contest – foward-looking versus backward-looking – when people do not have fair life chances. We use this result to motivate substantive conceptions of algorithmic fairness and outline two plausible procedures based on the luck-egalitarian doctrine of EO, and Rawls's principle of fair equality of opportunity.

READ FULL TEXT
research
06/15/2021

Fairness as Equality of Opportunity: Normative Guidance from Political Philosophy

Recent interest in codifying fairness in Automated Decision Systems (ADS...
research
05/14/2023

Algorithmic Pluralism: A Structural Approach Towards Equal Opportunity

While the idea of equal opportunity enjoys a broad consensus, many disag...
research
03/16/2021

RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity

We present RAWLSNET, a system for altering Bayesian Network (BN) models ...
research
02/18/2020

A Resolution in Algorithmic Fairness: Calibrated Scores for Fair Classifications

Calibration and equal error rates are fundamental conditions for algorit...
research
05/25/2023

Monitoring Algorithmic Fairness

Machine-learned systems are in widespread use for making decisions about...
research
05/12/2021

Fairness and Discrimination in Information Access Systems

Recommendation, information retrieval, and other information access syst...

Please sign up or login with your details

Forgot password? Click here to reset