Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification

by   Brian d'Alessandro, et al.

Recent research has helped to cultivate growing awareness that machine learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science community, leaving its members with little concrete guidance to proactively address these concerns. This article introduces issues of discrimination to the data science community on its own terms. In it, we tour the familiar data mining process while providing a taxonomy of common practices that have the potential to produce unintended discrimination. We also survey how discrimination is commonly measured, and suggest how familiar development processes can be augmented to mitigate systems' discriminatory potential. We advocate that data scientists should be intentional about modeling and reducing discriminatory outcomes. Without doing so, their efforts will result in perpetuating any systemic discrimination that may exist, but under a misleading veil of data-driven objectivity.



There are no comments yet.


page 11

page 12


Data, Science and Society

Reflections on the Concept of Data and its Implications for Science and ...

Biases in Data Science Lifecycle

In recent years, data science has become an indispensable part of our so...

The Data Science Fire Next Time: Innovative strategies for mentoring in data science

As data mining research and applications continue to expand in to a vari...

Approaching Ethical Guidelines for Data Scientists

The goal of this article is to inspire data scientists to participate in...

Detecting discriminatory risk through data annotation based on Bayesian inferences

Thanks to the increasing growth of computational power and data availabi...

Achieving non-discrimination in prediction

Discrimination-aware classification is receiving an increasing attention...

Fairness-aware machine learning: a perspective

Algorithms learned from data are increasingly used for deciding many asp...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.