Algorithmic Justice: Bias in Code, Bias in Society

Authors

  • Dr. Moeed Yusuf United States Institute of Peace (USIP) - Islamabad office (previously affiliated with universities in Pakistan) Author

Keywords:

algorithmic bias, social bias, artificial intelligence, machine learning, data, fairness, equity, accountability, algorithmic justice

Abstract

The increasing reliance on algorithms in decision-making across a range of societal domains raises concerns about algorithmic bias. This article explores the intricate relationship between bias in code and bias in society, arguing that algorithms not only reflect but also amplify existing societal inequalities. It examines common sources of algorithmic bias, the diverse consequences it produces, and potential strategies for promoting algorithmic justice. The article concludes by emphasizing the need for collaborative efforts from researchers, policymakers, and industry actors to ensure that algorithms are developed and deployed in a fair, equitable, and accountable manner.

Downloads

Published

2024-03-31

Issue

Section

Articles