Work

Fairness-Aware Programming

Year: 2019

Type: conference-paper

Abstract: Increasingly, programming tasks involve automating and deploying sensitive decision-making processes that may have adverse impacts on individuals or groups of people. The issue of fairness in automated decision-making has thus become a major problem, attracting interdisciplinary attention. In this work, we aim to make fairness a first-class concern in programming. Specifically, we propose fairness-aware programming, where programmers can state fairness expectations natively in their code, and have a runtime system monitor decision-making and report violations of fairness.

DOI: 10.1145/3287560.3287588

Authors: Aws Albarghouthi, Samuel Vinitsky

Institution: University of Wisconsin–Madison

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Peace, justice, and strong institutions

Open Access status: gold

Funder: National Science Foundation

Award: SHF: Medium: Formal Methods for Program Fairness