Algorithms and Decision-Making in the Public Sector

TL;DR

This paper surveys how governments use algorithmic systems across various public sectors, examining their social impacts, challenges, and the need for further empirical research.

Contribution

It provides a comprehensive overview of the social implications and stages of deployment of municipal algorithmic systems in the public sector.

Findings

Algorithms influence accountability and privacy concerns.

Deployment impacts social equity and public participation.

Open questions highlight gaps in empirical understanding.

Abstract

This article surveys the use of algorithmic systems to support decision-making in the public sector. Governments adopt, procure, and use algorithmic systems to support their functions within several contexts -- including criminal justice, education, and benefits provision -- with important consequences for accountability, privacy, social inequity, and public participation in decision-making. We explore the social implications of municipal algorithmic systems across a variety of stages, including problem formulation, technology acquisition, deployment, and evaluation. We highlight several open questions that require further empirical research.