Diagnosing and Addressing Emergent Harms in the Design Process of Public AI and Algorithmic Systems

Abstract

Algorithmic and data-driven systems are increasingly used in the public sector to improve the efficiency of existing services or to provide new services through the newfound capacity to process vast volumes of data. Unfortunately, certain instances also have negative consequences for citizens, in the form of discriminatory outcomes, arbitrary decisions, lack of recourse, and more. These have serious impacts on citizens ranging from material to psychological harms. These harms partly emerge from choices and interactions in the design process. Existing critical and reflective frameworks for technology design do not address several aspects that are important to the design of systems in the public sector, namely protection of citizens in the face of potential algorithmic harms, the design of institutions to ensure system safety, and an understanding of how power relations affect the design, development, and deployment of these systems. The goal of this workshop is to develop these three perspectives and take the next step towards reflective design processes within public organisations. The workshop will be divided into two parts. In the first half we will elaborate the conceptual foundations of these perspectives in a series of short talks. Workshop participants will learn new ways of protecting against algorithmic harms in sociotechnical systems through understanding what institutions can support system safety, and how power relations influence the design process. In the second half, participants will get a chance to apply these lenses by analysing a real world case, and reflect on the challenges in applying conceptual frameworks to practice.