Data management for platform-mediated public services: Challenges and best practices

TL;DR

This paper discusses the challenges and best practices in managing data for public services, emphasizing risks of platform reliance and proposing design principles to mitigate these issues.

Contribution

It introduces a set of design principles and primitives for public infrastructure to address data management challenges and risks.

Findings

Identification of risks in platform-mediated public services

Proposed design principles for safer data management

Guidelines for infrastructure providers to assess technology impacts

Abstract

Data harvesting and profiling have become a de facto business model for many businesses in the digital economy. The surveillance of individual persons through their use of private sector platforms has a well-understood effect on personal autonomy and democratic institutions. In this article, we explore the consequences of implementing data-rich services in the public sector and specifically the dangers inherent to undermining the universality of the reach of public services, the implicit endorsement of the platform operators by government, and the inability of members of the public to avoid using the platforms in practice. We propose a set of good practices in the form of design principles that infrastructure services can adopt to mitigate the risks, and we specify a set of design primitives that can be used to support the development of infrastructure that follows the principles. We argue that providers of public infrastructure should adopt a practice of critical assessment of the consequences of their technology choices.