Abstract
The COVID-19 pandemic is compelling us to make crucial data-driven decisions quickly, bringing together diverse and unreliable sources of information without the usual quality control mechanisms we may employ. These decisions are consequential at multiple levels: They can inform local, state, and national government policy, be used to schedule access to physical resources such as elevators and workspaces within an organization, and inform contact tracing and quarantine actions for individuals. In all these cases, significant inequities are likely to arise and to be propagated and reinforced by data-driven decision systems. In this article, we propose a framework, called FIDES, for surfacing and reasoning about data equity in these systems.
Original language | English (US) |
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Article number | 24 |
Journal | Digital Government: Research and Practice |
Volume | 2 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2021 |
Keywords
- Data equity
- data ethics
- responsible data science
ASJC Scopus subject areas
- Computer Science Applications
- Public Administration
- Information Systems
- Software
- Computer Networks and Communications