摘要：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 qualitycontrol 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 tophysical resources such as elevators and workspaces within an organization, and informcontact tracing and quarantine actions for individuals.In all these cases, significant inequitiesare likely to arise and to be propagated and reinforced by data-driven decision systems.In thisarticle, we propose a framework, called FIDES, for surfacing and reasoning about data equityin these systems.
关键词：Data equity;data ethics;responsible data science
