Spatial Fairness: The Case for its Importance, Limitations of Existing Work, and Guidelines for Future Research
arxiv(2024)
摘要
Despite location being increasingly used in decision-making systems employed
in many sensitive domains such as mortgages and insurance, astonishingly little
attention has been paid to unfairness that may seep in due to the correlation
of location with characteristics considered protected under anti-discrimination
law, such as race or national origin. This position paper argues for the urgent
need to consider fairness with respect to location, termed spatial
fairness, by outlining the harms that continue to be perpetuated due to
location's correlation with protected characteristics. This interdisciplinary
work connects knowledge from fields such as public policy, economic
development, and geography to highlight how fair-AI research currently falls
short of correcting for spatial biases, and does not consider challenges unique
to spatial data. Furthermore, we identify limitations of the handful of spatial
fairness work proposed so far, and finally, detail guidelines for future
research so subsequent work may avoid such issues and help correct spatial
biases.
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