AI RESEARCH
Assessing Predictive Models for Fairness Based on Movement Patterns
arXiv CS.LG
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ArXi:2605.23234v1 Announce Type: new Assessing the spatial fairness of predictive models involves establishing whether they are statistically penalizing (favoring) individuals associated with certain geographical locations. Literature on this topic makes the fundamental assumption that each individual is assigned to a single geographical location (e.g., place of residence). However, fairness with respect to the set of locations where one has been, i.e., their movement patterns over different regions, also matters when fairness is considered.