The Importance of Time in Causal Algorithmic Recourse
Isacco Beretta Martina Cinquini
The application of Algorithmic Recourse in decision-making is a promising
field that offers practical solutions to reverse unfavorable decisions.
However, the inability of these methods to consider potential dependencies
among variables poses a significant challenge due to the assumption of feature
independence. Recent advancements have incorporated knowledge of causal
dependencies, thereby enhancing the quality of the recommended recourse
actions. Despite these improvements, the inability to incorporate the temporal
dimension remains a significant limitation of these approaches. This is
particularly problematic as identifying and addressing the root causes of
undesired outcomes requires understanding time-dependent relationships between
variables. In this work, we motivate the need to integrate the temporal
dimension into causal algorithmic recourse methods to enhance recommendations'
plausibility and reliability. The experimental evaluation highlights the
significance of the role of time in this field.