Wednesday, Aug 9: 11:25 AM - 11:50 AM
Invited Paper Session
Metro Toronto Convention Centre
Automated decision systems are used for decision-making in societally high-stakes settings like healthcare and criminal justice, raising concerns around the suitability and equity of these systems. The discourse on responsible use largely focuses on fairness and ethics, often overlooking first-order questions of validity. In this talk, we explore the important role validity plays in responsible use and consider its implications for fairness.
Drawing on validity theory from the social sciences, we develop a taxonomy of challenges that threaten validity in algorithmic decision-making contexts. We delve into a couple common challenges — selection bias and missing data — in two domains, consumer credit lending and child welfare screening. We illustrate how failure to properly address these issues can invalidate standard fairness assessments and undermine fairness interventions. We present an alternative method for conducting fairness assessments and corrective interventions that addresses common forms of selection bias and missing data using techniques from causal inference. We conclude by considering the broader question of governance of high-stakes decision-making algorithms.