Diametrically Opposed Attributes? Review Process Preferences and Priorities When Contesting Algorithmic Decisions

Abstract

High-stakes algorithmic decisions should be contestable, yet there is limited guidance on how to design for contestability, resulting in inadequate contestation processes. Using an algorithmic university admissions decision scenario, we investigate what type of review process people prefer when contesting algorithmic decisions. Through a choice-based conjoint experiment, we explore review process preferences, asking participants to choose their preferred review process from a choice of two that differ across five design attributes: who the reviewer is, how independent the review is, the ability to communicate with the reviewer, the style of the review, and how much the review costs. Expanding on existing studies that focus on the perspective of the decision subject, we introduce eight different scenario perspectives to explore the extent to which particular design attributes matter to different stakeholders. People consistently prefer human reviewers who can make fresh decisions and communicate directly, while also prioritising affordable review processes. These findings highlight the importance of human involvement and cost-effectiveness in review processes. While the impact of perspective was relatively small, our qualitative analysis reveals important underlying tensions between efficiency, fairness, and individual needs. These subtle variations underscore the complexity of designing universally acceptable review processes. We propose design considerations that can help decision-makers to design review processes that are tailored to the specific decision-making context.

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