  In the process of evaluating competencies for job or student recruitment
through material screening, decision-makers can be influenced by inherent
cognitive biases, such as the screening order or anchoring information, leading
to inconsistent outcomes. To tackle this challenge, we conducted interviews
with seven experts to understand their challenges and needs for support in the
screening process. Building on their insights, we introduce BiasEye, a
bias-aware real-time interactive material screening visualization system.
BiasEye enhances awareness of cognitive biases by improving information
accessibility and transparency. It also aids users in identifying and
mitigating biases through a machine learning (ML) approach that models
individual screening preferences. Findings from a mixed-design user study with
20 participants demonstrate that, compared to a baseline system lacking our
bias-aware features, BiasEye increases participants' bias awareness and boosts
their confidence in making final decisions. At last, we discuss the potential
of ML and visualization in mitigating biases during human decision-making
tasks.
