FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoring

• URL: http://arxiv.org/abs/2508.20021v1
• Date: Wed, 27 Aug 2025 16:30:30 GMT
• Title: FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoring
• Abstract summary: We present FairLoop1, a tool for human-guided bias mitigation in neural network-based prediction models.<n>FairLoop distills decision trees from neural networks, allowing users to inspect and modify unfair decision logic.<n>It addresses the influence of sensitive attributes selectively rather than excluding them uniformly.
• Score: 1.5831073048826505
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Sensitive attributes like gender or age can lead to unfair predictions in machine learning tasks such as predictive business process monitoring, particularly when used without considering context. We present FairLoop1, a tool for human-guided bias mitigation in neural network-based prediction models. FairLoop distills decision trees from neural networks, allowing users to inspect and modify unfair decision logic, which is then used to fine-tune the original model towards fairer predictions. Compared to other approaches to fairness, FairLoop enables context-aware bias removal through human involvement, addressing the influence of sensitive attributes selectively rather than excluding them uniformly.

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