Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Fairness Shields: Safeguarding against Biased Decision Makers
Authors: Filip Cano, Thomas A. Henzinger, Bettina Könighofer, Konstantin Kueffner, Kaushik Mallik
AAAI 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical evaluation demonstrates the effectiveness of these shields in ensuring fairness while maintaining cost efficiency across various scenarios. |
| Researcher Affiliation | Academia | 1Graz University of Technology 2Institute of Science and Technology Austria (ISTA) 3IMDEA Software Institute EMAIL, EMAIL, EMAIL, EMAIL |
| Pseudocode | No | The paper describes algorithms in prose and mathematical equations but does not include a distinct pseudocode block or algorithm figure. |
| Open Source Code | No | The paper refers to an extended version on arXiv (Cano et al. 2024b) but does not provide an explicit statement or link for the source code of their methodology. |
| Open Datasets | Yes | We performed our experiments on the datasets Adult (Becker et al. 1996), COMPAS (Kirchner et al. 2016), German Credit (Hofmann 1994), and Bank Marketing (Moro et al. 2012). |
| Dataset Splits | No | The paper mentions using well-known datasets but does not explicitly provide details about training/test/validation dataset splits, percentages, or specific splitting methodologies used for reproduction. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | We synthesized shields to ensure DP and Eq Opp with thresholds κ {0.05, 0.1, 0.15, 0.2}. For all models and datasets, Fin Hzn shields were synthesized with T = 100 for DP and T = 75 for Eq Opp. We synthesized Static-Fair, Static-BW, and Dynamic shields with T = 50 for DP and Eq Opp, and simulated them for 10 periods. |