Unveiling Opaque Predictors via Explainable Clustering: The CReEPy Algorithm
Proceedings of the 2nd Workshop on Bias, Ethical AI, Explainability and the role of Logic...
AI Developers & Engineers
Achieving Complete Coverage with Hypercube-Based Symbolic Knowledge-Extraction Techniques
In: Nowaczyk, S., et al. Artificial Intelligence. ECAI 2023 International Workshops. ECAI 2023. Communications in...
AI Developers & Engineers
ExACT Explainable Clustering: Unravelling the Intricacies of Cluster Formation
Paper @ 2nd Workshop on Knowledge Diversity and the 2nd Workshop on Cognitive Aspects of...
AI Developers & Engineers
A geometric framework for fairness
Proceedings of the 1st Workshop on Fairness and Bias in AI, AEQUITAS 2023 co-located with...
AI Developers & Engineers
FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System
AEQUITAS 2023 – Proceedings of the 1st Workshop on Fairness and Bias in AI co-located...
AI Developers & Engineers
Assessing and Enforcing Fairness in the AI Lifecycle
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI 2023), pages 6554-6562, IJCAI...
AI Developers & Engineers
Aequitas WP7 Use Case HR1 Akkodis STEM data 1.0
This dataset contains information about the hiring process conducted by Akkodis for job positions and...
AI Developers & Engineers
Unfair Inequality in Education: A Benchmark for AI-Fairness Research
This is the repository for the code and dataset of the paper intitled “Unfair Inequality...
AI Developers & Engineers
Aequitas WP7 Use Case HR1 Adecco data 1.0
The dataset contains the matching of job positions and hiring candidates; this data has been...
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