On the Fairness of Causal Algorithmic Recourse
Authors: Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf9584-9594
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We study theoretically and empirically how to enforce fair causal recourse by altering the classifier and perform a case study on the Adult dataset. |
| Researcher Affiliation | Academia | 1 Max Planck Institute for Intelligent Systems, T ubingen, Germany 2 University of Cambridge 3 ETH Z urich 4 Saarland University 5 The Alan Turing Institute |
| Pseudocode | No | The paper describes optimization problems (e.g., Eq. 1, 2, 3) and solution approaches (e.g., 'using brute force search'), but it does not include any explicitly labeled 'Pseudocode' or 'Algorithm' blocks. |
| Open Source Code | Yes | Code to reproduce our experiments is available at https://github.com/amirhk/recourse. |
| Open Datasets | Yes | We use the Adult dataset (Lichman et al. 2013), which consists of 45k+ samples without missing data. |
| Dataset Splits | Yes | select all remaining hyperparameters (including the trade-off parameter λ for Fair SVM) using 5-fold cross validation. |
| Hardware Specification | No | The paper describes numerical simulations and a case study on the Adult dataset but does not provide specific details regarding the hardware used for these experiments. |
| Software Dependencies | No | The paper mentions training "linear and nonlinear logistic regression (LR), and different support vector machines (SVMs)" and using a "probabilistic framework of Karimi et al. (2020c)", but it does not specify exact version numbers for any software libraries or dependencies. |
| Experiment Setup | Yes | We use either a linear or polynomial kernel for all SVMs (depending on the GT labels) and select all remaining hyperparameters (including the trade-off parameter λ for Fair SVM) using 5-fold cross validation. |