{"id":22862878,"url":"https://github.com/yochem/bursting-burden","last_synced_at":"2025-04-30T21:52:45.660Z","repository":{"id":102731390,"uuid":"531065968","full_name":"yochem/bursting-burden","owner":"yochem","description":"📝 Accompanying code for our paper \"Bursting the Burden Bubble: An Assessment of Sharma et al.’s Counterfactual-Based Fairness Metric\" ","archived":false,"fork":false,"pushed_at":"2024-10-10T08:06:29.000Z","size":4056,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-30T21:52:39.498Z","etag":null,"topics":["burden","certifai","fairness","metric","sharma"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/yochem.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-08-31T12:04:53.000Z","updated_at":"2025-04-14T17:54:21.000Z","dependencies_parsed_at":"2023-03-08T19:30:34.260Z","dependency_job_id":null,"html_url":"https://github.com/yochem/bursting-burden","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yochem%2Fbursting-burden","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yochem%2Fbursting-burden/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yochem%2Fbursting-burden/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yochem%2Fbursting-burden/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/yochem","download_url":"https://codeload.github.com/yochem/bursting-burden/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251789310,"owners_count":21644081,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["burden","certifai","fairness","metric","sharma"],"created_at":"2024-12-13T10:15:46.615Z","updated_at":"2025-04-30T21:52:45.648Z","avatar_url":"https://github.com/yochem.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Bursting the Burden Bubble\n\n**An assessement of Sharma et al.'s Counterfactual-Based Fairness Metric.**\n\nBy Yochem van Rosmalen, Florian van der Steen, Sebastiaan Jans, and Daan van\nder Weijden.\n\nAs presented at the [BNAIC/BeNeLearn](https://bnaic2022.uantwerpen.be/) 2022\nconference in Mechelen, Belgium.\n\n### Abstract\n\nMachine learning has seen an increase in negative publicity in recent years,\ndue to biased, unfair, and uninterpretable models. There is a rising interest\nin making machine learning models more fair for unprivileged communities, such\nas women or people of color. Metrics are needed to evaluate the fairness of a\nmodel. A novel metric for evaluating fairness between groups is Burden, which\nuses counterfactuals to approximate the average distance of negatively\nclassified individuals in a group to the decision boundary of the model. The\ngoal of this study is to compare Burden to statistical parity, a well-known\nfairness metric, and discover Burden's advantages and disadvantages. We do this\nby calculating the Burden and statistical parity of a sensitive attribute in\nthree datasets: two synthetic datasets are created to display differences\nbetween the two metrics, and one real-world dataset is used. We show that\nBurden can be more nuanced than statistical parity, but also that the metrics\ncan disagree on which group is treated unfairly. We therefore conclude that\nBurden is a valuable metric to add to the existing group of fairness metrics,\nbut should not be used on its own.\n\nRead the full paper at [bursting-burden.pdf](paper/bursting-burden.pdf)!\n\n### Credits\n\nThe implementation of CERTIFAI is written by @Ighina, and can be found at\ngithub.com/Ighina/CERTIFAI. The Python file of the project is included\nin this repository: CERTIFAI.py. Licensed MIT.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyochem%2Fbursting-burden","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyochem%2Fbursting-burden","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyochem%2Fbursting-burden/lists"}