Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias

Author:

Baumann Joachim1ORCID,Castelnovo Alessandro2ORCID,Crupi Riccardo3ORCID,Inverardi Nicole3ORCID,Regoli Daniele3ORCID

Affiliation:

1. Department of Informatics, University of Zurich, Switzerland and Zurich University of Applied Sciences, Switzerland

2. Data Science & Artificial Intelligence, Intesa Sanpaolo, Italy and Dept. of Informatics, Systems and Communication, University Milano Bicocca, Italy

3. Data Science & Artificial Intelligence, Intesa Sanpaolo, Italy

Funder

Innosuisse - Schweizerische Agentur für Innovationsförderung

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

ACM

Reference63 articles.

1. Alekh Agarwal , Alina Beygelzimer , Miroslav Dudík , John Langford , and Hanna Wallach . 2018 . A reductions approach to fair classification . In International Conference on Machine Learning. PMLR, 60–69 . Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, and Hanna Wallach. 2018. A reductions approach to fair classification. In International Conference on Machine Learning. PMLR, 60–69.

2. Julia Angwin , Jeff Larson , Surya Mattu , and Lauren Kirchner . 2016. Machine bias: There’s software used across the country to predict future criminals, and it’s biased against blacks. ProPublica ( 2016 ). Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner. 2016. Machine bias: There’s software used across the country to predict future criminals, and it’s biased against blacks. ProPublica (2016).

3. Samuel A Assefa , Danial Dervovic , Mahmoud Mahfouz , Robert E Tillman , Prashant Reddy , and Manuela Veloso . 2020 . Generating synthetic data in finance: opportunities, challenges and pitfalls . In Proceedings of the First ACM International Conference on AI in Finance. 1–8. Samuel A Assefa, Danial Dervovic, Mahmoud Mahfouz, Robert E Tillman, Prashant Reddy, and Manuela Veloso. 2020. Generating synthetic data in finance: opportunities, challenges and pitfalls. In Proceedings of the First ACM International Conference on AI in Finance. 1–8.

4. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org.

5. Big data’s disparate impact;Barocas Solon;Calif. L. Rev.,2016

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