Qusai Ramadan
Steffen Staab
ABSTRACT
Decision-making software may exhibit biases due to hidden dependencies between protected characteristics and the data used as input for making decisions. To uncover such dependencies, we propose the development of a framework to support discrimination analysis during the system design phase, based on system models and available data.
- Amir Shayan Ahmadian, Sven Peldszus, Qusai Ramadan, and Jan Jürjens. 2017. Model-based privacy and security analysis with CARiSMA. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. ACM, 989--993. Google Scholar
Digital Library
- Amir Shayan Ahmadian, Daniel Strüber, Volker Riediger, and Jan Jürjens. 2017. Model-based privacy analysis in industrial ecosystems. In European Conference on Modelling Foundations and Applications. Springer, 215--231.Google ScholarCross Ref
- Solon Barocas and Andrew D Selbst. 2016. Big data's disparate impact. (2016).Google Scholar
- Toon Calders and Sicco Verwer. 2010. Three naive Bayes approaches for discrimination-free classification. Data Mining and Knowledge Discovery 21, 2 (2010), 277--292. Google ScholarDigital Library
- Laura Carmichael, Sophie Stalla-Bourdillon, and Steffen Staab. 2016. Data mining and automated discrimination: a mixed legal/technical perspective. IEEE Intelligent Systems 31, 6 (2016), 51--55. Google ScholarDigital Library
- Peter Pin-Shan Chen. 1988. The entity-relationship model - toward a unified view of data. In Readings in artificial intelligence and databases. Elsevier, 98--111.Google Scholar
- Anupam Datta, Matt Fredrikson, Gihyuk Ko, Piotr Mardziel, and Shayak Sen. 2017. Proxy Non-Discrimination in Data-Driven Systems. arXiv preprint arXiv:1707.08120 (2017).Google Scholar
- Dorothy E Denning. 1976. A lattice model of secure information flow. Communications of tshe ACM 19, 5 (1976), 236--243. Google ScholarDigital Library
- Sainyam Galhotra, Yuriy Brun, and Alexandra Meliou. 2017. Fairness testing: testing software for discrimination. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. ACM, 498--510. Google ScholarDigital Library
- Joseph A Goguen and José Meseguer. 1984. Unwinding and inference control. In Security and Privacy, 1984 IEEE Symposium on. IEEE, 75--75.Google ScholarCross Ref
- Sara Hajian, Josep Domingo-Ferrer, Anna Monreale, Dino Pedreschi, and Fosca Giannotti. 2015. Discrimination-and privacy-aware patterns. Data Mining and Knowledge Discovery 29, 6 (2015), 1733--1782. Google ScholarDigital Library
- Jan Jürjens. 2000. Secure Information Flow for Concurrent Processes, See {17}, 395--409. Google ScholarDigital Library
- Jan Jürjens. 2005. Secure systems development with UML. Springer Science & Business Media. Google ScholarDigital Library
- Faisal Kamiran, Toon Calders, and Mykola Pechenizkiy. 2010. Discrimination aware decision tree learning. In Data Mining (ICDM), 2010 IEEE 10th International Conference on. IEEE, 869--874. Google ScholarDigital Library
- Toshihiro Kamishima, Shotaro Akaho, and Jun Sakuma. 2011. Fairness-aware learning through regularization approach. In Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on. IEEE, 643--650. Google ScholarDigital Library
- Object Management Group (OMG). 2011. UML 2.5 Superstructure Specification. (2011).Google Scholar
- Catuscia Palamidessi (Ed.). 2000. CONCUR 2000 - Concurrency Theory, 11th International Conference, University Park, PA, USA, August 22-25, 2000, Proceedings. Lecture Notes in Computer Science, Vol. 1877. Springer. Google ScholarDigital Library
- Frank Pasquale. 2015. The black box society: The secret algorithms that control money and information. Harvard University Press. Google ScholarDigital Library
- Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi. 2015. Learning fair classifiers. arXiv preprint arXiv:1507.05259 (2015).Google Scholar
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