Why unbiased computational processes can lead to discriminative decision procedures

Studies in Applied Philosophy, Epistemology and Rational Ethics

Volumn 3, Issue , 2013, Pages 43-57

  Calders, Toon ^a   Žliobaitė, Indrė ^b  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b BOURNEMOUTH UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84910009040     PISSN: 21926255     EISSN: 21926263     Source Type: Book Series    
DOI: 10.1007/978-3-642-30487-3_3     Document Type: Chapter

References (14)

1. Blank, R., Dabady, M., Citro, C.: Measuring Racial Discrimination. Natl Academy Press (2004)
2. Jonah, B.A.: Accident risk and risk-taking behavior among young drivers. Accident Analysis & Prevention 18(4), 255-271 (1986)
3. Calders, T., Verwer, S.: Three Naive Bayes Approaches for Discrimination-Free Classification. Data Mining and Knowledge Discovery 21(2), 277-292 (2010)
4. Distance Learning Center. Internet Based Benefit and Compensation Administration: Discrimination in Pay, ch. 26 (2009), http://www.eridlc.com/index.cfm?fuseaction=textbook.chpt26 (accessed: November 2011)
5. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. John Wiley & Sons (2001)
6. Fang, H., Moro, A.: Theories of Statistical Discrimination and Affirmative Action: A Survey. In: Benhabib, J., Bisin, A., Jackson, M. (eds.) Handbook of Social Economics, pp. 133-200 (2010)
7. Kamiran, F., Calders, T.: Classification with no discrimination by preferential sampling. In: Proceedings of the 19th Annual Machine Learning Conference of Belgium and the Netherlands (BENELEARN 2010), pp. 1-6 (2010)
8. Kamiran, F., Calders, T.: Classifying without Discrimination. In: IEEE International Conference on Computer, Control and Communication (IEEE-IC4), pp. 1-6 (2009)
9. Kamiran, F., Calders, T., Pechenizkiy, M.: Discrimination Aware Decision Tree Learning. In: Proceedings of IEEE ICDM International Conference on Data Mining (ICDM 2010), pp. 869-874 (2010)
10. Kelly, M.G., Hand, D.J., Adams, N.M.: The Impact of Changing Populations on Classifier Performance. In: Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 1999), pp. 367-371 (1999)
11. Rice, W.: Race, Gender, “Redlining”, and the Discriminatory Access to Loans, Credit, and Insurance: An Historical and Empirical Analysis of Consumers Who Sued Lenders and Insurers in Federal and State Courts. San Diego Law Review 33, 637-646 (1996)
12. Turner, A., Skidmore, F.: Introduction, Summary, and Recommendations. In: Turner, A., Skidmore, F. (eds.) Mortgage Lending Discrimination: A Review of Existing Evidence (Urban Institute Monograph Series on Race and Discrimination), pp. 1-22. Urban Institute Press, Washington, DC (1999)
13. Widmer, G., Kubat, M.: Learning in the presence of concept drift and hidden contexts. Machine Learning 23(1), 69-101 (1996)
14. Zadrozny, B.: Learning and Evaluating Classifiers under Sample Selection Bias. In: Proceedings of the 21st International Conference on Machine Learning (ICML 2004), pp. 903-910 (2004)