Bias in data‐driven artificial intelligence systems—An introductory survey

Author:

Ntoutsi Eirini1ORCID,Fafalios Pavlos2ORCID,Gadiraju Ujwal1,Iosifidis Vasileios1,Nejdl Wolfgang1,Vidal Maria‐Esther3,Ruggieri Salvatore4ORCID,Turini Franco4ORCID,Papadopoulos Symeon5ORCID,Krasanakis Emmanouil5ORCID,Kompatsiaris Ioannis5ORCID,Kinder‐Kurlanda Katharina6ORCID,Wagner Claudia6,Karimi Fariba6,Fernandez Miriam7ORCID,Alani Harith7,Berendt Bettina89ORCID,Kruegel Tina10,Heinze Christian10,Broelemann Klaus11,Kasneci Gjergji11,Tiropanis Thanassis12,Staab Steffen11213

Affiliation:

1. L3S Research Center & Faculty of Electrical Engineering and Computer Science, Leibniz University Hannover Hannover Germany

2. Institute of Computer Science, Foundation for Research and Technology‐Hellas (FORTH‐ICS) Heraklion Greece

3. TIB Leibniz Information Centre For Science and Tecnhnology Hannover Germany

4. KDDLAB, Dipartimento di Informatica Università di Pisa Pisa Italy

5. Information Technologies Institute, The Centre for Research & Technology, Hellas (CERTH) Thessaloniki Greece

6. GESIS Leibniz Institute for the Social Sciences Cologne Germany

7. Knowledge Media Institute The Open University Milton Keynes UK

8. Faculty of Electrical Engineering and Computer Science TU Berlin Berlin Germany

9. Department of Computer Science KU Leuven Leuven Belgium

10. Institute for Legal Informatics Leibniz University of Hanover Hanover Germany

11. Innovation Lab, SCHUFA Holding AG Wiesbaden Germany

12. Electronics and Computer Science University of Southampton Southampton UK

13. Institute for Parallel and Distributed Systems, University of Stuttgart Germany

Funder

European Commission

Publisher

Wiley

Subject

General Computer Science

Reference95 articles.

1. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

2. A reductions approach to fair classification;Agarwal A.;ICML,2018

3. Angwin J. Larson J. Mattu S. &Kirchner L.(2016 May 23). Machine bias.ProPublica.

4. Bias on the web

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