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Artificial Intelligence without Bias

NoBIAS
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  • About
  • Beneficiaries
    • LUH-L3S
    • LUH-IRI
    • GESIS
    • SCHUFA
    • CERTH
    • UNIPI
    • OU
    • SOTON-ECS
    • SOTON-LS
    • KULEUVEN
    • UNI-KLU
  • ESRs
  • Events
  • Research agenda
  • PhD Projects
  • Publications
  • Resources
  • Contact
  • Twitter
  • About
  • Beneficiaries
    • LUH-L3S
    • LUH-IRI
    • GESIS
    • SCHUFA
    • CERTH
    • UNIPI
    • OU
    • SOTON-ECS
    • SOTON-LS
    • KULEUVEN
    • UNI-KLU
  • ESRs
  • Events
  • Research agenda
  • PhD Projects
  • Publications
  • Resources
  • Contact
  • Twitter

Publications

  • C. Mougan, D. S. Nielsen. Monitoring Model Deterioration with Explainable Uncertainty Estimation via Non-parametric Bootstrap. The 37th AAAI Conference on Artificial Intelligence (AAAI 2023).
  • S. Ruggieri, J. M. Alvarez, A. Pugnana, L. State, F. Turini. Can We Trust Fair-AI?  Senior Member Presentation Track, The 37th AAAI Conference on Artificial Intelligence (AAAI 2023).
  • I. Papageorgiou. Συστήματα Τεχνητής Νοημοσύνης και διακριτική μεταχείριση κατά το προσυμβατικό στάδιο σύναψης της σύμβασης εργασίας (eng. Artificial Intelligence (AI)-based systems and discrimination in recruitment). Efarmoges Astikou Dikaiou kai Politikis Dikonomias, Nomiki Bibliothiki Issue 10, October 2022. Greece.
  • J. M. Alvarez, M. Russo. Perception as a Fairness Parameter. NeurIPS workshop on Algorithmic Fairness through the Lens of Causality and Privacy (AFCP2022).
  • L. State, H. Salat, S. Rubrichi, Z. Smoreda. Explainability in Practice: Estimating Electrification Rates from Mobile Phone Data in Senegal. 2022 Trustworthy and Socially Responsible Machine Learning (TSRML 2022) co-located with Neural Information Processing Systems (NeurIPS) 2022
  • C. Mougan, K. Broelemann, G. Kasneci, T. Tiropanis, S. Staab. Explanation Shift: Detecting distribution shifts on tabular data via the explanation space. NeurIPS’22 workshop on Distribution Shift.
  • P. R. Lobo, E. Daga, H. Alani, M. Fernandez. Semantic Web technologies and bias in artificial intelligence: A systematic literature review. Semantic Web Journal, 2022.
  • L. State. Constructing Meaningful Explanations: Logic-based Approaches. Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES’22). https://dl.acm.org/doi/10.1145/3514094.3539544
  • P. R. Lobo. Bias in Hate Speech and Toxicity Detection. Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES’22). https://dl.acm.org/doi/pdf/10.1145/3514094.3539519
  • K. M. Scott, S. M. Wang, M. Miceli, P. Delobelle, K. Sztandar-Sztanderska, B. Berendt. 2022. Algorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric Perspective. In 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’22), June 21–24, 2022, Seoul, Republic of Korea. ACM, New York, NY, USA. https://doi.org/10.1145/3531146.3534631
  • O. Lampridis, L. State,·R. Guidotti, S. Ruggieri. Explaining short text classification with diverse synthetic exemplars and counter‑exemplars. Springer Maching Learning (2022). https://doi.org/10.1007/s10994-022-06150-7
  • A. Ferrara, L. Espín-Noboa, F. Karimi, C. Wagner. Link recommendations: Their impact on network structure and minorities. In 14th ACM Web Science Conference 2022 (WebSci ’22), June 26–29, 2022, Barcelona, Spain. https://doi.org/10.1145/3501247.3531583.
  • C. Mougan, G. Kanellos, J. Micheler, J. Martinez, T. Gottron. Introducing explainable supervised machine learning into interactive feedback loops for statistical production system. IFC workshop on “Data science in central banking – data, technologies and applications” 2021.
  • P. Naumann, E. Ntoutsi, Consequence-aware Sequential Counterfactual Generation, ECMLPKDD 2021.
  • C. Yi, A. Zimek, E. Ntoutsi, XPROAX-Local explanations for text classification with progressive neighborhood approximation, DSAA 2021.
  • C. Mougan, G. Kanellos, T. Gottron (2021). Desiderata for Explainable AI in statistical production systems of the European Central Ban. ECML-PKDD 2021 Workshop on BIAS.
  • P. Delobelle, K. M. Scott, S. M. Wang, M. Miceli, D. Hartmann, T. Yang, E. Murasso, & B. Berendt (2021). Time to Question if We Should: Data-Driven and Algorithmic Tools in Public Employment Services. FEAST International Workshop on Fair, Effective And Sustainable Talent Management Using Data Science ECML-PKDD 2021 Workshop, 8.
  • S. Fabbrizzi, S. Papadopoulos, E. Ntoutsi, I. Kompatsiaris (2021). A Survey on Bias in Visual Datasets.
  • C. Mougan, D. Masip, J. Nin, O. Pujol (2021): Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems, arxiv
  • K. Scott, P. Delobelle, B. Berendt (2021). Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium Using Multilingual BERT, arxiv
  • O. Lampridis, R. Guidotti, S. Ruggieri. Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars. Discovery Science (DS 2020). 357-373. Vol. 12323 of LNCS, Springer, September 2020. Honorable mention at DS 2020. (Best Paper Award)
  • T. Calders, E. Ntoutsi, M. Pechenizkiy, B. Rosenhahn, S. Ruggieri. Introduction to The Special Section on Bias and Fairness in AI. ACM SIGKDD Explorations Newsletter. Vol. 23 Issue 1, June 2021, 1-3.
  • L. State: Logic Programming for XAI: A Technical Perspective. ICLP Workshops 2021. CEUR Workshop Proceedings vol. 2970.
  • E. Ntoutsi, P. Fafalios, U. Gadiraju, V. Iosifidis, W. Nejdl, M. E. Vidal, … & I. Kompatsiaris (2020). Bias in data‐driven artificial intelligence systems—An introductory survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery.
  • E. Krasanakis, S. Papadopoulos, I. Kompatsiaris (2020). Applying Fairness Constraints on Graph Node Ranks under Personalization Bias, COMPLEX NETWORKS
Beneficiaries

Gottfried Wilhelm Leibniz Universität Hannover
GESIS
Schufa Holding AG
Centre for Research and Technology Hellas
University of Pisa
Open University
University of Southampton
KU Leuven
University of Klagenfurt

Partners

AstraZeneca
Expert System Iberia S.L.U.
Generali Italia S.p.A.
Media Gamma Limited
Ntent
Orange Labs Research
Research Institute AG & Co. KG
Vodafone Group PLC
NORD/LB
LSTECH ESPANA
University of Stuttgart
Freie Universität Berlin

Funding

The project is funded by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 860630.

Project coordinator

Prof. Dr. Wolfgang Nejdl

Leibniz University Hannover & L3S Research Center

nejdl@l3s.de

Project manager

Mr. Gourab K Patro

Leibniz University Hannover & L3S Research Center

patro@l3s.de

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