Artificial Intelligence without Bias

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Research documentation on accounting for bias in results [to be updated]

Research documentation on accounting for bias in results (Leader: UNIPI, participation of SCHUFA, SOTON-LS, LUH-L3S) (M24, M42): Reports on research progress and results.

Report on WP2 Integration and application [to be updated]

Report on WP2 Integration and application (Leader: CERTH, participation of OU, GESIS-CSS, LUH-IRI) (M24, M42): Reports on integration and application activities related to bias mitigation in algorithms (in collaboration with WP4).

Research documentation on mitigating bias in algorithms [to be updated]

D2.1a/b: Research documentation on mitigating bias in algorithms (Leader: OU, participation of GESIS-CSS, CERTH, LUH-IRI) (M24, M42): Reports on research progress and results.

Training Report [to be updated]

Training Report (Leader: UNI-KLU; participation: all) (M24, M48). Reports on planning and implementation of training activities and resources.

Report on use cases and applications

Report on use cases and applications (Leader: SCHUFA, participation: all) (M42). Report on the application of the NoBIAS research in real use cases.

Report on WP3 integration and application [to be updated]

Report on WP3 integration and application (Leader: SCHUFA, participation of UNIPI, SOTON-LS, LUH-L3S) (M24, M42): Reports on integration and application activities related to accounting for bias in results (in collaboration with WP4).

Report on WP1 integration and application [to be updated]

Report on WP1 integration and application (Leader: LUH-L3S, participation of GESIS-DAS, CERTH, UNIPI, KULEUVEN) (M24, M42): Reports on integration and application activities related to understanding bias in data (in collaboration with WP4).

Research documentation on understanding bias in data [to be updated]

D1.1a/b: Research documentation on understanding bias in data (Leader: KULEUVEN, participation of GESIS-DAS, CERTH, UNIPI, LUH-L3S) (M24, M42): Reports on research progress and results.

PhD Theses

PhD theses (Leader: GESIS-CSS) (>M42; participation: all). Submission of PhD dissertations (this can be also after the end of the action).

Living Document on Bias

Living Document and Book on Bias SOTONECS There is to date no established resource that combines the interdisciplinary expertise necessary to address bias in AIdriven decision making NoBIAS will deliver this resource through the establishment of a living training document that will begin with core contributions from academic partners M6 and will be developed by the NoBIAS researchers as part of the interdisciplinary training stream and ultimately be published as a book M42 This process will develop substantive knowledge of interdisciplinary approaches and generic team working and collaborative writing skills

NoBIAS Best Practices and Policy Advice

NoBIAS Policy Advice and Best Practices (UNIPI): NoBIAS will promote the proactive participation of ESRs in initiatives for policy making and best practices with the results of their research and the use cases from their secondments. This will be facilitated by UNIPI's participation in the IEEE P7003 Working Group on Algorithmic Bias Considerations . An introduction to this will be given during Summer School 1. Training of ESRs will benefit from their involvement in such and similar standardization initiatives, e.g., by exploiting outcomes like conceptualizations, methodologies, recommendations, and use cases (such as the bias taxonomy being developed in IEEE P7003).

Book on Bias

Living Document and Book on Bias (SOTON-ECS): There is to date no established resource that combines the interdisciplinary expertise necessary to address bias in AI-driven decision making. NoBIAS will deliver this resource through the establishment of a “living training document” that will begin with core contributions from academic partners (M6) and will be developed by the NoBIAS researchers as part of the interdisciplinary training stream and ultimately be published as a book (M42). This process will develop substantive knowledge of interdisciplinary approaches and generic team working and collaborative writing skills.

NoBias Testbed

NoBIAS testbed (LUH-L3S): NoBIAS will create an integrated technology testbed as a crystallization point for the methods and algorithms developed in the project. It will support the evaluation of methods developed in the IRPs in a larger context, foster collaboration, and integrate results from all projects. The testbed will include an open source library of algorithms and methods developed during the project, fostering openness and reproducibility, and facilitating research on related problems.

Dissemination report [to be updated]

Dissemination Report Leader LUHL3S participation all M24 M48 Reports on the setup of the project website and social media accounts implementation of the dissemination strategy planning and implementation of the projectrelated events and activities

Publicaciones

Declarative Reasoning on Explanations Using Constraint Logic Programming

Autores: Laura State; Salvatore Ruggieri; Franco Turini
Publicado en: Logics in Artificial Intelligence, JELIA 2023, 2023, Página(s) 132-141, ISBN 9783031436185
Editor: Springer Science and Business Media Deutschland GmbH
DOI: 10.1007/978-3-031-43619-2_10

Explanation Shift: Detecting distribution shifts on tabular data via the explanation space

Autores: https://arxiv.org/abs/2210.12369
Publicado en: 2022
Editor: Neural Information Processing Systems (NeurIPS 2022). Workshop on Distribution Shifts: Connecting Methods and Applications

Counterfactual Situation Testing: Uncovering Discrimination under Fairness given the Difference

Autores: Salvatore Ruggieri, Jose Manuel Alvarez
Publicado en: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization 2023, 2023
Editor: ACM

Enhancing Fairness through Reweighting: A Path to Attain the Sufficiency Rule

Autores: Xuan Zhao, Klaus Broelemann, Salvatore Ruggieri and Gjergji Kasneci
Publicado en: European Conference on Artificial Intelligence, ECAI 2024, 2024
Editor: Accepted for publication
DOI: 10.48550/arxiv.2408.14126

Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy

Autores: Ghodsi, Siamak; Ntoutsi, Eirini
Publicado en: Edición 1, 2023
Editor: CEUR Workshop Proceedings

Logic programming for XAI: A technical perspective

Autores: Laura State
Publicado en: ICLP Workshops, volume 2970 of CEUR Workshop Proceedings, Edición 1, 2021
Editor: CEUR-WS.org

Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems

Autores: Carlos Mougan; David Masip; Jordi Nin; Oriol Pujol
Publicado en: Modeling Decisions for Artificial Intelligence, Edición 5, 2021
Editor: Springer
DOI: 10.1007/978-3-030-85529-1_14

How to Data in Datathons

Autores: Mougan, Carlos; Plant, Richard; Teng, Clare; Bazzi, Marya; Cabrejas-Egea, Alvaro; Chan, Ryan Sze-Yin; Jasin, David Salvador; Stoffel, Martin; Whitaker, Kirstie Jane; Manser, Jules
Publicado en: Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks., Edición 1, 2023
Editor: Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks
DOI: 10.48550/arxiv.2309.09770

Desiderata for Explainable AI in statistical production systems of the European Central Bank

Autores: Carlos Mougan, Georgios Kanellos, Thomas Gottron
Publicado en: Workshop on bias and fairness in AI at ECMLPKDD, Edición 1, 2021
Editor: Springer International Publishing
DOI: 10.1007/978-3-030-93736-2_42

Can We Trust Fair-AI?

Autores: Ruggieri S.; Alvarez J. M.; Pugnana A.; State L.; Turini F.
Publicado en: AAAI Conference on Artificial Intelligence, AAAI 2023, 2023, Página(s) 15421-15430, ISBN 9781577358800
Editor: AAAI Press
DOI: 10.1609/aaai.v37i13.26798

Reason to Explain: Interactive Contrastive Explanations (REASONX)

Autores: Laura State, Salvatore Ruggieri, Franco Turini
Publicado en: World Conference on eXplainable Artificial Intelligence 2023, 2023
Editor: Springer Nature

Algorithmic Tools in Public Employment Services: Towards a Jobseeker-Centric Perspective

Autores: Kristen M. Scott, Sonja Mei Wang, Milagros Miceli, Pieter Delobelle, Karolina Sztandar-Sztanderska, Bettina Berendt
Publicado en: 2022 ACM Conference on Fairness, Accountability, and Transparency, 2023
Editor: ACM
DOI: 10.1145/3531146.3534631

Careful Explanations: A Feminist Perspective on XAI

Autores: Laura State, Miriam Fahimi
Publicado en: European Workshop on Algorithmic Fairness, EWAF 2023, 2023, Página(s) -
Editor: CEUR-WS.org

Introducing explainable supervised machine learning into interactive feedback loops for statistical production system

Autores: Carlos Mougan, George Kanellos, Johannes Micheler, Jose Martinez, Thomas Gottron
Publicado en: Irving Fisher Committee (IFC) - Bank of Italy workshop on Data science in central banking: Applications and tools, 2021
Editor: Arxiv

Fairness Implications of Encoding Protected Categorical Attributes

Autores: Carlos Mougan; Jose Manuel Alvarez; Salvatore Ruggieri; Steffen Staab
Publicado en: AAAI/ACM Conference on AI, Ethics, and Society, AIES 2023, 2023, Página(s) 454-465, ISBN 9798400702310
Editor: Association for Computing Machinery, Inc
DOI: 10.1145/3600211.3604657

The Explanation Dialogues: Understanding How Legal Experts Reason About XAI Methods

Autores: Laura State, Alejandra Bringas Colmenarejo, Andrea Beretta, Salvatore Ruggieri, Franco Turini, Stephanie Law
Publicado en: European Workshop on Algorithmic Fairness, EWAF 2023, 2023, ISBN 161300733442
Editor: CEUR Workshop Proceedings

Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric Measure

Autores: Alaa Elobaid, Nathan Ramoly, Lara Younes, Symeon Papadopoulos, Eirini Ntoutsi, Ioannis Kompatsiaris
Publicado en: 2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG), Edición 2, 2024, Página(s) 1-9
Editor: IEEE
DOI: 10.1109/fg59268.2024.10582012

The Role of Large Language Models in the Recognition of Territorial Sovereignty: An Analysis of the Construction of Legitimacy

Autores: Francisco Castillo-Eslava; Carlos Mougan; Alejandro Romero-Reche; Steffen Staab
Publicado en: Edición 1, 2023
Editor: European Workshop on Algorithmic Fairness (EWAF'23)
DOI: 10.48550/arxiv.2304.06030

Link recommendations: Their impact on network structure and minorities

Autores: Antonio Ferrara, Lisette Espin-Noboa, Fariba Karimi, Claudia Wagner
Publicado en: 14th ACM Web Science Conference 2022, 2023
Editor: ACM
DOI: 10.1145/3501247.3531583

Counterfactual Explanation for Regression via Disentanglement in Latent Space

Autores: Xuan Zhao, Klaus Broelemann, Gjergji Kasneci
Publicado en: 2023 IEEE International Conference on Data Mining Workshops (ICDMW), 2024
Editor: IEEE
DOI: 10.1109/icdmw60847.2023.00130

Time to Question if We Should: Data-Driven and Algorithmic Tools in Public Employment Services

Autores: Pieter Delobelle, Kristen M. Scott, Sonja Mei Wang, Milagros Miceli, David Hartmann, Tianling Yang, Elena Murasso, Karolina Sztandar-Sztanderska, Bettina Berendt
Publicado en: International workshop on Fair, Effective And Sustainable Talent management using data science, 2021
Editor: FEAST Workshop

Estimating Ground Truth in a Low-labelled Data Regime: A Study of Racism Detection in Spanish

Autores: Paula Reyero Lobo, Martino Mensio, Angel Pavon Perez, Vaclav Bayer, Joseph Kwarteng, Miriam Fernandez, Enrico Daga, Harith Alani
Publicado en: 2022
Editor: AAAI

Fairness in Agreement With European Values

Autores: Alejandra Bringas Colmenarejo, Luca Nannini, Alisa Rieger, Kristen M. Scott, Xuan Zhao, Gourab K Patro, Gjergji Kasneci, Katharina Kinder-Kurlanda
Publicado en: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2023
Editor: ACM
DOI: 10.1145/3514094.3534158

Explainability in Practice: Estimating Electrification Rates from Mobile Phone Data in Senegal

Autores: Laura State; Hadrien Salat; Stefania Rubrichi; Zbigniew Smoreda
Publicado en: World Conference on eXplainable Artificial Intelligence, xAI 2023, 2023, Página(s) 110-125, ISBN 9783031440663
Editor: Springer Science and Business Media Deutschland GmbH
DOI: 10.1007/978-3-031-44067-0_6

Bias in Hate Speech and Toxicity Detection

Autores: Paula Reyero Lobo
Publicado en: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2023
Editor: ACM
DOI: 10.1145/3514094.3539519

Causal Fairness-Guided Dataset Reweighting using Neural Networks

Autores: Zhao X.; Broelemann K.; Ruggieri S.; Kasneci G.
Publicado en: IEEE International Conference on Big Data (BigData 2023), 2023, Página(s) 1386-1394, ISBN 9798350324464
Editor: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/bigdata59044.2023.10386836

Constructing Meaningful Explanations: Logic-based Approaches

Autores: Laura State
Publicado en: AAAI/ACM Conference on AI, Ethics, and Society, AIES 2022, 2022, Página(s) 916, ISBN 978-1-4503-9247-1
Editor: ACM
DOI: 10.1145/3514094.3539544

Domain Adaptive Decision Trees: Implications for Accuracy and Fairness

Autores: Jose M. Alvarez, Kristen M. Scott, Salvatore Ruggieri, Bettina Berendt
Publicado en: ACM Conference on Fairness, Accountability, and Transparency 2023, 2023
Editor: ACM

A Survey on Bias in Visual Datasets

Autores: Simone Fabbrizzi, Symeon Papadopoulos, Eirini Ntoutsi, Ioannis Kompatsiaris
Publicado en: Edición 1, 2021
Editor: Arxiv

A Causal Framework for Evaluating Deferring Systems

Autores: Filippo Palomba, Andrea Pugnana, José M. Álvarez, Salvatore Ruggieri
Publicado en: 2024
Editor: Unpublished manuscript
DOI: 10.48550/arxiv.2405.18902

Beyond Demographic Parity: Redefining Equal Treatment

Autores: Carlos Mougan, Laura State, Antonio Ferrara, Salvatore Ruggieri, Steffen Staab
Publicado en: 2023
Editor: Unpublished manuscript

The Initial Screening Order Problem

Autores: Jose M. Alvarez, Antonio Mastropietro, Salvatore Ruggieri
Publicado en: 2023
Editor: Unpublished manuscript

Semantic Web Technologies and Bias in Artificial Intelligence: A Systematic Literature Review

Autores: Paula Reyero Lobo, Enrico Daga, Harith Alani, Miriam Fernandez
Publicado en: Semantic Web Journal, 2021
Editor: Semantic Web Journal

Uncovering Algorithmic Discrimination: An Opportunity to Revisit the Comparator

Autores: José M. Álvarez, Salvatore Ruggieri
Publicado en: 2024
Editor: Unpublished manuscript
DOI: 10.48550/arxiv.2405.13693

Context matters for fairness -- a case study on the effect of spatial distribution shifts

Autores: Siamak Ghodsi, Harith Alani, Eirini Ntoutsi
Publicado en: 2022
Editor: Unpublished manuscript

Causal Perception

Autores: Alvarez, Jose M.; Ruggieri, Salvatore
Publicado en: 2024
Editor: Unpublished manuscript
DOI: 10.48550/arxiv.2401.13408

Data Privacy Issues in Big Biomedical Data

Autores: Maria-Esther Vidal, Mayra Russo, Philipp Rohde
Publicado en: 2021
Editor: Nomos Verlagsgese llschaft

Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts

Autores: José Alberto Benítez-Andrades, María Teresa García-Ordás, Mayra Russo, Ahmad Sakor, Luis Daniel Fernandes Rotger, Maria-Esther Vidal
Publicado en: Semantic Web, Edición 14, 2023, Página(s) 873-892, ISSN 1570-0844
Editor: IOS Press
DOI: 10.3233/sw-223269

Bias-aware ranking from pairwise comparisons

Autores: Antonio Ferrara, Francesco Bonchi, Francesco Fabbri, Fariba Karimi, Claudia Wagner
Publicado en: Data Mining and Knowledge Discovery, Edición 38, 2024, Página(s) 2062-2086, ISSN 1384-5810
Editor: Kluwer Academic Publishers
DOI: 10.1007/s10618-024-01024-z

Supporting Online Toxicity Detection with Knowledge Graphs

Autores: Paula Reyero Lobo, Enrico Daga, Harith Alani
Publicado en: Proceedings of the International AAAI Conference on Web and Social Media, Edición 16, 2022, Página(s) 1414-1418, ISSN 2334-0770
Editor: AAAI Press
DOI: 10.1609/icwsm.v16i1.19398

Explaining short text classification with diverse synthetic exemplars and counter-exemplars

Autores: Orestis Lampridis, Laura State, Riccardo Guidotti, Salvatore Ruggieri
Publicado en: Machine Learning, 2022, ISSN 2730-9916
Editor: Springer

Policy advice and best practices on bias and fairness in AI

Autores: Jose M. Alvarez; Alejandra Bringas Colmenarejo; Alaa Elobaid; Simone Fabbrizzi; Miriam Fahimi; Antonio Ferrara; Siamak Ghodsi; Carlos Mougan; Ioanna Papageorgiou; Paula Reyero; Mayra Russo; Kristen M. Scott; Laura State; Xuan Zhao; Salvatore Ruggieri
Publicado en: Ethics and information technology, Edición 26, 2024, Página(s) 31, ISSN 1572-8439
Editor: Springer
DOI: 10.1007/s10676-024-09746-w

Predicting and explaining employee turnover intention

Autores: Matilde Lazzari; Jose M. Alvarez; Salvatore Ruggieri
Publicado en: International Journal of Data Science and Analytics, Edición 14, 2022, Página(s) 279–292, ISSN 2364-4168
Editor: Springer
DOI: 10.1007/s41060-022-00329-w

Monitoring Model Deterioration with Explainable Uncertainty Estimation via Non-parametric Bootstrap

Autores: Carlos Mougan, Dan Saattrup Nielsen
Publicado en: Proceedings of the AAAI Conference on Artificial Intelligence, Edición 37, 2023, Página(s) 15037-15045, ISSN 2374-3468
Editor: AAAI Press
DOI: 10.1609/aaai.v37i12.26755

Measuring Shifts in Attitudes Towards COVID-19 Measures in Belgium

Autores: Kristen Scott, Pieter Delobelle, Bettina Berendt
Publicado en: Computational Linguistics in the Netherlands Journal, Edición 11, 2021, Página(s) 161 - 171, ISSN 2211-4009
Editor: Computational Linguistics in the Netherlands

Studying bias in visual features through the lens of optimal transport

Autores: Simone Fabbrizzi, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi
Publicado en: Data Mining and Knowledge Discovery, Edición 38, 2024, Página(s) 281-312, ISSN 1384-5810
Editor: Kluwer Academic Publishers
DOI: 10.1007/s10618-023-00972-2

Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering

Autores: Siamak Ghodsi, Seyed Amjad Seyedi, Eirini Ntoutsi
Publicado en: Lecture Notes in Computer Science, Advances in Knowledge Discovery and Data Mining, 2024, Página(s) 284-296
Editor: Springer Nature Singapore
DOI: 10.1007/978-981-97-2242-6_23

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