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EWAF 2025 : European Workshop on Algorithmic Fairness

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Link: https://2025.ewaf.org/
 
When Jun 30, 2025 - Jul 2, 2025
Where Eindhoven, The Netherlands
Submission Deadline Mar 13, 2025
Notification Due May 5, 2025
Categories    machine learning   algorithmic fairness   ethics   artificial intelligence
 

Call For Papers

We are excited to invite submissions (full papers and extended abstracts) for the fourth European Workshop on Algorithmic Fairness (EWAF’25) (https://2025.ewaf.org/), which will be held from June 30 - July 2 2025 in Eindhoven, The Netherlands.

Important Dates
Submission deadline: Thursday, March 13, 2025 (AoE)
Acceptance notifications: Monday, May 5, 2025
Workshop dates: June 30 - July 2, 2025

More information
Call for Papers: https://2025.ewaf.org/submitting/call-for-papers
LinkedIn: https://www.linkedin.com/company/eaaf/
X: https://x.com/EWAFWorkshop
Bluesky: https://bsky.app/profile/ewafworkshop.bsky.social

About the Workshop
EWAF aims to foster dialogue between researchers working on algorithmic fairness in the context of Europe’s legal and societal framework, especially in light of the European Union’s attempts to promote ethical AI and the turn to AI for the common good.

EWAF welcomes submissions from multiple disciplines, including but not limited to computer science, law, philosophy, and social science, as well as interdisciplinary and transdisciplinary work. One of the primary goals of EWAF is to build a community and we encourage all participants to actively partake, e.g. by submitting an extended abstract of ongoing or recently published work. If you are planning to join us in Eindhoven, we strongly encourage you to make a submission!

Topics
We welcome submissions from the following areas:
Computer Science: fairness metrics, methods for qualitative evaluations, bias mitigation techniques, auditing frameworks, fairness-aware data collection
Philosophy: values embedded in distributive and procedural fairness, foundations of ethical AI, critical studies on AI
Social Sciences AI impact assessments, historical perspectives on discrimination, impact of algorithms on marginalized groups, perceptions of (un)fairness, AI and labor, digital governance, management and fairness, AI for public value creation
Policy and Law: non-discrimination law, data protection law and data governance, impact assessments, accountability measures, sensitive application areas of AI (e.g., the judiciary, government, law enforcement, public services), global regulatory developments)

We also explicitly welcome submissions of interdisciplinary and transdisciplinary work, sourcing from multiple disciplinary areas and/or highlighting joint insight-building with relevant non-academic stakeholders.

A non-exhaustive list of themes includes:
Industry experiences in developing and implementing fairness interventions, developing standards and practical approaches to introducing fairness in digital innovation governance.
Empirical and theoretical perspectives from social sciences on fairness and discrimination in Europe (e.g., analysis of labor markets, the concepts of class, race, disability, and discrimination against minorities in different social contexts, intersectional inequality).
Case studies based on concrete European instances of algorithmic design and regulation that machine learning scholars or practitioners have encountered in their work (e.g., datasets or audits of automated decision-making systems that are used in Europe).
An analysis of the implications of the European legislative framework for the debate on fairness in machine learning and AI more broadly (e.g., specificities connected to anti-discrimination and data collection legislation and the emerging regulatory frameworks for platforms and AI).
Principled arguments for certain fairness concepts and measures in specific contexts.
Implementing fairness in deployed systems, selecting fairness definitions and designing auditing processes.
Explorations of the relationship and trade-offs between fairness and transparency in practice.
Fairness and transparency of black-box models.
Generative AI and fairness, esp. relating to the job market and the data supply chain.

We also welcome submissions without a focus on European specificity or tackling other themes related to algorithmic fairness.

Submission information
Authors can choose between submitting a full paper or an extended abstract. For more details, please see the call for papers on our website: https://2025.ewaf.org/submitting/call-for-papers#h.dvmzku61yha8

Organization
Ana Maria Corrêa Harcus, KU Leuven (Belgium)
Doris Alhutter, Austrian Academy of Sciences (Austria)
Thomas Grote, University of Tübingen (Germany)
Cynthia Liem, Delft University of Technology (The Netherlands)
Mykola Pechenizkiy, Eindhoven University of Technology (The Netherlands)
Hilde Weerts, Eindhoven University of Technology (The Netherlands)

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