Workshop Aims and Scope
The goal is hence to favor a community-wide dialogue on new research perspectives through a workshop having the following objectives:
- Increase awareness of the algorithmic bias problem in IR.
- Identify dimensions influenced by algorithmic bias in IR.
- Solicit contributions addressing algorithmic bias in IR.
- Gain insights into recent advances and open issues in IR.
- Familiarize the IR community with current field practices.
- Uncover gaps in academic and industry research in IR.
Workshop Topics
The workshop welcomes contributions on topics about algorithmic bias in search and recommendation, focused (but not limited) to:
- Data Set Collection and Preparation:
- Studying the interplay between bias and imbalanced data.
- Designing methods for dealing with imbalances in data.
- Creating data pipelines for less biased data sets.
- Collecting data sets for the analysis of biased situations.
- Designing protocols for data sets tailored to bias analysis.
- Countermeasure Design and Development:
- Formalizing and operationalizing bias concepts.
- Conducting exploratory analysis that uncover bias.
- Designing treatments that mitigate biases.
- Devising methods for explaining biases.
- Studying causal and counterfactual reasoning for bias.
- Evaluation Protocol and Metric Formulation:
- Performing auditing studies with respect to bias.
- Conducting experimental studies on bias.
- Defining objective metrics that consider bias.
- Formulating bias-aware protocols to evaluate models.
- Evaluating mitigation strategies in unexplored domains.
- Comparative studies of existing evaluation protocols.
- Analysing scalability issues of debiasing methods.
- Case Study Exploration:
- E-commerce platforms.
- Educational environments.
- Entertainment websites.
- Healthcare systems.
- Social media.
- News platforms.
- Digital libraries.
- Job portals.
- Dating platforms.
Important Dates
- Submissions:
April 23, 2025May 8, 2025 (PASSED). - Notifications:
May 21, 2025May 29, 2025 (PASSED). - Camera-Ready: June 5, 2025 (PASSED).
- Workshop: July 17, 2025 - Padua, Italy.
All deadlines are 11:59pm, AoE time (Anywhere on Earth).
Submission Details
We invite authors to submit unpublished original papers, written in English. Submitted papers should not have been previously published or accepted for publication in substantially similar form in any peer-reviewed venue, such as journals, conferences, or workshops.
The authors should consult the Springer’s authors’ guidelines and use their proceedings templates, either LaTeX or Word.
Papers should be submitted as PDF files to Easychair at https://easychair.org/conferences/?conf=bias2025.
We will consider three different submission types:
- Full papers (12 pages) should be clearly placed with respect to the state of the art and state the contribution of the proposal in the domain of application, even if presenting preliminary results. In particular, research papers should describe the methodology in detail, experiments should be repeatable, and a comparison with the existing approaches in the literature should be made.
- Reproducibility papers (12 pages) should repeat prior experiments using the original source code and datasets to show how, why, and when the methods work or not (replicability papers) or should repeat prior experiments, preferably using the original source code, in new contexts (e.g., different domains and datasets) to further generalize and validate or not previous work (reproducibility papers).
- Short paper (6 pages) or position papers (4 pages) should introduce new point of views in the workshop topics or summarize the experience of a group in the field. Practice and experience reports should present in detail real-world scenarios in which search and recommender systems are exploited.
Submissions should not exceed the indicated number of pages, including any diagrams and references.
All submissions will go through a double-blind review process and be reviewed by at least three reviewers on the basis of relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility.
Submitted papers will be rejected without review in case they are not properly anonymized, do not comply with the template, or do not follow the above guidelines.
The accepted papers and the material generated during the meeting will be available on the workshop website. It is planned to send the workshop proceedings for consideration for inclusion as a Springer's Communications in Computer and Information Science (CCIS) revised post-proceedings volume, indexed on Google Scholar, DBLP and Scopus. The authors of selected papers may be invited to submit an extended version in a journal special issue.
Please be aware that at least one author per paper needs to register and attend the workshop to present the work.
We expect authors, the program committee, and the organizing committee to adhere to the ACM’s Conflict of Interest Policy and the ACM’s Code of Ethics and Professional Conduct.
Keynote Speakers
Prof. Shlomo Berkovsky
Professor, Macquarie University, Australia
Title: Generalisability, Transportability, and Education: Mitigating Biases in Medical Decision-Support
Abstract: Seemingly close to recommender systems, medical decision-support implies a different functionality and mode of interaction. This is primarily due to their higher-risk environment, scarce data, and higher=expertise users. This puts an emphasis on the robust design of medical AI technologies, as a means to ensure transparent and reliable performance in a range of settings. In this talk, we will discuss 2 challenges commonly faced by medical AI - generalisability and transportability -- that may lead to biases and endanger patients. We will also discuss how to educate the (non-technical, clinical) users of medical decision-support technologies about the ways to mitigate the biases.
Short Bio: Shlomo Berkovsky is the leader of the Interactive Medical AI research stream at Macquarie University. The stream focuses on the use of Artificial Intelligence and Machine Learning methods to develop usable patient models and personalised predictions of diagnosis and care. The stream also studies how clinicians and patients interact with health technologies and how Large Language Models can improve patient care. His other areas of expertise include user modelling, online personalisation, and behaviour change technologies.
Dr. Erasmo Purificato
Scientific Project Officer, European Centre for Algorithmic Transparency - European Commission’s Joint Research Centre, Italy
Title: Between Code and Compliance: Bridging Technical and Regulatory Perspectives on Algorithmic Fairness
Abstract: As AI systems increasingly influence access to information, services, and opportunities, the demand for algorithmic fairness has extended beyond academia into regulation and enforcement. The keynote will examine the changing concept of fairness in AI from two interconnected perspectives: the development of fairness-aware models, particularly within graph-based learning frameworks, and the operationalization of fairness within emerging legal and institutional structures. My talk will reflect on how technical and regulatory communities define, measure, and pursue fairness, often with different assumptions and priorities. Particular attention will be given to recent developments under the EU Digital Services Act and AI Act, as well as their implications for transparency, accountability, and risk-based auditing in algorithmic systems.
Short Bio: Erasmo Purificato is a Scientific Project Officer at the European Centre for Algorithmic Transparency (ECAT) of the European Commission’s Joint Research Centre (JRC), focusing on trustworthy algorithmic systems. He holds a Ph.D. in Computer Science from OVGU, where his research focused on the fairness analysis of graph neural networks for behavioral user modeling. Previously, he worked as a Research Assistant in the Human-Centred Artificial Intelligence group at Otto von Guericke University Magdeburg (OVGU) and the Leibniz Institute for Educational Media | Georg Eckert Institute (GEI) in Germany. He also worked as an ML Engineer at Blue Reply in Turin. Erasmo has co-organized workshops at ECIR, IUI, and CHItaly, and the IEEE Autumn School ISACT. He served as a guest editor for IJHCS and DMKD journals, on the organizing committees of conferences like RecSys and UMAP, and the program committee of several conferences, such as SIGIR, RecSys, ECIR, FAccT, UMAP, IUI, HT, and served as a reviewer for top-tier journals like IJHCS, TORS, TIST, IJHCI, and IPM.
Program
- TBD
Organization
Workshop Chairs
- Alejandro Bellogin , Universidad Autonoma de Madrid (Spain)
- Ludovico Boratto, University of Cagliari (Italy)
- Styliani Kleanthous, Open University of Cyprus (Cyprus)
- Elisabeth Lex, Graz University of Technology (Austria)
- Francesca Maridina Malloci, University of Cagliari (Italy)
- Mirko Marras, University of Cagliari (Italy)
Program Committee
- Marcelo Armentano, ISISTAN Research Institute, Argentina
- Ashwathy Ashokana, University of Nebraska Omaha, USA
- Bettina Berendt, KU Leuven, Belgium
- Glencora Borradaile, Oregon State University, USA
- Ivan Cantador, Universidad Autónoma de Madrid, Spain
- Federica Cena, University of Turin, Italy
- Vamshi Enabothala, Pinecone, USA
- Fabian Haak, TH Köln University of Applied Sciences, Germany
- Claudia Hauff, Google Research, Netherlands
- Toshihiro Kamishima, AIST, Japan
- Anastasiia Klimashevskaia, University of Bergen, Norway
- Marina Kogan, University of Utah, USA
- Matthew Lease, University of Texas at Austin, USA
- Aonghus Lawlor, University College Dublin, Ireland
- Cataldo Musto, University of Bari Aldo Moro, Italy
- Fedelucio Narducci, University of Bari Aldo Moro, Italy
- Rebekah Overdorf, University of Lausanne, Switzerland
- Panagiotis Papadakos, FORTH-ICS, Greece
- Philipp Schaer, TH Köln University of Applied Sciences, Germany
- Dimitris Sacharidis, Université libre de Bruxelles, Belgium
- Damiano Spina, RMIT University, Australia
- Antonela Tommasel, ISISTAN Research Institute, Argentina
- Marko Tkalčič, University of Primorska, Slovenia
- Eva Zangerle, University of Innsbruck, Austria
Register
Please register through the SIGIR 2025's main conference website following the instructions indicated at https://sigir2025.dei.unipd.it/registration.html.
Related Workshops
We also invite you to check out the five related workshops:
- 5th International Workshop on Algorithmic Bias in Search and Recommendation (Bias@SIGIR2024)
- 4th International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2023)
- 3rd International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2022)
- 2nd International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2021)
- 1st International Workshop on Algorithmic Bias in Search and Recommendation (Bias@ECIR2020)
Contacts
For general enquiries on the workshop, please send an email to alejandro.bellogin@uam.es, ludovico.boratto@acm.org, styliani.kleanthous@ouc.ac.cy, elisabeth.lex@tugraz.at, francescam.malloci@unica.it, mirko.marras@acm.org.