2nd CfP - ACM UMAP Workshop - Fourth Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2021)

3 views
Skip to first unread message

Styliani Kleanthous

unread,
Mar 30, 2021, 1:45:40 PMMar 30
to

Apologies in advance for crossposting


=====================================================================

                        CALL FOR PAPERS

=====================================================================

Fourth Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2021)

At the ACM Conference on User Modeling, Adaptation, and Personalization (UMAP 2021)

Utrecht, the Netherlands & Online, June 21-25, 2021

 

Workshop website: https://fairumap.wordpress.com/

Conference website: https://www.um.org/umap2021/index.php

---------------------------------------------------------------------

                       WORKSHOP DESCRIPTION

---------------------------------------------------------------------

Personalization has become a ubiquitous and essential part of systems that help users find relevant information in today's highly complex information-rich online environments. Machine learning, recommender systems, and user modeling are key enabling technologies that allow intelligent systems to learn from users and adapt their output to users' needs and preferences. However, there has been a growing recognition that these underlying technologies raise novel ethical, legal, and policy challenges.  It has become apparent that a single-minded focus on the user preferences has obscured other important and beneficial outcomes such systems must be able to deliver. System properties such as fairness, transparency, balance, openness to diversity, and other social welfare considerations are not captured by typical metrics based on which data-driven personalized models are optimized. Indeed, widely-used personalization systems in such popular sites such as Facebook, Google News and YouTube have been heavily criticized for personalizing information delivery too heavily at the cost of these other objectives.

Bias, fairness, and transparency in machine learning are topics of considerable recent research interest. However, more work is needed to expand and extend this work into algorithmic and modeling approaches where personalization and user modeling are of primary importance. In particular, it is essential to address these challenges from the standpoint of understanding stereotypes in users’ behaviors and their influence on user or group decisions.

 

The Workshop on Fairness in User Modeling, Adaptation, and Personalization 2021 aims to bring together experts from academia and industry to discuss ethical, social, and legal concerns related to personalization and user modeling with the goal of exploring a variety of mechanisms and modeling approaches that help mitigate bias and achieve fairness in personalized systems.

---------------------------------------------------------------------

                       TOPICS OF INTEREST

---------------------------------------------------------------------

Topics of interest include, but are not limited to the following.

- Bias and discrimination in user modeling, personalization and recommendation

- Computational techniques and algorithms for fairness-aware personalization

- Definitions, metrics and criteria for optimizing and evaluating fairness-related aspects of personalized systems

- Data preprocessing and transformation methods to address bias in training data

- User modeling approaches that take fairness and bias into account

- User studies and other empirical studies to evaluate impact of personalization on fairness, balance, diversity, and other social welfare criteria

- Balancing needs of multiple stakeholders in recommender systems and other personalized systems

- "Filter bubble" or "balkanization" effects of personalization

- Transparent and accurate explanations for recommendations and other personalization outcomes

---------------------------------------------------------------------

                        IMPORTANT DATES

---------------------------------------------------------------------

Submission deadline: March 31, 2021 (23:59 American Samoa Zone - UTC-11)

Notification of acceptance: April 19, 2021

Camera-ready due: May 7, 2021 (23:59 American Samoa Zone - UTC-11)

---------------------------------------------------------------------

                        PAPER SUBMISSION

---------------------------------------------------------------------

Research papers reporting original results as well as position papers proposing novel and ground-breaking ideas pertaining to the workshop topics are solicited.

Manuscripts must be in English with a maximum length of 8 pages for research papers and 4 pages for position papers (with a maximum of one additional page for references). Papers must be formatted according to the new workflow for ACM publications. The templates and instructions are available here: https://www.acm.org/publications/taps/word-template-workflow.


Authors should submit their papers as single-column PDF files following the templates:
LaTeX (use \documentclass[manuscript,review,anonymous]{acmart} in the sample-authordraft.tex file for single-column): https://www.acm.org/binaries/content/assets/publications/consolidated-tex-template/acmart-primary.zip
Overleaf (use \documentclass[manuscript,review,anonymous]{acmart} for single-column): https://www.overleaf.com/latex/templates/acm-conference-proceedings-master-template/pnrfvrrdbfwt
MS Word: https://www.acm.org/binaries/content/assets/publications/taps/acm_submission_template.docx  

Research papers should be submitted electronically as a single PDF file through the EasyChair submission system  by selecting the track "Workshop-Fair" (https://easychair.org/conferences/?conf=acmumap2021). Accepted papers will be published by ACM and will be available via the ACM Digital Library.

 

Accepted papers will be either presented as a talk or poster (to be determined).

At least one author of each accepted paper must attend the workshop and present the paper.

---------------------------------------------------------------------

                     WORKSHOP Organizing Committee

---------------------------------------------------------------------

Bamshad Mobasher, DePaul University, USA

Styliani Kleanthous, Cyprus Center for Algorithmic Transparency (CyCAT), Open University of Cyprus

Robin Burke, University of Colorado, Boulder, USA

Jahna Otterbacher, Cyprus Center for Algorithmic Transparency (CyCAT), Open University of Cyprus

Bettina Berendt, KU Leuven, Belgium

Tsvi Kuflik, University of Haifa, Israel

Avital Shulner, University of Haifa, Israel


--


Styliani Kleanthous, Ph.D

CyCAT - Cyprus Center for Algorithmic Transparency

Open University of Cyprus

Phone: 22411904

web: http://www.cycat.io

LinkedIn: https://www.linkedin.com/in/styliani-kleanthous/


Reply all
Reply to author
Forward
0 new messages