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From:
Styliani Kleanthous <[log in to unmask]>
Reply To:
Styliani Kleanthous <[log in to unmask]>
Date:
Wed, 18 Mar 2020 11:55:16 +0200
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=====================================================================
                         CALL FOR PAPERS
=====================================================================

3rd UMAP Workshop on Fairness in User Modeling, Adaptation, and
Personalization (FairUMAP 2020)

At the ACM Conference on User Modeling, Adaptation, and Personalization
(UMAP 2020)
14-17 July, 2020, Genoa, Italy

Workshops will take place on the 17th of July 2020

Workshop website:  https://fairumap.wordpress.com
Conference website: https://www.um.org/umap2020/

Please note that workshop presentations at ACM UMAP 2020 might take place
online.

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                        WORKSHOP DESCRIPTION
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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 3rd Workshop on Fairness in User Modeling, Adaptation, and
Personalization 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.

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                        TOPICS OF INTEREST
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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

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                         IMPORTANT DATES
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Submission deadline: April 9, 2020 (23:59 American Samoa Zone - UTC-11)

Notification of acceptance: April 30, 2020

Camera-ready due: May 6, 2020 (23:59 American Samoa Zone - UTC-11)

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                         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 long
research papers, minimum of 4 pages for short research papers and 2 pages
for position papers. These page limits do not include a maximum of one
additional page for references.
Papers must be formatted using the ACM SIG Standard (SIGCONF) proceedings
template: https://www.acm.org/publications/proceedings-template. 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.

Please submit your paper by using the on-line submission system via:
https://www.easychair.org/conferences/?conf=fairumap2020.

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                      WORKSHOP Organizing Committee
---------------------------------------------------------------------

Bamshad Mobasher, DePaul University, USA
Styliani Kleanthous, Open University of Cyprus
Michael Ekstrand, Boise State University, USA
Bettina Berendt, KU Leuven, Belgium
Jahna Otterbacher, Open University of Cyprus
Avital Shulner Tal, 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/

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