-------- Forwarded Message --------
------------------------------------------------------------------------
*Please forward to anyone who might be interested*
Apologies for cross-posting.
------------------------------------------------------------------------
In collaboration with Frontiers in Big Data’s special section in
Recommender Systems, we are bringing researchers together to
contribute to a Research Topic on:
*Human Issues in Recommender Systems*
Topic Editors:
* Dr. Bruce Ferwerda, Jönköping University, Jönköping, Sweden
* Dr. Christine Bauer, Utrecht University, Utrecht, The
Netherlands
https://www.frontiersin.org/research-topics/23412/human-issues-in-recommender-systems
Submissions are ongoing with the final submission deadline for
manuscripts to be considered on 31 January 2022.
------------------------------------------------------------------------
Recommendation systems (or recommender systems) have become a
pervasive ingredient in our everyday lives. Such systems assist
people to navigate immense amounts of content. In doing so,
recommenders help people find and discover various types of
content and goods, including movies, music, books, food, or dating
partners. When researching on, developing, or employing
recommender systems, we have a social responsibility to care about
the impact of their technology on individual people (this includes
the roles of users, providers, and other stakeholders) and on
society. This involves building, maintaining, evaluating, and
studying recommender systems that are fair, transparent, and
beneficial to society.
It is a combination of many aspects that make a recommender system
successful. In this Research Topic, we zoom in on humans. The goal
is to better understand humans' perceptions, needs, and the impact
that recommender systems may have on humans. For instance, the
call for fair and transparent recommenders is increasingly getting
stronger. But what is fair? What is beneficial for society? And
how can we achieve that? Early research in the field of fair and
transparent fair recommender systems has been inspired by research
in the machine learning domain, where we can observe a particular
focus on the algorithmic perspective.
With this Research Topic, we want to show the bigger picture of
the human issues, for instance, concerned with fair and
transparent recommender systems. Recommender systems have an
impact on individual people in the various roles they take (e.g.,
users, providers, and other stakeholders) and on society. What is
fair and transparent from various perspectives? How can fairness
and transparency be achieved? And how are the resulting
recommendations perceived?
We welcome original research papers addressing human issues in
recommenders, reporting research on theory and/or practice. The
type of research may include but is not limited to, explorative
studies, experiments, or methodological approaches studying human
issues.
Topics of interest related to human issues include, but are not
limited to, the following:
* Perception and expectations of stakeholders (e.g., users,
providers);
* Human factors (e.g., humans-in-the-loop);
* Humanistic theory (e.g., philosophical, moral, and ethical
analysis);
* Real-world cases and applications;
* Algorithmic development, measurement, and evaluation (e.g., bias
and discrimination);
* Data (e.g., bias and discrimination).
For more information about the Research Topic, information on
manuscript preparation, and related matters, please see:
https://www.frontiersin.org/research-topics/23412/human-issues-in-recommender-systems
Although the deadline for submission of manuscripts to this
Research Topic is 31 January 2022, papers will be reviewed and
published as they are received. Submitting an abstract before
submitting the manuscript is encouraged but not required.
We are looking forward to your contribution to the Research Topic.
Sincerely yours,
Dr. Bruce Ferwerda
Dr. Christine Bauer
(Topic Editors)
--
Dr. Christine Bauer | Assistant Professor | Department of
Information and Computing Sciences | Utrecht University |
Princetonplein 5, 3584 CC Utrecht | Buys Ballotgebouw, room 4.21 |
+31 30 253 4158 |
c.bauer@uu.nl<mailto:c.bauer@uu.nl> |
www.uu.nl/staff/CBauer<http://www.uu.nl/staff/CBauer> |
https://christinebauer.eu | Present: Mon-Fri
_______________________________________________
AISWorld mailing list
AISWorld@lists.aisnet.org