<div class="csl-bib-body">
<div class="csl-entry">Nalis, I., & Neidhardt, J. (2024, October 12). <i>Towards Possibility: Interdisciplinary Perspectives on Enhancing Recommender Systems Beyond Accuracy</i> [Conference Presentation]. ACM Europe School on Recommender Systems 2024, Bari, Italy. http://hdl.handle.net/20.500.12708/210789</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/210789
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dc.description.abstract
In this introductory lecture, Dr. Julia Neidhardt, Director of the CDLab for Recommender Systems and UNESCO Co-Chair in Digital Humanism, and Dr. Irina Nalis, psychologist, and interdisciplinary researcher at the CDLab, explore recommender systems from a Digital Humanism viewpoint, focusing on the intersection of technology, psychology, and societal needs. Addressing the limitations and risks of accuracy-centric metrics, they emphasize the importance of establishing new research and development methods to go beyond accuracy and towards more human-potential centered recommendations. Their lecture, based on interdisciplinary research including advanced algorithms, cross-domain recommendations, and the integration of large-language models, demonstrates the potential of recommender systems to foster diversity, serendipity, and democratic fairness. They further discuss the role of choice architecture and affordances in making responsible recommendations, highlighting the importance of aligning with broader policies like the EU Digital Services Act to meet societal needs and enrich the digital landscape.
en
dc.language.iso
en
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dc.subject
Beyond-accuracy metrics
en
dc.subject
Psychology-aware recommendation
en
dc.subject
Large Language Models
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dc.subject
Responsible Recommendation
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dc.title
Towards Possibility: Interdisciplinary Perspectives on Enhancing Recommender Systems Beyond Accuracy
en
dc.type
Presentation
en
dc.type
Vortrag
de
dc.type.category
Conference Presentation
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tuw.publication.invited
invited
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tuw.researchTopic.id
I4
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tuw.researchTopic.id
C5
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.name
Computer Science Foundations
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tuw.researchTopic.value
80
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tuw.researchTopic.value
20
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.author.orcid
0000-0001-7184-1841
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tuw.event.name
ACM Europe School on Recommender Systems 2024
en
tuw.event.startdate
08-10-2024
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tuw.event.enddate
12-10-2024
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Bari
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tuw.event.country
IT
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tuw.event.institution
ACM RecSys, SIGCHI, ACM Europe, EURAI, and University of Cagliari
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tuw.event.presenter
Nalis, Irina
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tuw.event.presenter
Neidhardt, Julia
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wb.sciencebranch
Informatik
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wb.sciencebranch
Psychologie
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5010
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wb.sciencebranch.value
70
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wb.sciencebranch.value
30
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item.openairecristype
http://purl.org/coar/resource_type/c_18cp
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item.cerifentitytype
Publications
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item.languageiso639-1
en
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item.fulltext
no Fulltext
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item.openairetype
conference paper not in proceedings
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item.grantfulltext
none
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crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.dept
E194-04 - Forschungsbereich Data Science
-
crisitem.author.orcid
0000-0001-7184-1841
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
