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Towards an Ethical and Data Privacy Metrology for AI-Enriched Human-Centered XR Systems
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-3283-2819
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-4814-4428
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-3128-191x
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-6920-9983
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2024 (English)In: 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2024, p. 119-124Conference paper, Published paper (Refereed)
Abstract [en]

This paper works towards an initial ontology of assessment techniques for building AI-enriched human-centered XR systems, denoted Intelligent Realities (IRs). Rather than connecting technologies, our work analyses the characteristics and requirements of IRs of being 'human-centered' and creates an ontology of techniques to assess and measure these features. To achieve this, we use an approach based on Formal Concept Analysis (FCA) to establish a concept hierarchy from a set of critical concepts in the area and their properties. The novel concept defines a metrology, i.e., a set of concepts and units of measurement that can be used to shape the architecture of human-centered XR and metaverse systems. Our work focuses particularly on the ethical and privacy needs of system design. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024. p. 119-124
Keywords [en]
data privacy, ethics, extended reality, human-centered, intelligent realities, metrology, Anonymity, Units of measurement, Assessment technique, Concept hierarchies, Formal concepts analysis, Intelligent reality, Novel concept, Ontology's, Property, Work analysis, Differential privacy
National Category
Artificial Intelligence Human Computer Interaction Computer Sciences
Identifiers
URN: urn:nbn:se:bth-27444DOI: 10.1109/MetroXRAINE62247.2024.10796457Scopus ID: 2-s2.0-85216093674ISBN: 9798350378009 (print)OAI: oai:DiVA.org:bth-27444DiVA, id: diva2:1936452
Conference
3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024, St Albans, Oct 21-23, 2024
Available from: 2025-02-11 Created: 2025-02-11 Last updated: 2025-09-30Bibliographically approved

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Hu, YanTutschku, KurtBoeva, VeselkaGoswami, PrashantAbghari, ShahroozSundstedt, Veronica

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Hu, YanTutschku, KurtBoeva, VeselkaGoswami, PrashantAbghari, ShahroozSundstedt, Veronica
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CiteExportLink to record
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Citation style
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